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Trump wants $95 billion more for his Iran war while oil giants cash in — and DNI pick Jay Clayton confesses to victimizing Epstein's victims. In this episode: • Hegseth testifies war money runs dry by August 1 — demands $87 to $95 billion more on top of a nearly $1 trillion budget • Hegseth admits $37.7 billion already spent, then warns we're low on ammo on camera • US bombing hits civilian desalination systems — 10,000 Iranians without drinking water • Oil near $90 a barrel, gas near $4 — Chevron, Exxon, ConocoPhillips feast while Hormuz stays shut • Jay Clayton clears committee 9–8 for Director of National Intelligence after he spilled Epstein victims' names, addresses, and photos • Clayton won't say Biden won 2020 — and shrugs at Tulsi helping seize Fulton County ballots • Tillis and Cornyn freeze Todd Blanche's Attorney General path after Epstein survivor meeting left victims more traumatized • Cornyn holds Kari Lake and Mastriano ambassadorships hostage over PEPFAR AIDS funding — Lancet warns 14 million dead if cuts stand, one third children • Ed Martin's pardon office ignores nearly 6,000 pleas for clemency so he can free Trump donors and Clean Air Act polluters • Sunny Hostin's Harvard grad son handcuffed jogging in New Rochelle Key figures covered: Donald Trump, Pete Hegseth, Jay Clayton, Todd Blanche, Thom Tillis, Jon Cornyn, Kari Lake, Ed Martin, Kash Patel, Chelsi "Sunny" Hostin Subscribe for live shows Sunday, Tuesday, and Thursday at 6:05 PM Eastern. Recorded live on the David Feldman Show July 21, 2026 #IranWar #EpsteinFiles #ToddBlanche #PeteHegseth #Trump #JayClayton #PEPFAR #WarSupplemental #OilPrices #DavidFeldmanShow

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

A Presidential Pardon closed one chapter—but according to today's guest, the conversation about diesel emissions enforcement is far from over. On this episode of The Diesel Podcast, I sit down with Jon Achtemeier who was convicted of Clean Air Act violations, served four months in federal prison, and was granted a Presidential Pardon this July. Whether you own a Cummins, Duramax, Powerstroke, operate a diesel repair shop, or simply want to understand how federal emissions enforcement has affected the diesel industry, this episode provides a firsthand perspective from someone who lived through it. Learn more about your ad choices. Visit megaphone.fm/adchoices

Wade LaLone of Diesel Freak shares his story on today's episode. He takes us through the day EPA officials and law enforcement arrived at his shop, the years of uncertainty that followed, his federal felony conviction under the Clean Air Act, and ultimately receiving a Presidential Pardon. We discuss the emotional toll the case took on him, his family, and the diesel community, as well as why he says the pardon gave him the opportunity to move forward with his life. ➨ BECOME A PATREON: https://www.patreon.com/thedieselpodcast -------------------------------- Protect your privacy with ExpressVPN: Get 4 extra months FREE! Go to: https://www.expressvpn.com/diesel -------------------------------- 20% off HOT SHOT'S SECRET with code: DIESELPOD20 https://www.hotshotsecret.com/shop/ -------------------------------- 20% OFF KERSHAW KNIVES with code: TDP4020266 Discount code valid until September 1, 2026 20% off your entire cart at Kershaw Knives with code: TDP4020266 FREE Shipping over $50 *Offer valid through 9/1/26 at 11:59 pm Pacific. Discount is applied before tax and shipping. The discount code must be added at the time of checkout, it cannot be added retroactively. The discount is off entire cart. No substitutes, backorders, or additional discounts can be applied.* https://kershaw.kaiusa.com/ Learn more about your ad choices. Visit megaphone.fm/adchoices

Ieri le è stata ridotta la condanna che le impediva di presentarsi e quindi potrà candidarsi regolarmente alle elezioni presidenziali 2027 come leader del Rassemblament National, il partito di estrema destra francese.  Impunità per chi inquina: Trump ha concesso la grazia presidenziale a 11 persone che avevano violato il Clean Air Act, la norma sulle emissioni. Mentre le più grandi aziende fossili al mondo puntano a aumentare ancora le estrazioni di fossili nei prossimi anni.  Copenaghen è risultata di nuovo la città con la più alta qualità della vita tra le oltre 170 analizzate. A chiudere il podio Vienna e Melbourne.    Rassegna stampa:  Copenaghen si conferma la città più vivibile al mondo  Learn more about your ad choices. Visit megaphone.fm/adchoices

Donate (no account necessary) | Subscribe (account required) Join Bryan Dean Wright, former CIA Operations Officer, as he dives into today's top stories shaping America and the world. In this daily briefing of The Wright Report, Bryan opens with a growing political and medical mystery around Senator Mitch McConnell, followed by a disturbing update on Maine Senate candidate Graham Platner facing a new rape allegation that is finally splitting his Democrat support. From there, Bryan covers a quiet but aggressive surge in deportations under the Trump Administration, new pardons for diesel mechanics caught up in Clean Air Act prosecutions, and an immigration fraud case involving a California teacher who married for political reasons. He also breaks down the FBI's deep dive into Fulton County election records, Toyota's decision to bring truck production back to Texas, and the backlash over Hollywood's casting choices in its new Odyssey remake. Plus, China flexes a new submarine-launched missile test in the Pacific, African fishermen cry out against Chinese trawlers destroying their livelihoods, a possible new US and Israeli drone base takes shape in Somaliland, and fresh research links blood sugar levels to brain aging and disease. "And you shall know the truth, and the truth shall make you free." - John 8:32   Keywords: Mitch McConnell health, Graham Platner rape allegation, Maine Senate race, Susan Collins, Trump deportations, ICE, DHS Markwayne Mullin, diesel mechanic pardons, Clean Air Act, Laura Pinho immigration fraud, Fulton County Georgia FBI investigation, 2020 election, Toyota Tacoma Texas, reindustrialization, tariffs, The Odyssey movie backlash, Hollywood DEI, Xi Jinping missile test, Pacific nuclear triad, Australia Pacific security, China fishing fleet Africa, Sierra Leone fishermen, Somaliland drone base, US Israel military base, Red Sea Houthis, Ilhan Omar, blood sugar brain aging, keto diet brain health

From Q-Anon nuttiness to JD Vance's “Deep State” quackery, wacko right-wing conspiracies have oozed into the center Republican politics.But don't let their goofiness obscure the fact that there is indeed a very real plot to rig America's economic and political system, causing wealth and power to flow uphill – from the workaday majority to moneyed elites.This rigging is not done by some cartoonish cabal of ogres in a secret lair, but by prominent AI tech barons and other Poo-Bahs of America's corporate royalty. They are soft-handed thieves, discreetly robbing us from the cozy confines of corporate boardrooms, ornate courtrooms, and legislative backrooms. Why should they dirty their hands in public scuffles with workers, consumers, local communities, and others “pests” when they can deploy public officials to do their grub work.Consider the gabillionaire huckster, Elon Musk. He barged into Mississippi to build a massive AI data center that would have 57 gas turbines spewing toxic pollution over several Black neighborhoods – without even bothering to get required environmental permits.It was a gross violation of the Clean Air Act – so the endangered families sued in April to stop the imperious profiteer.But instead of facing the perp himself – Surprise! – the locals were confronted by federal lawyers deployed by Trump to kill the people's lawsuit and protect Musk's toxic project. Going further, Trump's “Justice” department asserted that we citizens have no legal right to pursue Clean Air enforcement if the federal government objects.Did I mention that Musk gave $157 million to Trump's last election campaign? And that's how the system gets rigged against us.Do something!Support the people fighting Musk in this lawsuit:* NAACP* Southern Environmental Law Center* EarthjusticeJim Hightower's Lowdown is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit jimhightower.substack.com/subscribe

Tuesday July 7, 2026 Trump Pardons Violators of the Clean Air Act and a Major Donor

Mary and Andrew start with a deeper dive into the Supreme Court's decision to allow the removal of Temporary Protected Status designations from over 330,000 immigrants from Haiti and Syria — a consequential ruling that affects TPS holders well beyond those who brought the case, leaving over a million people vulnerable to removal. As Andrew notes, this case was based on two claims: one being a statutory challenge that DHS didn't follow the procedures set out by Congress, and the other a constitutional equal protection claim that this TPS status removal was “motivated in part by race” — both of which were struck down 6-3. Then, a look at Trump's latest retribution efforts including the heavy sentences doled out over a protest that ended in a shooting outside the ICE Prairieland Detention Center inTexas one year ago; a felony indictment of former Olympian David Hearn for allegedly tearing part of the liner of the Lincoln Memorial Reflecting Pool; and former CIA Director John Brennan going on offense to challenge the DOJ's investigation into him. Plus, Mary and Andrew analyze the DOJ's response to a “show cause” order to unredact some of the Epstein files in a lawsuit filed by journalist Katie Phang. Sign up for MS NOW Premium on Apple Podcasts to listen to this show and other MS podcasts without ads. You'll also get exclusive bonus content from this and other shows. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Headlines have been popping up since Friday that Trump may consider adding Sean Diddy Combs to his pardon list in honor of our nation’s 250th anniversary. Trump reportedly wants to pardon 250 people for our 250th celebrations. On Friday, Trump pardoned 11 people, most of whom were convicted on emissions violations of the Clean Air Act, but the question remains will he pardon more in the coming days. Diddy’s release date has already been moved up at third time, to February of 2028, but he also has a pending appeal that could either vacate his conviction or drastically reduce his sentencing. That appeals court decision could come at any time, with one of the judges acknowledging it is “an exceptionally difficult case.”See omnystudio.com/listener for privacy information.

Headlines have been popping up since Friday that Trump may consider adding Sean Diddy Combs to his pardon list in honor of our nation’s 250th anniversary. Trump reportedly wants to pardon 250 people for our 250th celebrations. On Friday, Trump pardoned 11 people, most of whom were convicted on emissions violations of the Clean Air Act, but the question remains will he pardon more in the coming days. Diddy’s release date has already been moved up at third time, to February of 2028, but he also has a pending appeal that could either vacate his conviction or drastically reduce his sentencing. That appeals court decision could come at any time, with one of the judges acknowledging it is “an exceptionally difficult case.”See omnystudio.com/listener for privacy information.

Headlines have been popping up since Friday that Trump may consider adding Sean Diddy Combs to his pardon list in honor of our nation’s 250th anniversary. Trump reportedly wants to pardon 250 people for our 250th celebrations. On Friday, Trump pardoned 11 people, most of whom were convicted on emissions violations of the Clean Air Act, but the question remains will he pardon more in the coming days. Diddy’s release date has already been moved up at third time, to February of 2028, but he also has a pending appeal that could either vacate his conviction or drastically reduce his sentencing. That appeals court decision could come at any time, with one of the judges acknowledging it is “an exceptionally difficult case.”See omnystudio.com/listener for privacy information.

Headlines have been popping up since Friday that Trump may consider adding Sean Diddy Combs to his pardon list in honor of our nation’s 250th anniversary. Trump reportedly wants to pardon 250 people for our 250th celebrations. On Friday, Trump pardoned 11 people, most of whom were convicted on emissions violations of the Clean Air Act, but the question remains will he pardon more in the coming days. Diddy’s release date has already been moved up at third time, to February of 2028, but he also has a pending appeal that could either vacate his conviction or drastically reduce his sentencing. That appeals court decision could come at any time, with one of the judges acknowledging it is “an exceptionally difficult case.”See omnystudio.com/listener for privacy information.

The Great Smog of London: December 1952Weather With Enthusiasm — Episode 11Historical Extreme Weather Series━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━EPISODE SUMMARY━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━Five days in December 1952 turned London into a death trap. A stalled high-pressure system — an anticyclone — trapped millions of tonnes of coal smoke, sulfur dioxide, and acid particulates over the city in a dense, yellow-green fog that reduced visibility to near zero and killed thousands. This episode covers the meteorology, the human toll, the government cover-up, and the law that changed the world.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━KEY FACTS━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━Dates: December 5–9, 1952Location: London, EnglandDeath toll: ~4,000 (1952 government estimate) | ~12,000 (modern research, 2004)Injuries/illnesses: ~100,000Duration: 5 days━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━METEOROLOGICAL DETAILS━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━• December 4: anticyclone settled over windless London — created a temperature inversion• Cool stagnant air trapped below warmer air — zero wind to disperse pollutants• Daily pollutant output during the smog: 1,000 tonnes smoke particles, 140 tonnes HCl, 14 tonnes fluorine compounds, ~370 tonnes SO2 (converted to ~800 tonnes H2SO4)• Sulfuric acid formed in fog droplets — effectively acid fog breathed by millions• Coal sources: home fireplaces, Fulham/Battersea/Bankside/Greenwich/West Ham power stations, diesel buses, steam locomotives━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━GOVERNMENT RESPONSE & LEGACY━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━• Initial government report (never finalized) attributed deaths to influenza• E.T. Wilkins, Atmospheric Pollution officer, found ~12,000 total deaths through mortality tracking• Feb 1953: Labour MP Marcus Lipton raised 6,000 deaths + 25,000 sickness claims in Parliament• 1956: British Parliament passed the Clean Air Act — world's first comprehensive national air pollution law• Established smoke-free zones, restricted coal burning, offered grants to switch to gas/oil/electricity• Updated in 1968 — became global template for environmental regulation━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━SOURCES━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━• Wikipedia: Great Smog of London — https://en.wikipedia.org/wiki/Great_Smog_of_London• Britannica: Great Smog of London — https://www.britannica.com/event/Great-Smog-of-London• National Geographic: The Great Smog woke the world to coal dangers — https://www.nationalgeographic.com/history/article/great-smog-of-london-1952-coal-air-pollution-environmental-disaster• London Museum: The Great Smog of 1952 — https://www.londonmuseum.org.uk/collections/london-stories/the-great-smog-of-1952/• Met Office: The Great Smog of 1952 — https://weather.metoffice.gov.uk/learn-about/weather/case-studies/great-smog• Texas A&M GeoNews: London Fog 1952 research — https://geonews.tamu.edu/news/2016/11/london-fog-1952.php━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━HASHTAGS━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━#GreatSmog #London1952 #WeatherHistory #AirPollution #CleanAirAct #ExtremeWeather #WeatherWithEnthusiasmNew episodes every Tuesday and Thursday.Morning forecasts every day at 7 AM on Spreaker.Support the show: $5/monthBecome a supporter of this podcast: https://www.spreaker.com/podcast/weather-with-enthusiasm--4911017/support.Weather with Enthusiasm is produced by Kol Simcha Productions.New episodes drop daily (B'N)— a morning forecast at 7 AM and historical deep dives Tuesdays and Thursdays. Contact: kolsimchaproductions@outlook.comHistorical content is thoroughly researched and factually verified. After it has been factually verified it often will say so in the description. Should you find any mistakes, please email kolsimchaproductions@outlook.com so we can look into it and correct it. Not affiliated with any government agency or academic institution. Presented for educational and entertainment purposes — with meaning.Support the show — exclusive bonus episodes available to subscribers for just $2/month at spreaker.com/organization/kol-simcha

This week, Scott sat down with his Lawfare colleagues Kevin Frazier, Roger Parloff, and Molly Roberts to talk through some of the week's big news in AI, including:“Citizen Cain't.” When the NAACP sued Elon Musk's xAI under the Clean Air Act—alleging that the company built dozens of gas-fired turbines to power a data center in Mississippi without relevant air permits and exposing nearby, predominantly Black communities to harmful pollution—the Justice Department opted to do something it has never done before: it intervened in a citizen suit against a private company in order to kill it. DOJ's motion offers two theories: first, that shutting down the turbines would threaten national security because the military relies on xAI's Grok Gov model (including in relation to the Iran war) to secure the nation, and second, that the Constitution's vesting of executive power in the president means private citizens cannot enforce federal law over the executive's objection. How strong are these arguments? And what would it mean for environmental and other citizen-enforcement suits if DOJ were to prevail?“Grok the Vote.” We may be living through the first true “AI elections.” In Manhattan's NY-12 Democratic primary, more than $40 million in AI-industry and AI-safety money turned a little-known assemblyman, Alex Bores, into something of a national referendum on whether voters care about AI regulation and AI safety—though Bores ultimately lost to Micah Lasher this week. Meanwhile, overseas in Malaysia, parties are using chatbots and other AI-driven technologies to reach out to voters in new and novel ways. And just this week in Washington, a new study has concluded that frontier AI is perhaps more persuasive than ever, but also may not be as politically neutral as some suspect or one might hope. What does this all mean for democratic politics when both money and the messaging involved in our politics are increasingly shaped by AI?“Kill, Kill Switch, Kill, Kill!” The government's frontier-AI "kill switch" is now ready to have its first day in court. If you recall, a few weeks ago, the Commerce Department's Bureau of Industry and Security sent Anthropic an "Is Informed" letter ordering it to suspend all access to its Fable 5 and Mythos 5 models for any foreign nationals, including its own employees. This ultimately led Anthropic to pull access to those models for everyone within hours. But this past Monday, June 22, a technology startup called Legion LegalTech filed a lawsuit against the U.S. government alleging that it has acted in a way that is unlawful and raises a number of statutory and constitutional concerns. How strong is the legal challenge, and what does it tell us about whether courts—rather than the executive—will end up defining the government's power to switch a frontier model on and off?In object lessons, Molly sticks to the script for this week's episode with her call-out of Erik Nitsche's “Atoms for Peace” poster series for General Dynamics. Also inspired by this week's theme, Kevin dives into some “light summer reading” about technology, globalization, and the law with “Rules for a Flat World,” by Gillian Hadfield. Roger, similarly, is “unwinding” with “The Winter Warriors,” by Olivier Norek, a novel about the lesser-known David vs. Goliath story of Finland taking on the Soviet Union in 1939. And Scott says enough already! He's headed on vacation next week, and so is Rational Security. We'll be back with a new episode and a rejuvenated Scott on July 9.To receive ad-free podcasts, become a Lawfare Material Supporter at www.patreon.com/lawfare. You can also support Lawfare by making a one-time donation at https://givebutter.com/lawfare-institute.Support this show http://supporter.acast.com/lawfare. Hosted on Acast. See acast.com/privacy for more information.

This week, Scott sat down with his Lawfare colleagues Kevin Frazier, Roger Parloff, and Molly Roberts to talk through some of the week's big news in AI, including:“Citizen Cain't.” When the NAACP sued Elon Musk's xAI under the Clean Air Act—alleging that the company built dozens of gas-fired turbines to power a data center in Mississippi without relevant air permits and exposing nearby, predominantly Black communities to harmful pollution—the Justice Department opted to do something it has never done before: it intervened in a citizen suit against a private company in order to kill it. DOJ's motion offers two theories: first, that shutting down the turbines would threaten national security because the military relies on xAI's Grok Gov model (including in relation to the Iran war) to secure the nation, and second, that the Constitution's vesting of executive power in the president means private citizens cannot enforce federal law over the executive's objection. How strong are these arguments? And what would it mean for environmental and other citizen-enforcement suits if DOJ were to prevail?“Grok the Vote.” We may be living through the first true “AI elections.” In Manhattan's NY-12 Democratic primary, more than $40 million in AI-industry and AI-safety money turned a little-known assemblyman, Alex Bores, into something of a national referendum on whether voters care about AI regulation and AI safety—though Bores ultimately lost to Micah Lasher this week. Meanwhile, overseas in Malaysia, parties are using chatbots and other AI-driven technologies to reach out to voters in new and novel ways. And just this week in Washington, a new study has concluded that frontier AI is perhaps more persuasive than ever, but also may not be as politically neutral as some suspect or one might hope. What does this all mean for democratic politics when both money and the messaging involved in our politics are increasingly shaped by AI?“Kill, Kill Switch, Kill, Kill!” The government's frontier-AI "kill switch" is now ready to have its first day in court. If you recall, a few weeks ago, the Commerce Department's Bureau of Industry and Security sent Anthropic an "Is Informed" letter ordering it to suspend all access to its Fable 5 and Mythos 5 models for any foreign nationals, including its own employees. This ultimately led Anthropic to pull access to those models for everyone within hours. But this past Monday, June 22, a technology startup called Legion LegalTech filed a lawsuit against the U.S. government alleging that it has acted in a way that is unlawful and raises a number of statutory and constitutional concerns. How strong is the legal challenge, and what does it tell us about whether courts—rather than the executive—will end up defining the government's power to switch a frontier model on and off?In object lessons, Molly sticks to the script for this week's episode with her call-out of Erik Nitsche's “Atoms for Peace” poster series for General Dynamics. Also inspired by this week's theme, Kevin dives into some “light summer reading” about technology, globalization, and the law with “Rules for a Flat World,” by Gillian Hadfield. Roger, similarly, is “unwinding” with “The Winter Warriors,” by Olivier Norek, a novel about the lesser-known David vs. Goliath story of Finland taking on the Soviet Union in 1939. And Scott says enough already! He's headed on vacation next week, and so is Rational Security. We'll be back with a new episode and a rejuvenated Scott on July 9.To receive ad-free podcasts, become a Lawfare Material Supporter at www.patreon.com/lawfare. You can also support Lawfare by making a one-time donation at https://givebutter.com/lawfare-institute. Hosted on Acast. See acast.com/privacy for more information.

In a remarkable intervention, Trump's DOJ argues in a court filing that Elon Musk's Grok is too important to national security to be slowed down by environmental permitting requirements, citing its use by the military to bomb Iran thousands of times during Operation Epic Fury. The NAACP lawsuits argues that xAI's failure to obtain permits for its Memphis data centers violated the Clean Air Act and polluted a community already facing elevated asthma rates. Dina Doll reports Veracity: For up to 65% off your order, head to https://VeracityHealth.co and use code MISSTRIAL. Visit https://meidasplus.com for more! Remember to subscribe to ALL the MeidasTouch Network Podcasts: MeidasTouch: https://www.meidastouch.com/tag/meidastouch-podcast Legal AF: https://www.meidastouch.com/tag/legal-af MissTrial: https://meidasnews.com/tag/miss-trial The PoliticsGirl Podcast: https://www.meidastouch.com/tag/the-politicsgirl-podcast Cult Conversations: The Influence Continuum with Dr. Steve Hassan: https://www.meidastouch.com/tag/the-influence-continuum-with-dr-steven-hassan The Weekend Show: https://www.meidastouch.com/tag/the-weekend-show The Ken Harbaugh Show: https://meidasnews.com/tag/the-ken-harbaugh-show Majority 54: https://www.meidastouch.com/tag/majority-54 On Democracy with FP Wellman: https://www.meidastouch.com/tag/on-democracy-with-fpwellman Uncovered: https://www.meidastouch.com/tag/maga-uncovered

Introduction California Attorney General Rob Bonta has established himself to be one of California's leading legal advocates for climate accountability. Through lawsuits against big fossil fuel companies, including ExxonMobil, Shell, Chevron, BP, and ConocoPhillips, Bonta alleges that the industry misled the public about the climate impacts of their products. As federal environmental protections face increasing challenges, he has also led legal efforts against actions by the Trump administration that California argues undermine clean energy, environmental safeguards, and climate progress. Background States such as California have turned to litigation as a way to preserve environmental protections and advance climate action.Many of these efforts are led by California Attorney General Rob Bonta, whose office is currently involved in 67 lawsuits, including several focused on environmental and climate issues. Transportation remains California's largest source of greenhouse gas emissions, accounting for roughly half of the state's total emissions. In response, California adopted aggressive vehicle-emissions standards and zero-emission vehicle requirements. These standards were enabled through waivers granted under the federal Clean Air Act. Recent efforts by Congress to overturn or weaken these authorities have triggered new legal battles over the future of vehicle emissions regulation at the state level. The Supreme Court's 2007 decision in Massachusetts v. EPA held that greenhouse gases qualify as air pollutants under the Clean Air Act. The ruling ultimately led to the EPA's Endangerment Finding, the scientific and legal determination that greenhouse gas emissions harm public health and welfare. That finding became the basis for federal greenhouse-gas regulations across multiple sectors, but notably provided an avenue for transportation regulations. The Trump administration's efforts to rescind the Endangerment Finding and eliminate vehicle-emissions standards represents one of the most significant climate-policy reversals in decades. California is suing to stop the rescission. Beyond regulatory disputes, California has also pursued accountability from fossil fuel companies. In ongoing litigation against major oil producers, including ExxonMobil and Shell, the state alleges that companies misled the public for decades about the climate risks associated with fossil fuel use while continuing to promote products that contributed to rising emissions.  Advantages Litigation gives states the power to hold the federal government and companies responsible for violations of the law. By bringing cases against the federal government, states can challenge actions they believe violate environmental laws and ensure that agencies follow existing legal requirements. Lawsuits also serve as an important component of the United States' system of checks and balances, allowing courts to review government decisions and determine whether they comply with the law. Drawbacks Despite its potential benefits, litigation is often a slow and uncertain path to climate action. Court cases can take months or even years to reach a final resolution, particularly when they involve appeals that move through multiple levels of the judicial system. Critics also argue that major climate decisions are better addressed through elected legislatures than through the courts. While lawsuits can enforce existing laws, they cannot always provide the comprehensive policy solutions needed to reduce emissions at the scale required to address climate change. Bonta's Take Attorney General Rob Bonta views litigation as one of California's most effective tools for advancing climate action and protecting environmental regulations. He argues that the courts provide a venue where disputes can be evaluated based on evidence, legal precedent, and statutory authority rather than political considerations. Through lawsuits against federal actions and fossil fuel companies, Bonta hopes to give Californians a voice in legal decisions that could affect the state's environmental future. Bonta emphasizes that his office's role is not to pursue political objectives, but to uphold the law and the Constitution. According to Bonta, decisions about which cases to bring are guided by facts, legal analysis, and the state's responsibility to protect its residents. He argues that when government agencies or private companies violate environmental laws or mislead the public, the legal system provides an important mechanism for accountability. About our guest Sworn in as California's 34th Attorney General in 2021, Rob Bonta has become a leading legal advocate for California residents. As the head of the nation's largest state Department of Justice, he oversees efforts to protect consumers, defend civil rights, and enforce environmental laws. With a 80% case win rate in court Bonta continues to work hard to be the heart of California's legal justice. For a transcript, please visit climatebreak.org/advancing-climate-solutions-through-legal-action-with-rob-bonta/

Environmental law in the United States can be a double-edged sword. "I think that when people think about environmental law, very frequently what they mean is environmental protection, and what that misses is the other side of the coin, that there is a whole lot of law that is meant to exploit the environment," says law professor Brig Daniels. When Daniels and his writing partner Alejandro Camacho looked at the literature available on the development of environmental law in the United States, they found it lacking. "Most sort of focus only on environmental protection laws emerging from the 1970s or possibly the progressive era, missing frankly centuries of legal history that drove exploitation," says Camacho. They hope to remedy this with their new book, Lessons for a Warming Planet: A Vital History of US Environmental Law. From colonial expansion that deprived Native Americans of their ancestral lands to modern day battles over the Clean Air Act, Lessons for a Warming Planet offers a broad history of how environmental law has been developed. Change can happen gradually, or all at once. Camacho and Daniels have identified five different eras with dominant ideologies, some pushing towards protection and others towards exploitation. But in all eras, there were elements of both, the authors say. "It isn't just a black and white sort of binary of any of these eras," Camacho tells host Lee Rawles in this episode of the Modern Law Library. "And of course, what often happened is that an undercurrent in any given era becomes the dominant era in a subsequent era." The latest era of environmental law is one of contention, without a dominant force yet emerging. Lessons for a Warming Planet warns that either exploitation or protection could hold sway in the next era. "The thing that I hope that people understand is that looking back, one of the things that is so prevalent is that we didn't get the history that we had due to luck," says Daniels. "A big chunk of way we got our history was due to effort." In this episode of the Modern Law Library, Camacho, Daniels and Rawles discuss the Homestead Act, Cuyahoga River fires, and what Nixon really thought of pesky environmentalists. Subscribe to Modern Law Library: https://play.megaphone.fm/93wtgxnatpsubsdxwklzwq Learn more about your ad choices. Visit megaphone.fm/adchoices

There's a lot on the docket today. To pull apart the Iran “deal” framework, Mary and Andrew are joined by Tess Bridgeman, an international law expert who served as a legal advisor in the Obama administration through the 2015 nuclear deal with Iran. Tess lays out how President Trump's 14-point memorandum of understanding differs from what was brokered in 2015, and what to watch for as negotiations continue. Before she joins, the co-hosts begin by analyzing several examples of what Mary calls the Trump Justice Department's "consistent effort” to avoid judicial review: their refusal to put into a sworn declaration that they won't move forward with the “Anti-Weaponization” fund and a motion to dismiss a Clean Air Act violation lawsuit against Elon Musk's xAI data center in Mississippi. They also tackle a few instances where, contrastingly, the government has positioned itself “on the offense” this week, including an indictment of 15 protesters on a conspiracy charge against ICE and the DHS' intent to build a border wall through a holy landmark atop Mount Cristo Rey in New Mexico. Further reading: Here is the New York Times piece, Mary referred to about the Las Cruces case: A Diocese Tries to Protect Its 29-Foot Jesus From Trump's Border Wall Here is the Just Security tracker that Mary and Andrew mentioned: Immigration Habeas Tracker: Government Obstruction, Judicial Trust, and Accountability Sign up for MS NOW Premium on Apple Podcasts to listen to this show and other MS podcasts without ads. You'll also get exclusive bonus content from this and other shows. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Americans are drinking less wine, but growers say there's another reason demand is down for California grapes. It's a law that allows U.S. wineries to include cheaper imported wines in products labeled as American. On Tuesday, the State Senate will vote on a bill sponsored by California grape growers that aims to close that international blending loophole. Reporter: Tina Caputo California is suing the Trump administration over its latest attempt to undo Clean Air Act waivers, which govern many of the state's auto emission standards. Learn more about your ad choices. Visit megaphone.fm/adchoices

Patrick DaHaan, vice president of petroleum analysis at Gas Buddy, joins the conversation to break down the current state of oil and gas prices. With his expertise, he sheds light on why the price of gasoline has increased by nearly 40% since the war, while the price of oil has only risen by around 10-12%. He explains that the difference lies in the refining process and the changing specifications of gasoline, which are influenced by factors like the Clean Air Act and seasonal demands. As we dive into the conversation, Patrick shares his insights on how the oil market reacts to changes in the Strait of Hormuz situation. He notes that the market is anticipating a potential deal between the US and Iran, which has led to a decrease in oil prices. However, if the situation doesn't improve, prices could spike again. Patrick's analysis provides a clearer understanding of the complex relationships between oil, gas, and global events. One of the key takeaways from this episode is the importance of considering the lag time between oil price changes and the impact on gasoline prices. Patrick explains that it can take several weeks for the effects of a decline in oil prices to be reflected in the price of gasoline. He also highlights the differences in gasoline specifications between winter and summer months, which affect the production costs and, ultimately, the prices at the pump. If you're curious about the intricacies of oil and gas prices and how they're influenced by global events, this episode is a must-listen. Patrick's expertise and straightforward explanations make complex topics accessible to everyone. Tune in to hear his insights and gain a better understanding of the oil and gas market.See omnystudio.com/listener for privacy information.

In June 2024 the Greater Memphis, Tennessee Chamber of Commerce announced Elon Musk's artificial intelligence company, xAI, would build its "Colossus" data center in an old Electrolux factory. Two years on, the story continues to expand alongside the company's growing footprint, with a second campus, Colossus II, across the state line in Southaven, Mississippi; a contested gray water recycling plant; an ever-rising count of gas turbines; multiple lawsuits; and communities in South Memphis still pressing for straight answers.Few people have tracked all of it more closely than Neil Strebig, a reporter with The Commercial Appeal in Memphis who has covered the xAI story daily from the beginning. He's attended community meetings and hearings, filed right-to-know requests, parsed the differing interpretations of the Clean Air Act by the EPA, the Shelby County Health Department and the Mississippi Department of Environmental Quality, counted turbines, and spent time with residents living alongside the facilities. The result is a level of detail that few can match.In this conversation, Strebig brings us up to speed on the latest developments — including a newly updated lawsuit citing unpermitted turbines in Southaven, the implications of the SpaceX IPO and the impending IPOs of other AI firms, and the stalled water recycling plant Memphis leaders had counted on. And, he reflects on what it has been like to chase facts as the story spread across two states and a thicket of jurisdictions.

Environmental law in the United States can be a double-edged sword. "I think that when people think about environmental law, very frequently what they mean is environmental protection, and what that misses is the other side of the coin, that there is a whole lot of law that is meant to exploit the environment," says law professor Brig Daniels. When Daniels and his writing partner Alejandro Camacho looked at the literature available on the development of environmental law in the United States, they found it lacking. "Most sort of focus only on environmental protection laws emerging from the 1970s or possibly the progressive era, missing frankly centuries of legal history that drove exploitation," says Camacho. They hope to remedy this with their new book, Lessons for a Warming Planet: A Vital History of US Environmental Law. From colonial expansion that deprived Native Americans of their ancestral lands to modern day battles over the Clean Air Act, Lessons for a Warming Planet offers a broad history of how environmental law has been developed. Change can happen gradually, or all at once. Camacho and Daniels have identified five different eras with dominant ideologies, some pushing towards protection and others towards exploitation. But in all eras, there were elements of both, the authors say. "It isn't just a black and white sort of binary of any of these eras," Camacho tells host Lee Rawles in this episode of the Modern Law Library. "And of course, what often happened is that an undercurrent in any given era becomes the dominant era in a subsequent era." The latest era of environmental law is one of contention, without a dominant force yet emerging. Lessons for a Warming Planet warns that either exploitation or protection could hold sway in the next era. "The thing that I hope that people understand is that looking back, one of the things that is so prevalent is that we didn't get the history that we had due to luck," says Daniels. "A big chunk of way we got our history was due to effort." In this episode of the Modern Law Library, Camacho, Daniels and Rawles discuss the Homestead Act, Cuyahoga River fires, and what Nixon really thought of pesky environmentalists.

As the Trump administration rolls back environmental regulations, we revisit a 2022 episode that explored the hidden cost of an invisible threat: air pollution.   SOURCES: Angela Duckworth, psychologist at the University of Pennsylvania. Michael Greenstone, economist at the University of Chicago, director of the Energy Policy Institute, co-director of the Climate Impact Lab. Stephan Heblich, economist at the University of Toronto. Andrea La Nauze, economist at Deakin University. Steve Levitt, professor emeritus of economics at the University of Chicago. Edson Severnini, economist at Boston College.   RESOURCES: "Most Polluted Cities," (American Lung Association, 2026). "Air Pollution and Adult Cognition: Evidence from Brain Training," by Andrea La Nauze and Edson Severnini (Journal of the Association of Environmental and Resource Economists, 2025). "Air Pollution and Student Performance in the U.S.," by Michael Gilraine and Angela Zheng (NBER Working Papers, 2022). "Billions of people still breathe unhealthy air: new WHO data," (World Health Organization, 2022). "Evolution of the Clean Air Act," by the United States Environmental Protection Agency (2020). "The Death of U.K. Coal in Five Charts," by Hannah Ritchie (Our World in Data, 2019). "The Colour of Pollution," (The Economist, 2014). Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

 Holly Fretwell explains how NEPA, the Endangered Species Act, and the Clean Air Act create "red tape" and litigation that stall restoration projects. She highlights that the Clean Air Act paradoxically limits prescribed burns, which would prevent far more damaging, high-emission wildfires. Some litigious groups cling to unrealistic, romanticized visions of unmanaged forests. (2)180E  HARLEM HEIGHT00

OSU board approves $100M settlement with nearly all remaining survivors who sued over abuse by Dr. Richard Strauss; central Ohio family sues funeral home alleging the body of their mother was cremated against her wishes; Kroger settles with the feds over violations of the Clean Air Act; a Buc-ee's location in Mansfield is one step closer to reality.

Share your Field Stories!We're LIVE from NAEP 2026 in Anchorage! Nic leads a special on-stage episode featuring Anna Kohl, Carolyn Nelson, and Fred Wagner as they dive into Alaska's unique environmental landscape, NEPA challenges, and the realities of project delivery. With candid insights, legal perspectives, and memorable field stories, this live recording captures the humor, complexity, and energy of environmental work in action.Welcome back to Environmental Professionals Radio, Connecting the Environmental Professionals Community Through Conversation, with your hosts Laura Thorne and Nic Frederick! Help us continue to create great content! If you'd like to sponsor a future episode hit the support podcast button or visit www.environmentalprofessionalsradio.com/sponsor-form Please be sure to ✔️subscribe, ⭐rate and ✍review. This podcast is produced by the National Association of Environmental Professions (NAEP). Check out all the NAEP has to offer at NAEP.org.Connect with Anna Kohl at https://www.linkedin.com/in/anna-kohl-cep-8184159/Guest Bio:Anna Kohl was born and raised in Anchorage and left for college before realizing there was much to explore back home. She obtained a BA in Geology from Mount Holyoke College and worked in coffee shops and remediation before landing at HDR Engineering in 2004, where she has been ever since. Anna's technical background is in the NEPA and impact analysis/environmental science fields, though she currently is the Operations Manager for 150 engineers, planners, scientists, GIS professionals, and other smart folks who make up HDR in Alaska. An active member of NAEP and a Trustee of ABCEP, she obtained a certificate in NEPA from the Duke University Nicholas School of the Environment in 2012 and her CEP in 2017.Connect with Carolyn Nelson at https://www.linkedin.com/in/carolyn-nelson-p-e-02768977/Guest Bio:Carolyn Nelson is responsible for providing technical assistance for NEPA compliance and other related environmental laws and Executive Orders as Director of Environmental Analysis & Compliance Division of PHMSA.  Carolyn has over 30 years' experience as a geometric design engineer and NEPA practitioner.  She was Co-Chair of the White House Interagency Council (IAC), NEPA Committee and is recognized as a national expert for NEPA compliance. Carolyn has worked at Headquarters of the FHWA and also in the FHWA Michigan Division Office. Prior to FHWA, she worked for the Michigan DOT and CH2M Hill (now Jacobs).Connect with Fred Wagner at https://linkedin.com/in/fred-wagner-59043019Guest Bio:Fred Wagner focuses on environmental and natural resources issues concerning major infrastructure, including surface transportation, energy, mining, and commercial project development. Fred advises clients on environmental reviews under the National Environmental Policy Act or equivalent state statutes. He also helps secure permits and approvals from regulators under a variety of federal programs, including Section 404 of the Clean Water Act, the Endangered Species Act, the Clean Air Act, and the National Historic Preservation Act. Fred provides strategic counseling regarding implementation of the full spectrum of federal environmental programs, as well as U.S. Department of Transportation (USDOT) surface transportation grant management and safety regulations. Prior to joining Jacobs, Fred represented a wide variety of developers, public entities, and businesses in environmental, land use, and natural resources litigation in federal trial and appellate courts across the country, from citizen suits to government enforcement actions and Administration Procedure Act (APA) challenges. Most recently, Fred was counsel of record in the Seven County Infrastructure Coalition NEPA case before the U.S. Supreme Court.Music CreditsIntro: Givin Me Eyes by Grace MesaOutro: Never Ending Soul Groove by Mattijs MullerSupport the showThanks for listening! A new episode drops every Friday. Like, share, subscribe, and/or sponsor to help support the continuation of the show. You can find us on Twitter, Facebook, YouTube, and all your favorite podcast players. 

How did Arizona lock in billion-dollar investments from TSMC, Intel, and LG Energy? Ian O'Grady, Senior Policy Advisor to Arizona Governor Katie Hobbs, joins ChinaTalk to share war stories from the state that's successfully reshoring semiconductor and battery production. Our conversation covers: Labor Disputes and Crisis Management — How the Governor's Office mediates disagreements between stakeholders and keeps workers happy. Clean Air Act vs. chips — Why Arizona's fabs struggled to get building permits despite the state's low per-capita emissions. Arizona's Abundance Playbook — Including a consolidated commerce authority, a culture of engineering > litigation, and institutional factors that help Arizona outbuild Ohio and Texas. Taiwanifying the Desert — How Phoenix welcomed TSMC engineers with Mandarin programs in schools, Din Tai Fung, and a new Costco. Industrial Policy Resource Wars — How Arizona avoids backlash based on power and water use concerns. Co-hosting is ChinaTalk researcher Aqib Zakaria. Cadillac Desert by Marc Reisner Learn more about your ad choices. Visit megaphone.fm/adchoices

How did Arizona lock in billion-dollar investments from TSMC, Intel, and LG Energy? Ian O'Grady, Senior Policy Advisor to Arizona Governor Katie Hobbs, joins ChinaTalk to share war stories from the state that's successfully reshoring semiconductor and battery production. Our conversation covers: Labor Disputes and Crisis Management — How the Governor's Office mediates disagreements between stakeholders and keeps workers happy. Clean Air Act vs. chips — Why Arizona's fabs struggled to get building permits despite the state's low per-capita emissions. Arizona's Abundance Playbook — Including a consolidated commerce authority, a culture of engineering > litigation, and institutional factors that help Arizona outbuild Ohio and Texas. Taiwanifying the Desert — How Phoenix welcomed TSMC engineers with Mandarin programs in schools, Din Tai Fung, and a new Costco. Industrial Policy Resource Wars — How Arizona avoids backlash based on power and water use concerns. Co-hosting is ChinaTalk researcher Aqib Zakaria. Cadillac Desert by Marc Reisner Learn more about your ad choices. Visit megaphone.fm/adchoices

With the growth of the administrative state over the last half-century, an equal expansion has occurred in the number of actions committable by individual citizens that can be prosecuted as crimes. At President Trump’s direction, the U.S. Department of Justice has initiated a new round of reforms aimed at ending “over-criminalization” of the Nation’s complex web of regulatory laws and standards. Most recently, DOJ announced that it was exercising enforcement discretion to dismiss several Biden-era prosecutions of individuals charged with violating the Clean Air Act who were alleged to have tampered with emissions-related diagnostic systems on cars and trucks. Supporters of the Biden-era policies and critics of this new policy argue that such emissions control deliver considerable benefits to the owner in the form of better fuel efficiency, and to society, in the form of cleaner air, and that this is a step backwards in environmental enforcement. This panel will discuss DOJ’s traditional approaches to criminal enforcement of administrative laws and regulations and offer viewpoints on recent reforms and changes to criminal enforcement in the current administration. Discussion will focus, in particular, on the DOJ’s decision to end criminal prosecutions of individuals for vehicle tampering cases under the Clean Air Act.Featuring:Granta Nakayama, Partner, King & Spalding LLPJustin Savage, Partner, Sidley Austin LLP(Moderator) John Irving, Partner, Secil Law

California is suing the federal government to save our Clean Air Act. Today, a conversation with our Attorney General Rob Bonta. Then, the lead singer of the band Electric Ex explains the process behind their new album Analog Therapy. Plus, authors read from their books about nature, and humanity.

Right now, the state of California has a very litigious relationship with the federal government. Currently our state is actively working on 67 separate lawsuits against Trump's administration. The legal disputes range from tariffs, public housing funding, sanctuary city policies, ICE agents wearing masks and even birth right citizenship.And, something notable is that almost a quarter of all the lawsuits are related to protecting our environment. Staying on top of all the litigation is the job of our state's Attorney General Rob Bonta. A few weeks ago he visited our live event space in downtown San Francisco to talk with Ethan Elkind, the host of KALW's show Climate Break.Bonta spoke about one of the most crucial climate lawsuits that is in the court system right now, the fight for our state's Clean Air Act. Nearly half of our carbon emissions come from transportation, but last year the US Senate voted to block California's mandate to phase out gas-powered cars by 2035.  In this excerpt, Bonta gives an update on how the lawsuit to protect the Clean Air Act is progressing…

In 2025, New Hampshire lawmakers passed a measure to eliminate their annual motor vehicle inspection requirement, effective Jan. 31, 2026. The vendor that had overseen the state’s vehicle inspections, Gordon-Darby Holdings Inc., challenged that measure, filing a lawsuit. The state was made aware by federal and state officials that repealing the inspection program without first obtaining the EPA’s approval regarding federal environmental law would violate the Clean Air Act. The program was repealed without approval first, leading to further legal proceedings and public confusion. What are your thoughts on eliminating annual motor vehicle inspections?See omnystudio.com/listener for privacy information.

In 2025, New Hampshire lawmakers passed a measure to eliminate their annual motor vehicle inspection requirement, effective Jan. 31, 2026. The vendor that had overseen the state’s vehicle inspections, Gordon-Darby Holdings Inc., challenged that measure, filing a lawsuit. The state was made aware by federal and state officials that repealing the inspection program without first obtaining the EPA’s approval regarding federal environmental law would violate the Clean Air Act. The program was repealed without approval first, leading to further legal proceedings and public confusion. What are your thoughts on eliminating annual motor vehicle inspections? NH House Majority Leader Rep. Jason Osborne checked in to bring clarity to the topic!See omnystudio.com/listener for privacy information.

Mike Hoeflich, Mike Lomas, and Russ Gaiser open with the latest assassination attempt targeting President Trump and members of his administration, calling out what they see as repeated, inexcusable failures in Secret Service security protocols. The conversation moves to the ongoing U.S./Iran standoff around the Strait of Hormuz, where the guys reflect on Trump's strategic approach to the region and what a lasting resolution could mean for the Middle East. EPA Administrator Lee Zeldin gets a moment in the spotlight after a viral congressional exchange with purple-haired Rep. Rosa DeLauro over climate policy and the Clean Air Act, with the hosts breaking down Zeldin's composed response and their frustrations with climate alarmism more broadly. The back half of the show covers AI's growing role in financial advising, with Russ sharing takeaways from a recent conference and Mike Lomas drawing parallels between today's AI adoption curve and earlier technology waves he lived through. The episode wraps with Mike Lomas recapping his first NHRA national event, a conversation on winner's mindset, and Sabers playoff predictions ahead of Game 5.(00:00:52) Enhancing Security Measures for Presidential Protection(00:11:21) Ineffective Communication in National Security Agencies(00:12:32) Intellectual Dynamics in Political Interviews(00:17:14) Urban Tree Planting for Environmental Sustainability(00:21:03) AI Tools Enhancing Financial Advisors' Efficiency(00:30:22) Believing in Success: Power of Positive Thinking

Sarah Light, Wharton Professor of Legal Studies and Business Ethics, examines how efforts to repeal the EPA's endangerment finding under the Clean Air Act could limit federal regulatory authority while opening the door to expanded state-level nuisance lawsuits against power plants and fossil fuel companies. Hosted on Acast. See acast.com/privacy for more information.

The EPA's 2009 Greenhouse Gas Endangerment Finding has been the legal foundation for U.S. climate regulation under the Clean Air Act for over a decade. In February, the Trump administration repealed it. That move puts the future of federal climate policy in question. Professor Alejandro Camacho explains what the endangerment finding did and why it mattered for policies ranging from vehicle emissions to power plant rules. Drawing on his new book, he also puts this moment in context: showing how earlier waves of environmental policymaking took shape in the 1960s and '70s, and why today's approach is marked by polarization, legal battles, and uncertainty. For more on this topic: Check out the book Camacho coauthored, Lessons for a Warming Planet: A Vital History of US Environmental Law Read his commentary in Legal Planet, The Trump Administration is Squandering Our Natural Heritage Read his op-ed in The Hill, Donald Trump's record-breaking race to wreck the planet   

I'm excited to welcome my friend, Ross Pifer, from Penn State University Dickinson School of Law to the show.  Ross and I are chatting about the right to repair.  What is controversial about the right to repair?  Why is this such a concern for agriculture?  What should we know about the recent John Deere settlement?  Ross helps answer these questions and more!   Contact Info for Ross Pifer - Website   Topics Mentioned in the Show -Center for Ag and Shale Law website -Penn State Ag Law Newsletter -Penn State Shale Law Newsletter -Penn State Agricultural Law Podcast -Prior Right to Repair podcast episode with Todd Janzen -EPA statement that Clean Air Act supports farmer right to repair  -Article on John Deere settlement -Article on FTC v. John Deere case Ag Law Resources -AgriPulse -Texas Agriculture Law Blog -National Agriculutral Law Center -Ohio State Ag Law Blog -Iowa State Center for Ag Law and Taxation Ag Docket Sponsors  

Fifty-six years ago, the first Earth Day helped spark a generation of landmark environmental legislation — and the Environmental Law Institute (ELI) was born from that same moment. On this Earth Day 2026, host Sebastian Duque Rios sits down with ELI President Jordan Diamond and Senior Attorney Jay Austin to trace the arc of environmental law from that founding era to the compounding crises of today.Together, they reflect on how statutes like NEPA and the Clean Air Act were designed with more foresight than we often credit them for, why adaptive management is baked into the DNA of environmental law, and how ELI is responding to an era of rapid institutional change — from regulatory rollbacks and executive action to the governance challenges posed by emerging industries like deep sea mining, geothermal energy, and data centers. They also dig into ELI's new collaboration with the Federation of American Scientists' (FAS) Center for Regulatory Ingenuity and their joint white paper laying out a framework for rebuilding and reimagining environmental governance fit for the 21st century.This episode is a candid, long-view conversation about what it takes to protect people, places, and the planet. For more information on other emerging topics in environmental law, see our recent episode, "What's Next for Environmental Law in 2026." ★ Support this podcast ★

Back on this day in 1970, the first ever Earth Day was celebrated. The reason it came about in the first place was because there was no Environmental Protection Agency, no Clean Water Act, no Clean Air Act.

For the second week in a row, the 3WHH gang (minus one) were on the road, this time recording live in the corner of a hotel lobby before the annual meeting of the Philadelphia Society. The sound quality of this episode is . . . authentic. Yes, I'll go with that. John Yoo couldn't make the meeting, so we have a special guest, our old pal Glenn Ellmers. With John absent, we get our freak on about the Clean Air Act . . . actually we didn't do that. We did worse: We get down in the weeds of metaphysics, radical historicism, the theological-political problem (especially in the context of this week's feud between the President and the Pope), dishing on Laura Field's terrible book Furious Minds, contrasting Justice Sotomayor's jurisprudence of "feels" versus Justice Thomas's jurisprudence of principle—the principle of the Declaration of Independence. And finally, we take up the perennial question, what's the matter with kids today. And as such the exit music this week is "Kids," from moe:Kids will try to run you overKids will try to bring you downKids will never say they're sorryKids back then are older now

What happens when lawsuits quietly shape public policy—without a full trial, public scrutiny, or legislative debate? In this episode of Sanity Check, David R. Legates unpacks the controversial practice known as “sue-and-settle.”What begins as a seemingly straightforward legal mechanism—citizens holding agencies accountable—can, in practice, become something far more complex. Through negotiated settlements between advocacy groups and federal agencies like the Environmental Protection Agency, binding regulations can emerge behind closed doors, often bypassing the traditional rulemaking process and limiting public input.This episode walks through how sue-and-settle works, why it's been used under laws like the Clean Air Act, and where the real controversy lies: accountability, transparency, and the balance of power in a democratic system. With millions in taxpayer-funded legal fees and far-reaching regulatory consequences at stake, critics argue this approach amounts to “regulation through litigation.”Is sue-and-settle an efficient tool for enforcing the law—or a loophole that sidelines the public and reshapes policy without consent?Tune in for a clear-eyed breakdown of one of the most debated—and least understood—mechanisms in modern environmental governance.https://openthebooks.substack.com/p/trump-epa-ends-exorbitant-pay-outshttps://www.uschamber.com/regulations/sue-and-settle-regulating-behind-closed-doorshttps://virginialawreview.org/wp-content/uploads/2020/12/Tyson_Book.pdfhttps://www.heritage.org/environment/commentary/environmentalists-sue-settle-and-apologize-laterVisit our podcast resource page: https://cornwallalliance.org/listen%20to%20our%20podcast%20created%20to%20reign/Our work is entirely supported by donations from people like you. If you benefit from our work and would like to partner with us, please visit www.cornwallalliance.org/donate. 

This Day in Legal History: McDonald's Franchise OpeningOn this day in 1955, Ray Kroc opened his first franchise location for McDonald's in Des Plaines, Illinois, marking a turning point in American business and legal history. Although franchising existed before this moment, Kroc's model introduced a new level of uniformity and control that reshaped how franchise systems operate. He required strict adherence to standardized procedures, branding, and product quality, which became central features of modern franchise agreements. These agreements are legally binding contracts that define the relationship between franchisors and franchisees, including fees, territorial rights, and operational obligations. As McDonald's expanded rapidly, it exposed gaps in existing business laws governing franchising practices. This growth led to increased scrutiny over issues such as disclosure requirements and fairness in contract terms.By the 1970s, concerns about deceptive practices and unequal bargaining power prompted regulatory responses, including the Federal Trade Commission's Franchise Rule. This rule requires franchisors to provide detailed disclosures to prospective franchisees, improving transparency and reducing fraud. Kroc's model also raised legal questions about liability, particularly whether franchisors could be held responsible for the actions of independently owned franchise locations. Courts have since developed tests to determine the level of control necessary to establish such liability. Additionally, franchise law has evolved to address disputes over termination rights and non-compete clauses. The McDonald's system became a case study in how private contracts can shape an entire industry's legal framework. Today, franchising remains a major part of the global economy, with legal standards that can be traced back to the system Kroc helped popularize.The NAACP filed a lawsuit against xAI in federal court in Mississippi, alleging that the company violated environmental laws while operating a gas-powered plant tied to its data center near Memphis. The complaint claims xAI built and ran the plant without obtaining required permits under the Clean Air Act. According to the NAACP, the plant emits harmful pollutants such as nitrogen oxides and formaldehyde, which are linked to serious health risks including asthma, heart conditions, and cancer. The organization argues that these emissions disproportionately affect nearby communities with large Black populations.The lawsuit also alleges that xAI deliberately avoided regulatory oversight by skipping the permitting process, which would have required pollution controls and environmental review. The plant is described as a major regional source of smog-forming emissions, potentially releasing large quantities of pollutants into the air. The NAACP is seeking court orders to halt operations until proper permits are obtained, require emission controls, and impose financial penalties for violations. The case reflects broader concerns about environmental justice, corporate compliance, and the rapid expansion of infrastructure supporting artificial intelligence technologies.NAACP Sues Musk's XAI Over Data Center Pollution In Miss. - Law360Albertsons has agreed in principle to pay $773 million to resolve claims brought by several states, local governments, and Native American tribes over its alleged role in the opioid crisis. The agreement involves attorneys general from states including California, Colorado, Illinois, and Oregon, though some terms—such as requirements for future conduct—are still being negotiated. The states claim the company contributed to the public health crisis through its pharmacy operations, while Albertsons maintains the settlement does not admit wrongdoing.This deal is part of a broader wave of opioid-related litigation targeting companies across the pharmaceutical supply chain. Governments have accused pharmacies, distributors, and manufacturers of contributing to widespread addiction through improper practices. Other major settlements, including those involving Purdue Pharma and the Sackler family, have pushed total payouts in opioid cases beyond $50 billion nationwide.Funds from the Albertsons settlement are expected to support addiction treatment, prevention, and recovery programs, with allocation plans already in place in some states. Officials emphasized that these settlements aim to both address past harm and fund ongoing efforts to combat the opioid epidemic.State AGs, Albertsons Chain Reach $773M Opioid Deal - Law360Amazon has agreed to acquire Globalstar for about $11.6 billion as part of its push into satellite-based internet services. The deal will give Amazon access to Globalstar's satellite network, spectrum rights, and infrastructure, helping expand its low Earth orbit (LEO) system aimed at providing global connectivity without relying on traditional cell towers.Under the agreement, Globalstar shareholders can receive either cash or Amazon stock, with the total deal value capped at $90 per share. A majority of Globalstar shareholders have already approved the transaction, but it still requires regulatory clearance and fulfillment of certain operational conditions before closing, which is slotted for 2027.The acquisition positions Amazon to compete more directly in the growing satellite internet market, where companies like SpaceX's Starlink currently dominate. Globalstar's existing technology and planned satellite upgrades are expected to strengthen Amazon's ability to deliver direct-to-device connectivity worldwide. The deal also ties into Amazon's partnership with Apple, supporting satellite features on devices like iPhones and Apple Watches.Paul Weiss, Skadden Lead Amazon's $11.6B Globalstar Deal - Law360A law student at Texas Tech University has filed a federal lawsuit claiming the school violated her First Amendment rights by disciplining her over comments about the killing of Charlie Kirk. The student, Ellen Fisher, alleges she was unfairly singled out for punishment while other students who discussed the same topic were not disciplined. She received a written reprimand, which she argues could negatively affect her ability to become a licensed attorney.Fisher maintains that her statements were part of normal academic discussion and did not celebrate Kirk's death, despite claims from at least one witness. She also argues the university's investigation was flawed because it ignored testimony supporting her version of events. The university concluded her remarks could have been perceived as celebratory and violated professional conduct standards.The lawsuit seeks to block the disciplinary action, obtain damages, and secure a ruling that the university infringed on her constitutional free speech rights. The case comes amid broader national debates over campus speech and how universities respond to controversial or sensitive political discussions.Texas law student sues to stop sanctions over Charlie Kirk comments | Reuters This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.minimumcomp.com/subscribe

I sit down with Evan Raskin, National Campaign Manager for Earthday.org, to explore the powerful relationship between art and environmental activism. Evan shares how artists have been central to the Earth Day movement since its very first gathering in 1970 and how creative expression continues to drive climate action today.Evan shares his own life as an artist and how art helps him find harmony in a world full of dissonance. We discuss why collective action — starting at the local level — matters more than ever.

Biodiversity is collapsing under the pressures of human overpopulation, overconsumption, and animal agriculture. Tierra Curry and Stephanie Feldstein of the Center for Biological Diversity explain how science, law, and advocacy can protect wildlife and wild places. They also share strategies for combating extinction and staying motivated to act in an age of ecological crisis. Highlights include: Why human population pressure, industrial animal agriculture, and growth economies are key issues that the Center addresses, even though they are often ignored or treated as taboo by most environmental organizations; How rapid, human-driven extinctions are mutilating the tree of life, and why biodiversity is essential not just for wellbeing and thriving of all the species, but also for human survival; How water and other ecosystems in the U.S. are threatened by lax regulation, industrial agriculture, and political attacks on protections like the Endangered Species Act, Clean Water Act, and Clean Air Act; Why industrial agriculture's promotion of pasture grazing and regenerative agriculture is based on myths, and what the facts show about meat reduction as the most effective strategy to preserve habitats and wild animals; How positive change requires both individual action, such as plant-based diets, and collective political action to protect ecosystems and biodiversity; Why love of the natural world spurs both Stephanie and Tierra to action, despite immense ecological grief. See episode website for show notes, links, and transcript:  https://www.populationbalance.org/podcast/stephanie-feldstein-tierra-curry   OVERSHOOT | Shrink Toward Abundance OVERSHOOT tackles today's interlocked social and ecological crises driven by humanity's excessive population and consumption. The podcast explores needed narrative, behavioral, and system shifts for recreating human life in balance with all life on Earth. With expert guests from wide-ranging disciplines, we examine the forces underlying overshoot: from patriarchal pronatalism that is fueling overpopulation, to growth-biased economic systems that lead to consumerism and social injustice, to the dominant worldview of human supremacy that subjugates animals and nature. Our vision of shrinking toward abundance inspires us to seek pathways of transformation that go beyond technological fixes toward a new humanity that honors our interconnectedness with all beings.  Hosted by Nandita Bajaj and Alan Ware. Brought to you by Population Balance. Subscribe to our newsletter here: https://www.populationbalance.org/subscribe Support our work with a one-time or monthly donation: https://www.populationbalance.org/donate Learn more at https://www.populationbalance.org Copyright 2016-2026 Population Balance

On February 12, the Environmental Protection Agency dealt a major blow to the government's power to fight climate change by rescinding a key piece of research called the endangerment finding. The finding, issued in 2009, basically says: Greenhouse gas emissions endanger public health and welfare—and because they're harmful, they must be regulated. It's the legal basis for the federal government's regulation of greenhouse gases under the Clean Air Act. So what does it mean that this finding has been thrown out? Host Flora Lichtman digs into this question with Andy Miller, an original author on the endangerment finding who spent more than 30 years working for the EPA. Guest: Dr. Andy Miller worked on air pollution and climate change at the EPA for more than 30 years. He was an original author on Endangerment Finding. Transcripts for each episode are available within 1-3 days at sciencefriday.com. Subscribe to this podcast. Plus, to stay updated on all things science, sign up for Science Friday's newsletters.

The Environmental Protection Agency rescinds its 2009 assertion that it can regulate greenhouse gases under the Clean Air Act, because they "endanger" public health. EPA Administrator Lee Zeldin says this means cheaper cars and no more EV mandates, but is it going next to the courts, and maybe the Supreme Court? Learn more about your ad choices. Visit megaphone.fm/adchoices

 In this episode of the MeidasTouch Podcast, we break down the latest news, including the fallout from Pam Bondi's disastrous congressional hearing, where she erupted when pressed on her role in the Epstein cover-up. We also examine Donald Trump's latest assault on climate policy after repealing the critical endangerment finding that determined greenhouse gases are dangerous to public health under the Clean Air Act, setting up a massive legal fight with global implications. We discuss a federal judge's decision to block Defense Secretary Pete Hegseth from punishing Senator Mark Kelly as Trump allies push alarming efforts to target lawmakers who simply told service members to follow lawful orders. Plus, we dive into Trump's ICE pulling back its aggressive operation in Minnesota following months of terror, and more. Ben, Brett, and Jordy break it all down. Subscribe to Meidas+ at https://meidasplus.com Get Meidas Merch: https://store.meidastouch.com Deals from our sponsors!  Zip Recruiter: Try ZipRecruiter for FREE at https://ZipRecruiter.com/MEIDAS Leaf Filter: Schedule your free inspection and get up to 30% off your entire purchase at https://leaffilter.com/meidas Hims: To get simple, online access to personalized, affordable care for ED, Hair Loss, Weight Loss, and more, visit https://Hims.com/meidas Cash App: Download Cash App Today: https://capl.onelink.me/vFut/2ukx7bii #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. Cash App Green, overdraft coverage, borrow, cash back offers and promotions provided by Cash App, a Block, Inc. brand. Visit http://cash.app/legal/podcast for full disclosures. Remember to subscribe to ALL the MeidasTouch Network Podcasts: MeidasTouch: https://www.meidastouch.com/tag/meidastouch-podcast Legal AF: https://www.meidastouch.com/tag/legal-af MissTrial: https://meidasnews.com/tag/miss-trial The PoliticsGirl Podcast: https://www.meidastouch.com/tag/the-politicsgirl-podcast Cult Conversations: The Influence Continuum with Dr. Steve Hassan: https://www.meidastouch.com/tag/the-influence-continuum-with-dr-steven-hassan The Weekend Show: https://www.meidastouch.com/tag/the-weekend-show Burn the Boats: https://www.meidastouch.com/tag/burn-the-boats Majority 54: https://www.meidastouch.com/tag/majority-54 On Democracy with FP Wellman: https://www.meidastouch.com/tag/on-democracy-with-fpwellman Uncovered: https://www.meidastouch.com/tag/maga-uncovered Learn more about your ad choices. Visit megaphone.fm/adchoices