Podcasts about Casselman

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

On She Built It®, Lori Casselman, a 20-year healthcare executive turned founder, shares what it took to build June Health, Canada's first virtual clinic providing complete care across every stage of women's health.Lori talks about the opportunity she sees for AI to close the gender health equity gap, the leadership lessons that come with scaling a startup in healthcare, and the culture principles she fiercely protects inside a fully virtual team. She's candid about the hardest parts of building, including the moment you realize a team member who helped you get here may not be the right person to get you to the next stage, and honest about what keeps her grounded through the pressure of a very big mission. This conversation is for any founder building something that matters at the intersection of people, technology, and purpose.Connect with us:June Health WebsiteJune Health LinkedInJune Health InstagramLori Casselman LinkedInWork with She Built It® Media She Built It® Instagram She Built It® CEO, Melanie Barr InstagramMelanie Barr LinkedInShe Built It® LinkedIn

2026-06-07 : Chad Casselman – Rebuilding the Temple

Travelling to Casselman, Blue Jays blast the Marlins, Memorial Cup, the Hurricanes culture, and will Lane Hutson bounce back for the Habs.

Cette semaine, Alexandre Fontaine Rousseau accueille Rachel Samson et Pierre Chemartin pour un épisode 100% consacré à l'édition 2026 des Sommets du cinéma d'animation. Retour sur les films (regroupés par thèmes) et moments forts du festival qui s'est tenu du 11 au 16 mai à la Cinémathèque québécoise. Liste des films mentionnés : The Square (Gwand-jang) / Paradaïz (Matea Radic) / Ultra forte (Catherine Lepage) / Blessed (Birute Sodeikaite) / Je m'appelle Daniel (Daniel Léger) / La tête en champ de bataille (Anaë Bilodeau, Louis-Pierre Cossette) / A Better Day (Scott Cowan) / Still Moving (Rui Ting Ji) / Raconte-moi ton prénom (Cantiane Breton) / Matrescence (Elizabeth Laferrière) / Pertes ambiguës (Fanny Lord-Bourcier) / Good Luck to You All (Cordell Barker) / Plus (Renaud Hallée) / Cardinal (Joël Vaudreuil) / Oh, Casselman! (Dominic Asselin) / We're Kinda Different (Ben Meinhardt) / Vera (John Harbour) / Le bruit des nuages (Jade Bressan) / Violet After The Storm (Bekky O'Neil) / Action Bog (Winston Hacking) / Cabbage Daddy (Grace An) Le balado 100% cinéma de la revue de cinéma 24 images

Need help? Check out these resources: www.firstresponderwellness.co/resources or Dial 988 for immediate help.    126 - The Hidden Injury Behind the Anger with Jeff Casselman What happens when the trauma isn't just emotional — but neurological? In this powerful episode, Conrad Weaver talks with retired police officer and Army veteran Jeff Casselman about the devastating intersection of PTSD, cumulative concussions, and traumatic brain injury. Jeff opens up about blackout rage, memory loss, seizures, personality changes, and the painful impact those injuries had on his career, marriage, and identity. This is an honest conversation about what policing can cost when injuries go unseen, symptoms get misread, and officers keep pushing through. If you serve in law enforcement, lead first responders, support officer wellness, or love someone in the job, this episode is a wake-up call you need to hear. CONNECT WITH JEFF Book: A Survival Guide for Cops with TBI & PTSD: Accountability, Moral Injury, and the Cost at Home Order here: https://a.co/d/0c2d9zqn LinkedIn +++++ FIRST RESPONDER WELLNESS PODCAST Order the PTSD911 Film and Educational Toolkit here: https://ptsd911movie.com/toolkit/ Web site:  https://ptsd911movie.com/ Instagram: https://www.instagram.com/ptsd911movie/ Facebook: https://www.facebook.com/ptsd911movie/ YouTube: https://www.youtube.com/channel/UClQ8jxjxYqHgFQixBK4Bl0Q Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/first-responder-wellness-podcast/id1535675703 Listen on Spotify: https://open.spotify.com/show/2wW72dLZOKkO1QYUPzL2ih Purchase the PTSD911 film for your public safety agency or organization: https://ptsd911movie.com/toolkit/ The First Responder Wellness Podcast is a production of First Responder Wellness Solutions, LLC Copyright ©2026 First Responder Wellness Solutions, LLC - All rights Reserved.

Ashley Casselman from the Western Fair Association joined Mike Stubbs to discuss the world of AgRobotics.

Discover the raw truth about traumatic brain injury (TBI) and PTSD in law enforcement from retired officer Jeff Casselman, who served 27 years in the military and at Lorain Ohio PD. After multiple concussions from cruiser accidents, bar fights, and on-duty violence, Jeff faced memory loss, rage blackouts, seizures, and three failed marriages before a diagnosis changed everything. He shares powerful stories: brutal fights, bizarre calls (like a grim reaper walking a goat), heartwarming redemption with a former addict he helped save, and the "Wild West" days of policing. Jeff founded the Sentinel Neuro Awareness Institute and authored Survival Guide to educate officers, departments, and families on recognizing cumulative brain damage early—before it destroys careers, relationships, or lives. Topics include: firearm concussion risks, hyperactive startle response, adult-onset ADD from head trauma, medications like lamotrigine (Lamictal) for impulse control, and why early awareness matters for cops, veterans, and contact-sport athletes. If you're in law enforcement, a first responder, veteran, or love someone who is—this eye-opening interview reveals the hidden neurological toll of the job and how to fight back. Jeff's Book https://a.co/d/09rr36Ge Facebook https://www.facebook.com/share/1FRkgeRM8F/?mibextid=wwXIfr Contact Steve - steve@thingspolicesee.com Support the TPS show by joining the Patreon community today! https://www.patreon.com/user?u=27353055 Sergeant Steve YouTube Channel https://www.youtube.com/@TheSergeantSteve      

2026-02-22 : Chad Casselman – The Power of Language

Vandaag schuif ik aan bij de Vlaamse powervrouw An-Katrien Casselman. Blogger, ondernemer en moeder, maar vooral een Dopamina in hart en nieren. We hebben het over het moment dat alles te veel werd na de geboorte van haar dochter, hoe haar zus (psychiater!) haar op het spoor van ADHD zette en waarom kleur voor haar rust betekent.Van het vergeten van bestellingen tot keihard openbloeien op school, van supplementen tot structuur die altijd net buiten bereik blijft en toch: ze bewijst dat je voluit jezelf kunt zijn, mét chaos en al.

We bespreken de beursreactie op Novo Nordisk op groen licht van de Amerikaanse geneesmiddelen-autoriteit. En we bespreken de beursrally in China met analist Patrick Casselman. In Trends podcasts vind je alle podcasts van Trends en Trends Z, netjes geordend volgens publicatie.  De redactie van Trends brengt u verschillende podcasts over wat onze wereld en maatschappij beheerst.  Vanuit diverse invalshoeken en met een uitgesproken focus op economie en ondernemingen, op business, personal finance en beleggen.  Onafhankelijk, relevant, telkens constructief en toekomstgericht. 

What's your strategy for tackling care fragmentation and unattached patients? In this video, Akinox Chief Growth Officer Mark Casselman shares how his team is building practical tools—like Linx and CarePath—to close care gaps and support population health at scale.From AI-powered assessments to digital-first strategies for unassigned patients, Casselman unpacks how healthcare IT leaders can better support clinicians and patients alike without waiting on massive infrastructure overhauls.What do you think of the new trends in healthcare IT? Leave a comment below and share your thoughts. Don't forget to subscribe for more content on AI in healthcare and the latest tech innovations.

The conversation around women's health is finally changing—and it's about time. In this episode of Success Leaves Clues, hosts Robin and Al reconnect with Lori Casselman, founder and CEO of June, a virtual clinic dedicated to midlife women's health. Lori shares how her personal health journey sparked the creation of June and speaks to the need for better access to care and open dialogue around menopause and aging. The conversation explores how partnerships, workplace support, and a focus on legacy can create meaningful change, not just for women today, but for generations to come.Key Takeaways:✨ June is reimagining access to midlife women's health through virtual care.✨ Menopause is no longer a taboo topic—it's entering workplace wellness conversations.✨ Lori's journey illustrates how personal experiences can lead to impactful innovation.✨ Building strong relationships and partnerships is foundational in startup success.✨ Legacy means creating a better, more empowered future for women.Connect with LoriLinkedIn: https://www.linkedin.com/in/loricasselman/Website: https://junehealth.care/Connect with Us • LinkedIn: Robin Bailey and Al McDonald • Website: Aria Benefits and Life & Legacy Advisory Group

In this episode of the Startup Woman podcast, Lori Casselman discusses her... The post Exploring Menopause and Perimenopause with Lori Casselman first appeared on Startup Canada.

In this episode of the Startup Woman podcast, Lori Casselman discusses her... The post Exploring Menopause and Perimenopause with Lori Casselman first appeared on Startup Canada.

Would you date you? This was the question and catalyst that started our beautiful guest today, Ila Casselman, on her own journey to living a juicy life. Ila is an Osteopathic Practitioner best known for her well-known clinical practice in Vancouver where she's been treating people for their physical and emotions pain for the past 13 years.  She holds a Masters Degree in Osteopathic Medicine - and if you don't know what that is, we get into that in this episode. Today she joins us today to talk about her forthcoming book called Love Your Villain. In this episode we're talking about: How to learn to love that part of us most people find unloveable or unlikeable. And how she learned to wake up loving her life, and how you can too. For more on Ila: Follow her on Instagram @thujawellness or visit her website at: www.thujawellness.com

Guest:   Barry Casselman, The Prairie Editor.   We will look at the results of the 2024 election and other stories:

Guest:   Barry Casselman, The Prairie Editor.   We will look at the state of the 2024 election and other stories: Check our blog....and follow our friend Carlos Guedes...  

We were very fortunate to have Ian Casselman from Marianas Trench on the podcast to talk about their new album, "Haven". Enjoy! Marianas Trench Socials: Twitter: https://x.com/mtrench Instagram: https://www.instagram.com/mtrenchofficial/ Facebook: https://www.facebook.com/MarianasTrench TikTok: https://www.tiktok.com/@mtrenchofficial YouTube: https://www.youtube.com/@Mtrench Apple Music: https://music.apple.com/us/artist/marianas-trench/124943892 Spotify: https://open.spotify.com/artist/68EB3QvNdVLkC7SAgDbHIR Website: https://marianastrench.net/ Grab some GNP Merch!: https://goodnoisepodcast.creator-spring.com/ Check out the recording gear we use: https://www.amazon.com/shop/goodnoisepodcast Support the show on Patreon: https://www.patreon.com/goodnoisepodcast Good Noise Podcast Socials: Twitter: https://twitter.com/good_noise_cast Instagram: https://www.instagram.com/goodnoisepodcast/ Facebook: https://www.facebook.com/goodnoisepod Discord: https://discord.gg/nDAQKwT YouTube: https://www.youtube.com/channel/UCFHKPdUxxe1MaGNWoFtjoJA Spotify: https://open.spotify.com/show/04IMtdIrCIvbIr7g6ttZHi All other streaming platforms: https://linktr.ee/goodnoisepodcast Bandcamp: https://goodnoiserecords.bandcamp.com/

Guest:   Barry Casselman, The Prairie Editor.   We will look at the state of the 2024 election and other stories: Check our blog....and follow our friend Carlos Guedes...  

00:00 Introduction and Persistence 02:00 JVZoo as an Affiliate Platform 05:16 The Role of Affiliates in Laura's Business 08:15 Laura's Growth Mindset and Evolution in JVZoo 11:14 Opportunities in Online Marketing 13:25 Listening to User Feedback and Utilizing AI 16:03 The Importance of Good Copy for Affiliates 18:31 Avoiding the Race to the Bottom 21:29 Transition in Ownership and Future of JVZoo 32:39 Lessons in Teamwork and Leadership: From Professional Dancer to CEO 38:35 The Power of Consistency and a Positive Mindset in Achieving Success 41:04 The Importance of Physical Activity and Taking Care of Your Body Market like you mean it. Now go sell something. Get private coaching with the Make Every Sale Program here: https://saleswhisperer.gumroad.com/l/OiXZk SUBSCRIBE to sell more, faster, at higher margins, with less stress, and more fun! https://www.youtube.com/@TheSalesWhispererWes ----- Connect with me: Twitter -- https://twitter.com/saleswhisperer TikTok -- https://www.tiktok.com/@thesaleswhisperer Instagram -- http://instagram.com/saleswhisperer LinkedIn -- http://www.linkedin.com/in/thesaleswhisperer/ Facebook -- https://www.facebook.com/wes.sandiegocrm Facebook Page -- https://www.facebook.com/thesaleswhisperer Vimeo -- https://vimeo.com/thesaleswhisperer Podcast -- https://feeds.libsyn.com/44487/rss YouTube — https://www.youtube.com/@TheSalesWhispererWes Sales Book -- https://www.thesaleswhisperer.com/c/way-book   BUSINESS GROWTH TOOLS https://12WeeksToPeak.com https://CopyByWes.com https://CRMQuiz.com https://TheBestSalesSecrets.com https://MakeEverySale.com https://www.TheSalesWhisperer.com/ https://www.thesaleswhisperer.com/c/ipa

Summer rewind: Ontario's electricity sector is evolving, as the province navigates the transition to cleaner energy amidst rising demand. In thinkenergy episode 135, we explore the grid's structure and key players, highlighting the crucial role of distributors (Local Distribution Companies or LDCs) in facilitating this transition. Guest Teresa Sarkesian, President and CEO of the Electricity Distributors Association (EDA), sheds light on LDCs' frontline efforts and contributions shaping the energy landscape. Related links   Teresa Sarkesian on LinkedIn: https://www.linkedin.com/in/teresa-sarkesian-53898613/   Electricity Distributors Association: https://www.eda-on.ca/  Green Button information: https://www.oeb.ca/consumer-information-and-protection/green-button  Electrification and energy transition panel report: https://www.ontario.ca/document/ontarios-clean-energy-opportunity-report-electrification-and-energy-transition-panel  Ontario Electricity Support Program: https://ontarioelectricitysupport.ca/  Trevor Freeman on LinkedIn: https://www.linkedin.com/in/trevor-freeman-p-eng-cem-leed-ap-8b612114/ Hydro Ottawa: https://hydroottawa.com/en     To subscribe using Apple Podcasts:  https://podcasts.apple.com/us/podcast/thinkenergy/id1465129405   To subscribe using Spotify: https://open.spotify.com/show/7wFz7rdR8Gq3f2WOafjxpl   To subscribe on Libsyn: http://thinkenergy.libsyn.com/ --- Subscribe so you don't miss a video: https://www.youtube.com/user/hydroottawalimited   Follow along on Instagram: https://www.instagram.com/hydroottawa   Stay in the know on Facebook: https://www.facebook.com/HydroOttawa   Keep up with the posts on X: https://twitter.com/thinkenergypod     Trevor Freeman Hey everyone. Well, it's officially summer, and the think energy team is taking a break to recharge over the next two months, but also to plan our content for the fall. So stay tuned for some great episodes in the fall. Not to worry, though, we still have our summer rewind to keep you engaged. This is where we pick out some of the great past episodes that we've done and repost them. So whether you're lucky enough to be sitting on a dock or going on a road trip or if you're just keeping up with your commute through the summer, it's a great time to revisit our past content. You will hear past episodes from my predecessor and the host chair, Dan Sagan, as well as a couple of mine from the past few months, and you're welcome to check out your own favorite past episodes as well. Wherever you get your podcasts. We hope you have an amazing summer, and we'll be back with new content in September, and until then, happy listening.   Trevor Freeman  0:07   Hi, welcome to think energy, a podcast that dives into the fast-changing world of energy through conversations with industry leaders, innovators and people on the frontlines of the energy transition. Join me Trevor Freeman, as I explore the traditional, unconventional and even up and coming facets of the energy industry. If you've got thoughts, feedback or ideas for topics that we should cover, we'd love to hear from you. Please reach out to us, at think energy at hydro ottawa.com Hi, everyone, welcome back. Now it's no secret that Ontario's electricity sector is transforming rapidly as it moves to both decarbonize the grid itself, you know, we have a very clean grid in Ontario, but it's not totally carbon free. And to support the growing demand for electricity as our customers across the province, take steps to electrify and change how they use energy. The show is all about exploring those changes, among other things, and today is no different. But before we dive into our conversation today, I think it would be helpful for me to spend just a few quick minutes on some basics about how our electricity grid is structured in Ontario, and who some of the key players are. Now I know some of our listeners will know this already, but it can be hard to keep track of all those key players. And Ontario's structure is a little different than some of the neighboring jurisdictions no two jurisdictions are exactly alike. So, a refresher is never a bad thing. Now the most basic description is that electricity is largely generated at central generation facilities. So, think nuclear power plants are your electric generating stations, some gas fired generating stations and large-scale wind and solar installations. We call these entities generators simple as that. That electricity is then transmitted across the province in an interconnected grid of high voltage transmission lines, which also connect to other jurisdictions such as neighboring provinces and states, and Ontario, Hydro One runs the transmission network. Now you've probably seen this transmission network. These would be the large metal towers that you see out in the middle of a field when you're driving along the highway or in rural areas that have electricity wires strung way up high in the air. The last stage before it gets to the end user is called distribution. So, this is where electricity is taken from those high voltage lines stepped down to a usable voltage for residential and commercial customers via transformers and substations, and then distributed over a network of overhead and underground wires, then these would be the wires that you would see at the top of those wooden or composite poles that are along the side of the road in your neighborhood. The entities that run this distribution part are called distributors, again, simple as that. So, there's a few other key players that are worth mentioning here. Energy Policy is primarily the jurisdiction of the provincial government, who sets the general direction and associated rules and regulations accordingly. The Ontario Energy Board or OEB is the regulatory body who governs what all those other players do and enacts the government mandate. And finally, at least for today's purposes, we have the system operator. It's called The Independent Electricity System Operator in Ontario, or IESO, who runs the system. So, if you're in Windsor, Ontario, or Ottawa, or North Bay, and you want to turn on your air conditioner, or plug your EV in to charge, the IESO is responsible for making sure there's enough power on the grid to handle that load. So, I hope everyone is still with me and feel free to pause and do some jumping jacks if that was a lot to take in. Our conversation today is going to be focused on the role of the distributor. So, for full disclosure, as you know, I work for hydro Ottawa who is one of those distributors, we serve most electricity customers in the City of Ottawa, and the neighboring village of Casselman and in Ontario, you will often hear distributors referred to as local distribution companies or LDCs. So forgive me if I slip into that acronym throughout the conversation today, that's really just the sort of common name that we refer to those distributors as. But I'll try to mix it up and make sure that, that I'm explaining that acronym throughout as well. So the distributor is really the front line, the customer facing entity of the entire electricity system. If you are an electricity customer, and you think about the electricity system, you are probably thinking about your distributor. Chances are you get your bill from a distributor, even though for most customers, most of what you pay on that bill doesn't actually go to the LDC. Some of it stays with your local distribution company, but most of it goes to the transmitter to the generator, to the IESO etc. When the power goes out, it's probably your LDC that you call and it's your LDC that will give you a restoration time. Sometimes outages are caused by issues up the line, so to speak in the transmission portion of the grid. But often the issue is a localized one. And it's your LDC that is identifying the problem and fixing it, whether that means rolling a truck to string new cable, or performing switching to work around the problem. And finally, it's your LDC that is really on the frontlines of the energy transition. While all parts of the grid must then have started to change, the LDCs are really working hand in hand with our customers to identify where and how fast and new demand is needed to bridge that gap between customers and policymakers to enable more and more renewable generation. And also to determine what new technologies or programs we need to pilot and scale up. And it's really the LDCs that are driving change in the way that electricity is managed at the individual customer level moving forward. So to help us make some sense of this, I'm happy to have Teresa Sarkesian on the show today. Teresa is the president and CEO of the electricity Distributors Association, which is a role that she's held since 2016. This is actually Teresa second time on the show the first being back in December 2021. So we're happy to have Teresa back, Teresa, welcome back to the show.   Teresa Sarkesian  6:23   Thanks so much, Trevor. I'm really delighted to be back.    Trevor Freeman  6:27   Yeah, we're glad to have you. So, like I said, you were back on our show in 2021. I don't know if it's because of how COVID has changed our lives or if this is just the way things go. But sometimes, you know, weeks seem like years. So 2021 is a long time ago. Let's start by refreshing our listeners on the role and mandate of the electricity Distributors Association.   Teresa Sarkesian  6:49   Sure thing so the electricity Distributors Association, or the EDA our little acronym represents Ontario's public and private electric utilities that distribute electricity to 5.4 million homes, businesses and institutional customers across the province. And I should note that those 5.4 million customers really refers to build accounts so you have families that are behind a build account. So effectively the millions and millions of Ontarians and businesses that operate and live here are customers of our utilities. And as you know our members are on the front lines of power, and have developed a strong trust with their customers by providing safe, reliable and affordable service for over 100 years. The EDA itself provides analysis and networking and advocacy for our members to ensure that the energy policy direction and framework in Ontario is fair and balanced, supporting the financial viability of utilities to deliver service and ensuring affordability for customers. And long term, we are looking to ensure that our local distribution company members can become the premier energy solution providers to their customers, and that they're able to provide the value-added services that customers are already expecting from them but are going to grow with the energy transformation and electrification in the future.    Trevor Freeman  8:09   Yeah, it's kind of like I said, when people think about the electricity sector, they're probably thinking about their distributor. And the EDA is kind of that common voice for those distribution companies. So, you first joined the EDA back in 2009, and have been the president and CEO since 2016. So, we'll look ahead and talk about the future in a minute. But before we do that, tell us about how things have changed so far during your tenure. How are things different from 2009 When you first joined the organization?   Teresa Sarkesian  8:40   Yeah, and you know, this is almost like perfect timing, Trevor, because I've been at the association now for 15 years, I'm just marking my 15-year anniversary. So, feels really apropos to kind of reflect and look back. So, I want to break down my answer into two parts. So, I'm going to talk to you about some, I guess, just my own personal observations about the electricity system at large. And then I'm going to talk more about the changes in distribution. But some of the changes that I thought were really quite significant and profound, sort of when I joined the industry in 2009, I joined at a time when there was the Green Energy Act, and the province was looking to connect all kinds of renewable energy generation to the electricity grid. So that was fairly significant. Another thing that was happening with the province is that they closed down coal fired generation. That was pretty massive. In fact, I think, at the time, it was the largest kind of carbon reduction initiative in North America. And I think even to this date today, I think it still is something that Ontario really has to be proud of. Another thing that you know, at the time, I think that was you know, fairly significant in 2015 is just the expectation of what the demand would be. What was interesting, sort of like the past for 15 years, the demand from customers for electricity was actually flat or declining. And that's all changed. Now. 15 years later, we're, we're now forecasting, massive increases in in demand of energy, which could potentially be doubling in the future. And the other point I'd like to make is just the nuclear renaissance that we're having. I think when I joined the sector in 2009, I'll tell you, I think the public opinion of nuclear was actually quite low. And that's been completely turned around lots of geopolitical events around the world, I think, have driven that. And now that nuclear is having a huge Renaissance. And you're seeing, you know, lots of new investments in nuclear. And we're not talking about shutting down reactors anymore. We're talking about refurbishing and expanding. So those are some of the things that I've observed over the last 15 years that have really changed. And for local distribution companies, I think what I have seen is a growing expectation by both government and the regulators for electric utilities to do more to both support the grid reliability and meet growing expectation from customers. So, I started in the sector in 2009, it was right on the brink of implementation of smart meters, and time of use. And what was interesting is that was mandated, there were very few jurisdictions in the world that actually had mandated smart meters and time of use pricing. So again, Ontario is was one of the first. And so that was a big change for LDCs. To move from, you know, smart meters and having to bring in that technology and also support the technology of time of use. I did mention the Green Energy Act at the time, we suddenly had to connect 1000s and 1000s, of new solar and wind generation, as well. And that was all new. There were no protocols, there were no standards for that. So that was fairly significant as well. And when I kind of fast forward to I guess, more recently, there have been a lot of changes from government, I think they've really supported our industry, they understand the trust that we have, with our customers. And they've implemented, you know, a number of new changes in terms of rate structures, they've asked us to implement ultra low-rate pricing that can support overnight electric vehicle charging. And they've also asked us to introduce a green button digital platform that allows customers to download their energy data and share with third parties for you know, different assessments and tools for lowering energy costs. But it's all not, you know, unicorns and kittens, there's challenges to for our sector, grid resilience was, you know, not really, people talked about it in 2009, but not like they're talking about it now, because of climate change. And we are seeing more frequent storms, causing, you know, obviously, outages for the customer, and also significant damage to the distribution grid. And I know that hydro Ottawa has faced more than its fair share of very destructive storms over the past few years, we have Yes, I can't remember which Victoria Day weekend where we had, I didn't ever know how to say it the derecho or the derecho. So there, we weren't getting storms we've never even heard of before. And unfortunately, I think that is our new normal. So, grid resilience is something that we are very concerned about, and we need to make sure we've got the appropriate investments for that. So those are just a few of the highlights that, you know, when I came into the sector sort of things that were kind of ramping up, and then what's happening now, but I guess what I could say, the commonality is there's constant change in the sector. And what I'm seeing going forward is that change is going to be accelerated.    Trevor Freeman  13:40   Yeah, I mean, it's, it's fascinating to listen to you lay it all out like that. Thinking back to 15 years ago, it's hard to even remember, you know, not having smart meters, having meters that really just ticked forward and measured your consumption over the course of a month, and someone would come and read that. And, you know, having declining or even flat demand profiles that aren't increasing is so different from the world that we are in today. But I think what you said there at the end is really important. We are in our industry, an organization that knows about change, we're constantly changing, which helps us as we look forward into your point, we're going to see that level of change and the pace of change accelerate. So, I think that sets us up pretty well. So, let's start to look forward, then I know that the EDA is about to launch a new vision paper. So, we're going to dive into some of the details. But maybe let's start by kind of a high-level summary of what is the vision that you are trying to lay out with this paper?   Teresa Sarkesian  14:42   Okay, and no problem. So, I think what I want to start just give a little bit of background as to why we did this. We've done a couple of vision papers and implementation plans in the past. But you know, they were like seven, eight years ago and things have changed a lot even in Seven or eight years. So, what we've been seeing, obviously, I think the big change over the last few years has been the big focus on meeting Net Zero targets in 2050, that we are going to get to net zero in terms of our greenhouse gas emissions. Not only in Canada, but this is actually a bit of a global commitment, you know, for countries that have signed on to that objective. So, what happens when you set up, you know, those big audacious goals? You have all kinds of organizations and entities looking at how are we going to get there, how much it's going to cost? What do we need to do to get there? And so when we started reviewing some of these publications, both in Ontario, Canada, and actually in other jurisdictions, they were very good. They talked about what supply mix that we need the investment in transmission, but almost 100% of the papers, Trevor, if you can believe this, just neglected distribution, no one talked about distribution, they didn't talk about how distribution is going to have to change what the investments would be. And then we'll so we said it's going to be critical for us to identify the electric utility role and the energy transition, and how the sector will need to be grid ready to support electrification, economic development, grid resilience, and customer preferences. So we view that LDCs are going to be pivotal in enabling Ontario's low carbon economy, navigating the challenges posed by climate policies, electrification trends, and these evolving customer demands. And with Ontario's growing economy and the demands for housing intensify, LDCs must innovate to effectively meet these accelerating electricity needs and changing preferences. And right now, we've seen the ISO is predicting significant consumption growth from 144 terawatt hours in 2023, to 240 terawatt hours and 2050 not quite double, but it's getting close. And so this rapid growth demands urgent attention to adopt new strategies and to ensure that the local distribution companies can make the necessary investments in grid enhancements to expand the capacity and capability of the distribution system. So while reliability and affordability remain Paramount customers do expect additional value from their utility service. And, you know, we are seeing all sorts of things that are happening, you know, such as the need for swift electric vehicle charging installation, and other upgrades that will increase the electrical load. We see that LDCs are more frequently interacting with businesses that seek utility partners to achieve their energy management, sustainability and ESG goals. And in parallel, the LDC must prepare to respond to increase climate change induced extreme weather events. So recognizing the essential role of LDCs in the energy transition, we've worked in collaboration with industry experts to outline a vision of the role of utilities, so they can enable economic development, housing growth and electrification. And the report identifies urgent and practical steps that LDCs in partnership with the government, and its agencies must take in the near term to achieve the benefits of this transition. So what you'll see in the paper is recommendations related to the need for clear policy direction on regulatory frameworks to support LDCs in becoming grid ready, and with a continued focus on affordability and enabling a customer choice and opportunity. And we also discuss issues like workforce needs. And we also emphasize the role of human capital in enabling technological advancements. So that's very high level what it is, and I will get into it a bit more as we have our discussion further.   Trevor Freeman  18:41   Yeah, I think it's a good way to frame it of the entire sector is changing at all levels. But what you're really doing is laying out that vision that roadmap for the distributors, in particular, and I think that's great. Maybe like, Who is the audience for this paper? Who are you kind of directing this at?   Teresa Sarkesian  18:59   Well, we're still putting the crossing the T's and dotting the I's., but I think it's about 80 pages. So, it's not going to be for everyone, obviously, you know, government decision makers, government, policymakers, people that work in their regulatory agencies and our energy board, the Independent Electricity System Operator, we did try to make it accessible. There is an executive summary that's about two or three pages, which I think will be of great interest to a lot of people to read. And I think it gives a very kind of a high-level overview of what's in the document. So that's something that we're trying to do. And, you know, obviously our LTC members are an audience as well. They've been working with us hand in glove the last few months we've had extensive member meetings we had a board committee that helped steer this paper. But you know, ultimately, the paper is really focused on our customers because its customers and businesses that are driving a lot of this change for the future, whether it's businesses that are on their own journey on environmental, social and governance ESG objectives, and they're looking for more low carbon communities to invest in its customers who are very interested in EV charging, and maybe what the opportunity for the batteries can be to sell that storage back to the grid. It's, it's really the customers that are driving this change.    Trevor Freeman  20:31   Right Yeah, and I mean, the nature of this medium is I don't know who's out there listening. But I'd encourage, you know, all of our listeners, when this comes out, take a look at it and get some insight into kind of how the distributors role is laid out there. So let's dive into some of the details. You know, you outline obviously, some of the traditional roles and functions of the LDCs. So from maintaining, owning and maintaining the infrastructure, the poles and wires, and doing customer metering and billing, that stuff's not going away, we're gonna keep doing those things. But you also highlight some of these emerging roles that have begun to appear, or that we'll see in the next couple of years, you know, a more of a focus on distributed energy resources, like solar on roofs, for example, that LDCs are going to have to work to both enable as well as integrate into our own systems. It's going to include things like more customer programs, and rate design, etc. I'm curious, you know, how are LDCs going to balance that traditional role that we've already been doing, along with this rapidly new expanding set of roles that we need to tackle?    Teresa Sarkesian  21:38   That's a great question, Trevor. So look, LDCs will continue, as we always have been to be responsible for safe, reliable and affordable delivery of electricity to customers, customers can count on us to do that 24/7. And even with all these anticipated grid expansions, we're not going to be shut down, if the critic dispatches so, you know, we're experts at multitasking in our sector, and we will continue to do so. And with the increases, as you mentioned, in distributed energy resources, and electrification, there are the pressures for us to adapt, modernize and change how we ensure the safety and reliability in the service to customers. And the emerging roles and responsibilities aren't something that's in the distant future. You know, as I mentioned before, changes the constant, we have been engaging in ongoing adaptation. And so when I think about the future, and I think about what we call grid modernization, it really is part of the ongoing continuous improvement, and the pursuit of the digital utility of the future, that every utility is on that journey. So you know, utilities have been bringing in new technologies, particularly related to information technology, communications, and digital solutions. And so while we're in early stages, we are expecting our members to become more digitally based in the future, they're going to be introducing advanced distribution management systems to monitor the grid. And they're also going to have distributed energy resource management systems to monitor all the connections that are behind the meter. So I think what is different now than in the past, is simply that the pace of change is being dramatically accelerated. So for example, it took us about 100 years to get the grid to its current size, yet, we need to almost double the current grid in 25 years. So we have to move four times as fast. And the grid is not going to be built with just simple poles and wires and one way energy flow like it has been for basically the last 100 years, it's going to be a lot more complex, we're going to see two way energy flows, so it's not just us sending power to the customer one way, they're potentially going to be selling back their energy generation or their energy storage back onto the grid. So we need to have that temerity, that two way, power flow. So that's going to be a big change. And we also expect there to be a lot more customer interaction. They want to leverage their own generation and storage behind the meter. And we as utilities, want to be able to leverage that to help us with you know, reliability, Storm outage, other emergency situations. So we see there's going to be a greater interactive relationship with customer than simply, you know, maybe sending a bill to them or offering them conservation programs, it's going to be much more dynamic than it has been in the past. And so, you know, over the last two decades, and we talked about this a bit already, the utility has been modernizing the system in response to government policy initiatives, regulatory requirements, and customer preferences. One other example, recently, utilities were required to implement something called green button. And we've been also engaging by bringing them more into the system through net metering. And a lot of our members are also involved in various pilot projects with the Independent Electricity System Operator and with Enercan to look at all kinds of new LTC models and functions. So and you're going to see a lot of this actually, in our vision paper is that to really be effective, cost effective. To make sure this happens at the accelerated pace, we do need for there to be proactive policy and regulatory changes, to remove barriers and empower LDCs to embrace these new evolving roles in shaping the future of the energy sector. And as I mentioned before, customers are demanding it. And I want to point out a research report that came out by the International Energy Agency just late last year. And they made it very clear that in quite a number of countries around the world, the lack of the regulatory permission to provide more investments in the distribution system is now becoming a significant barrier to new renewable energy projects connecting on the system. And while we don't have that situation here in Ontario, if we don't start moving quickly, in terms of reforming the regulatory context, then we might be like some of these other countries, and we don't want to be that a barrier, you want to be able to enable what our customers want on the grid.    Trevor Freeman  26:07   Yeah, so I'm going to ask you a question about that last point in a minute. But I think your framing of the ways that the sector is going to change, and the way our customers are going to interact with us is going to change is really great. And it's something that you know, often comes up in conversation. And I often say, there is no single strategy or tool here, we can't solve the coming challenges with just more poles and wires. We can't solve it with just new innovative solutions, we need all of those things, we need more poles and wires. But we also need more programming, more innovation, more technology, we need to utilize those distributed energy resources out there on the grid. So, I think that's a great way to frame it. Okay, so let's talk about grid planning a little bit. So LDCs play a really key role in helping forecast the needs of the future, both for our own distribution systems, but also feeding up into those broader provincial needs. So, the insight that we gain from our customers, we pass up to the IESO, for example, so that they can do planning at the provincial level. Traditionally, this is a pretty consistent process. You know, in the past, we get a sense from municipalities and developers, how cities are going to expand and grow. And we've generally been able to count on the typical home using roughly the same amount of electricity as homes that are out there today. So, we account for a certain expansion of commercial customers based on the Intel that we get from those customers. And we know roughly what they're going to use. The problem is that model's kind of being turned on its head a little bit. So, we now need to account for even our existing customers increasing their load because they are electrifying or they want to add EV chargers. And new developments today are likely going to have increased demand compared to some of the historical developments, because we're going to see all electric communities or at the very least more electrified and uses. So I know you don't have a crystal ball yet that tells us exactly how this change is going to happen. But what are LDCs doing to adapt their long term grid planning to account for this uncertainty?   Teresa Sarkesian  28:22   Yeah, you're so right, Trevor forecasting is getting more challenging. And I just want to start with a little story before I get into my answer about that. So, you know, electric vehicles are kind of the hot thing right now. And you know, although people I think are still on a waiting list for certain cars, there's lots of others that are available. And so one of the concerns that our sector had was we didn't know where these electric vehicles were going to pop up. And we weren't getting any kind of pre advanced warning when people started making orders or, you know, advanced purchases for electric vehicles. So we actually did a great advocacy campaign, with the province with both the Ministry of Energy of the Ministry of Transportation, to secure postal code data for utility, so they could see where people were going to be purchasing electric vehicles to help them with their own planning, in terms of, you know, making sure that their local feeders were upgraded their local transformers, and so that just got announced a year ago. But that's obviously not going to be good enough. And that just tells us about electric vehicles, you know, in the near term, but this is I think, you know, having sightlines into our customer behavior, whether we do that proactively with you know, consultations and communications with customers, or we can do it by you know, pinging the meter, or getting data such as postal codes. We are going to have to, you know, adapt and have greater visibility and sightlines into the customer. And so this is that some of that technology that I was talking about earlier, the sophisticated future grid is going to need lots of visibility and transparency, for usage and investment to be able to, you know, look at these two way power flows, look at how customers are behaving, in order to better plan the system, we also need to maximize and optimize the data that we have, you know, from our planners, it's going to be vital to protecting the grid reliability and resilience, we're going to have to have more partnerships with municipalities, in terms of their energy planning for the future and things that they want for their community. And, you know, one of the things that we're asking for on our paper is actually to, you know, rethink the distribution system plan, that the utilities have to file with the OMB every five years, and start building in a, you know, Grid Modernization plan within that broader plan. So we can get the regulator to start looking ahead and seeing what these requests are, it'll be important to also have various performance metrics and filing guidelines for grid modification from the energy board. So you know, these are some of the things I think that the membership is going to have to look at but it is going to be a very iterative experience, because it's just it's the pace of change is the big unknown. And so everyone talks about these things. But you know, I saw something today, I think it was from Ford Motor Company, and they're kind of slowing down, it's taken them a while to retool their plants. So that could take an extra two years now for them to be up and running and producing electric vehicles. So there's going to be all these other pieces of the puzzle that are constantly going to be changing a moving and evolving. It is I think, planning for the future is going to be very challenging. And I do expect the province to start talking about this higher level, maybe starting at the end of this year, they just came off a massive exercise related to the energy transition electrification panel. And I do expect to see more guidance from the province as well, in terms of how they're going to manage this planet, because it's not just planning for us. It's planning for everybody else in the system, too.    Trevor Freeman  32:02   Yeah. And for listeners out there, if you haven't had a look at that energy transition electrification panel reports, a really fascinating read. So I'd encourage you to take a look at it. You mentioned a lot of interesting things there. So for our listeners, and I'll probably do a future episode on this so I won't get into detail, but LDCs typically have to file five year rate applications once every five years that really lay out their plans for those five years and how they're going to fund them. So coincidentally, hydro Ottawa was getting ready to do our next one. And like I said, I'll probably talk about that on a future episode. But one thing we did when it comes to forecasting is, we conducted a electrification study that looks at if we electrify by 2050, like our plans, say we will and you know, society wise, what does that mean for the grid? And some of the inputs we took is, you know, what are the federal plans for electrification? What are our own municipal plans for electrification? What are we hearing from our customers, and that really, is helping us modify and change how we do grid forecasting, based on some of the changes that we're seeing from our customers. So I think this is a really important piece that, like you said, we're going to need to iterate on we're not going to get it right the first time. But we're starting to think of how do we need to change the way we do things in order to keep up with what our customers are doing.   Teresa Sarkesian  33:28   I think one thing I've seen more of the last few years, because this is much more complex than it's been in the past that I've seen, like the IESO, for example, they've done more, you know, scenario setting. So when they've had their, you know, their APO's and AER safe, they sort of had other two or three scenarios, and they're constantly updating their numbers every year. So these are other changes that we're starting to see. And even myself, I was just looking at the provincial budget detail the other day, they also set out, you know, scenarios as well. They're just not picking Oh, it's going to be, you know, X amount of deficit. And you know in 2028 they're actually forecasting out different scenarios. So I think that's another piece I see more in play, that people will, you know, showcase what assumptions they have, and will have maybe two or three different scenarios as well.    Trevor Freeman  34:21   Yeah, and I think it's a, it's a great way to tackle that unknown component to where we've never really been through a change like this before. We've never wholesale changed the way we use energy in our society. So there's a degree of uncertainty, obviously, and I think, targeting out that kind of, let's call it high, medium, low scenario, or whatever the metric might be, is going to be really critical for us to make sure we're staying within the boundaries of what's possible and what's probable and refining that constantly as we move forward. So that's a great point. Something else you mentioned a little bit ago, that's, you know, could be a bit of a nebulous term is grid modernization now I've actually got a future episode, and specifically about grid modernization and what hydro Ottawa is doing, I think it might actually be our next one. So we don't need to go into all the details on this. But let's just help our listeners understand what do we mean when we're talking about grid modernization? And why is this important? Why is it important to our customers that we do this kind of back office improvement?   Teresa Sarkesian  35:23   So I'm going to keep it really simple, because I know you're going to do a deep dive on it and a future episode. But essentially, Grid Modernization are improvements that LDCs will make simply to augment our capabilities, and enable us to offer new or improved services to customers. So back office improvements might look like things like real time sensing, and monitoring systems to improve efficiency and reliability. Or we may be investing in new digital infrastructure communication systems to improve safety, cybersecurity, it can also include more visible improvements to safeguard our infrastructure against extreme weather, and climate change to reduce outages. And like one, I guess, example that some of your customers might already be recognizing, you know, we made investments in green button, which enables customers to download their data, send it to a third party if they want to save on customer use. So it really is the whole soup to nuts, it really is not just one type of technology or solution. It is a combination of a whole series of things that the that the utility will need to do. And I think why we want to do it, I think when we look at all of the pressures on the system, from NetZero objectives to housing priorities, you know, to accelerate broadband development, and support electrification, the pressures seems to be never ending. And the only way that we can respond to all those pressures, is to be grid ready. And, you know, like I said, it's it is a form of continuous improvement. It's just that now it's the pace accelerated pace is such so extraordinary, that we need to have a more dedicated plan. But most importantly, we have to make sure we have dedicated attention by policymakers and regulatory decision makers as well. Because right now, there isn't that dedicated attention to this very important task. Yeah,   Trevor Freeman  37:28   Yeah, I mean, it's, it's great that you bring up all these pressures that we're feeling that it's I think it's time we kind of talk about that elephant in the room, our customers often ask us about affordability, or we're hearing from our customers about affordability, I was actually at a customer event not too long ago, and talking about the change that we're going to see here talking about some of this, you know, large scale transition of our of our energy sector. These are not small investments that we have to make. We're talking about both an increase of our infrastructure, you know, you mentioned almost doubling the capacity of the grid. We're talking about modernizing our grid systems, that's a lot of back office work with new technology, and bringing on new programs. Like this is a big change. Energy affordability is already a kind of a challenge today for some folks. So as we get into this new investment that we have to make as we start moving down the path of the energy transition, how do we balance affordability, especially for our vulnerable populations, with the level of investment that we know is necessary to do the things that we have to do? Yes,   Teresa Sarkesian  38:42   Yes, that's the multibillion-dollar question, Trevor. And it's something I'm going to carve out my response, because there's some things that we've put into our vision paper for the future, because affordability is absolutely critical. And as you know, this is basically a massive restructuring of the economy going forward. So, there's may be other participants who might be playing a funding role. So, you know, right now, obviously, you know, customers aren't monolithic, and you know, residential customers who are struggling to pay bills. Do you have some programs that they can, that they can access, they have the low income Energy Assistance Program, they have the Ontario electricity support program. Some of those are funded by the tax base, some are funded by other electricity customers. The province also gives a rebate to customers in Ontario, and that's a pretty big rebate. I don't think a lot of residential customers are aware of it but it is over 7 billion annually to residential small business customers. That's a lot of money. But I don't know if customers really appreciate that. So I don't know what's going to be available going forward. These are some of the challenges that you know policy makers, you know, have to address as well. So, when we were thinking about this as part of our paper, we sort of looked at it from a number of perspectives. So, the federal government has set up all these Net Zero targets, they've set out, you know, targets for electric vehicle manufacturing, as well. And so it might be appropriate for them to share part of the burden with this massive energy transformation. And it's interesting, we actually pulled customers about 2000 Customers two years ago, we asked them a whole series of questions about the changes going forward. And customers do have different perspectives about who should be paying for some of this energy transition. So when we asked them about who should be paying for electric vehicle, charging infrastructure, and they said, Oh, electricity, customers should pay for that, because that's something that everyone's going to benefit from. When we ask them about, you know, who should be paying for the electricity grid, to address climate change and hit Net Zero targets, they actually the majority, 58% said, the taxpayer should be paying for that. So I think that's just a very interesting data point. But it's something that, you know, we've been active on in terms of having those conversations with the federal government, saying that, you know, you have offered different subsidies to attract different companies to invest in Ontario, based on our clean grid, but we need to have the whole grid support it. So, you know, we're pursuing federal government support, we also are looking at increased maybe private equity engagement in in our sector. So right now, we have a couple of private members, but there's not a lot of private equity money in the sector, most of our members are municipally owned, and municipalities can't invest in their utility, probably even if they wanted to, because they're in short supply of funds as well, they have their own taxpayer that they have to deal with. So one of the solutions we are putting forward to government is to increase the private equity threshold, so it doesn't trigger additional taxes, right now, it's only 10% ownership. But we're saying that maybe a tool in the toolbox should be up to 49% ownership. So it would allow private equity to come the patient capital, they're not maybe looking to seek a return right away. So there's some you know, flexibility there as well. Another thing we're looking at is to revisit the debt equity ratios of utilities to manage the costs over the long term. So you'd be effectively amortizing on some of those grid investments as well. So these are some of the ideas that we have around how we can basically fund the energy transition going forward. You know, and some people say, Well, if you could get customers to think about their energy usage holistically, so if they're going to be, you know, moving away from a, you know, a combustion engine car, and they're going to be using heat pumps, instead of, you know, natural gas heating in their home, if you could get people to think holistically what they're saving on the kind of, you know, GHG side of things, versus what they are going to be spending on electricity, they may actually be spending less if they look at it holistically, but I don't really know, to be honest with you, so that I'd rather focus on the things that we could ask government for, as opposed to asking customers to be, you know, thinking more holistically at their entire energy usage, which is just not how they think. And I think, to change that behavior, would be quite a monumental task going forward. But those are some of the things that we think about, because we are very concerned about the affordability going forward, because it is such a massive change that we're all experiencing.   Trevor Freeman  43:50   Yeah, I think this is another example of there is no single solution here. There is no you know, silver bullet that's going to help us pay for all of this, we need all the tools on the table here, we need to look at all different options. And I think you outlined a couple of them, you know, in what you said about our customers impression of some of this change and who should pay for it. Last episode, I talked to David Coletto, from Abacus data, and he was saying on the whole Canadians really believe that a an electrified energy system, we know once we make that transition, we will be more secure, it will be more affordable. And I think those customers who have made some transition in their lives can see the benefit of that. But sometimes the initial hurdle is pretty hard to get over that upfront capital cost. And so looking for ways, both at the customer level as well as at the utility level, the LDC level I think is going to be important to help get over that initial capital outlay that's required, so that we can realize those benefits that we all know where they are that we know we'll see. So . Yeah, great filling some of those out. So I know I mentioned that I will get back to this. But I do want to talk to you about the advocacy role that the EDA plays. So you mentioned, you know, talking to governments and Ontario, the provincial governments across Canada, the provincial government has jurisdiction over most energy matters. So advocacy to the government is a key role that you play. I'm curious, what are you asking the government to do or to provide to help some of these changes that we're talking about happen? What is the advocacy that you're pushing for with the government.   Teresa Sarkesian  45:32    So I'm going to try to keep it really simple and just sort of, you know, tie it back to our vision paper for now, because at any given time, I'm working on 20 or 30 l policy issues, primarily with the Ontario government. But this past year, we have expanded our work to also include the federal government, because they have investment tax credits that we are interested in for our members to see if they could be eligible for those. We're interested in them changing things to the Canada Infrastructure Bank, also to provide new sources of equity there. And we're also pursuing grants, as well, for grid modernization. So provincially, a whole whack of issues. But I'm going to go back to our paper just to give your audience a little bit of a sneak peek on some of the things that we're going to be asking for. So one of the first things we're going to be asking for is to get a common understanding and definition of grid modernization, and electrification. And this is not really new of an idea, we kind of have copied it from the US, there's a lot of jurisdictions, there where very clear objectives that have been set out in order to justify grid modernization, investments. So we think that it'd be beneficial for Ontario to do that, because then once you have those objectives in place, it is going to make it a lot easier to be able to prioritize grid modernization capabilities, functionalities, and investments in line with those objectives. You know, and then from there, you know, we're looking at creating a series of foundational investments. So going forward, some of the things that we think are foundational, are things like the distributed energy resource management systems and the advanced metering infrastructure, which is sort of like smart meters 2.0, for lack of a better term, and also the advanced distribution management systems. So we see those are going to be foundational pieces that all utilities are going to need to be able to help customers interact with the grid, and they're going to be necessary grid investments. So how what we see for those is we would like it to be similar policy direction, like we had for smart meters and green button, where you have government mandated activities. And then those are given, you know, a kind of lower standard of evidence with the Ontario Energy Board to support that capital infrastructure, they're deemed as priorities and ties back to that initial plan, where you set objectives, as long as those objectives can be that then those should get a pass through.   Trevor Freeman  48:12   If I could jump in right there just for our listeners. So what Teresa is describing here is, at the moment when there are unique things that are not part of government mandate, yet every LDC and Ontario, of which there are many 60, something I don't even have the number in front of me but every LDC when it comes time to enact that project has to go through a whole exercise of justifying it proving why it's necessary, saying this is why we want to do it. If there was some commonality across LDCs in the province, we wouldn't have to put as much effort into, you know, the report writing side of it, we could just get down to business and make these changes that we all know across the province are important. So I think it's helpful for us to understand how that process works.    Teresa Sarkesian  49:00   Yeah, and thank you for interjecting on that, Trevor, because if government wants us to move fast, we can, but we need that certainty. So you know, we're no different than any even though we're regulated monopolies. We're really no different than any other business that wants to do business in Ontario, you're always looking for certainty and clarity, from legislation from policy from regulation, because the uncertainty is what slows things down. Another recommendation that I'm moving forward with is that we need to move beyond pilot projects. I had a conversation with a consultant who is working with Enercan on this and they want to move beyond I love their term, death by demonstration. We've got a couple of dozen pilot projects currently in the sector, whether they're funded provincially through the IESO or they're funded federally through Natural Resources Canada, and you know, there's some very exciting results that are coming out of those. But some of those pilot projects have been going on for all almost four years, in one case, almost five. And at some point you need to pull off the band aid said, Yes, this is a success, all LDCs would be eligible for funding in this. So we need to be able to scale it up. Or we just say no, that's not going to work. But being in this constant state of the pilot projects, while it's informative, at some point, someone has to have the courage to say we're moving forward, this is going to be scalable. Another recommendation we have is to create an action plan to develop a comprehensive human resource strategy to address quantity quality, and partnership aspects of the labor force going forward. There's some great work that electricity, Human Resources Canada has done. And, you know, DC 28,000, replacement and new jobs in our sector, by 2050 and that's, the electricity sector at large across Canada. And I did some, I think back of the envelope calculations to try to figure out, okay, some assumptions about distribution. And we're looking at close to 10,000 new positions in the sector, over the next 25 years. Every sector is having challenges, filling current jobs, never mind jobs, that we're not even sure what they are quite yet. So we don't necessarily have the right programs at the universities and colleges or private training institutions to start getting the right people and talent into our organization. And, you know, so we need help for that. And, you know, I am encouraged, I saw a little announcement out of the province yesterday to have more electricians down on the Chatham Kent area, because that's the whole greenhouse industry. And so I said, Okay, that's exciting. So people are starting to pay attention, but we need it more than just in one local community, it needs to be province wide. And, you know, like I mentioned before, we need to have more conversations about what the funding models are going to be to fund the energy transition. So these are some of the issues and recommendations that we're taking forward from our vision paper. But day to day, I guess that's the other thing, I want to mention in terms, the change I've seen, I've never seen us work on so many issues, prepare so many submissions, invest so many staff at various tables and working groups. And we love doing all that work. We love representing our members at every table of discussion possible, but I've never seen so many. And they're not just oh, you're there for a month, and you're done. Some of these they are multi year. So they have longer legs, because they are far more complex. But you know, we're working every day, you know, for members that way. Very, very proud to represent our sector think it's a fantastic sector. And the fact that they're going to play such a pivotal role in the future makes us only want to work harder to make sure we get the best of everything for our membership.    Trevor Freeman  52:54   Yeah, I know, we echo that at our level, we can certainly see a lot more stakeholdering and engagement happening with all players in the sector, but especially the government as they figure out this energy transition to right, let's not, you know, let's not forget that the government needs to figure out where policy needs to go to lead it, and it's a great role that you're playing to kind of bring the voice of the distributors to the government. Because again, as we've talked about a couple of times, we're really on the front lines, and we're hearing from our customers, and we're seeing what needs to change right at that customer level, in order to enable some of this stuff that's happening so that that conversation between the LDCs and the government I think is really important. So you know, we don't work in a vacuum, I just mentioned a number of stakeholders in our sector. And I highlighted the interconnected nature of our grid at the beginning of our conversation. There are a lot of different players working together to really, at the end goal is bring power to the customer. How do you see the existing model changing or expanding in terms of, you know, the kinds of partnerships that LDCs have moving forward? So you know, you mentioned private equity is being a potential upcoming role. There are things like technology companies that are developing innovative solutions, who, you know, we maybe were a bit more arm's length with in the past. There's a changing nature of our relationship with the customers, you brought up the idea of going from one way power flow to kind of two way back and forth. arrangement. How do you see that partnership evolving in the future?   Teresa Sarkesian  54:30   Well, I think the good news is, there's a very strong foundation knowledge to build on. So I'm going to talk about three different areas. I'm going to talk about sort of shared services across utilities, and I'll talk about a partnerships with the private industry. And I'd like to talk about the engagement with customers as well. So firstly, there's lots of shared services going around in the industry already. There's all kinds of partnerships that members are trying to reduce costs for customers and find the best solution. So instead of saying, having 60 utilities run, seek out the best solution, you know, you get everyone working collaboratively to find a solution at the best price for customers. So we've seen a lot, just in my 15 years I've been there you've got in the past, there was, you know, common delivery of conservation programs, members work together on common engineering standards, lots of mutual aid assistance agreements across among utilities, for Storm Recovery. I've seen shared billing services, bulk purchasing products, and shared control room practices and services. And I've seen private sector play a much bigger role in utilities, as well. I've had the privilege to attend some openings, and launches of micro grids, where you have maybe a solar company and an energy storage, battery company, that are part of that group with utility, creating a micro grid for their community to provide maybe warming and cooling charging services when there's a major outage, for example. And I've seen now, some smart grids, you know, one that's already been implemented up in the north that has a significant private sector partner. And I've seen it also there's a new one, that's another one in the north, that's going to be developed with a private sector partner. And I've seen, not just Ontario businesses, I've seen what businesses come in one of our members is doing a distribution system operator pilot model with a partner in from Norway. So I'm really encouraged, I think the foundation is already there to kind of build on all those successes we already have, and do more, you know, and we talked about the customers going forward as well, that they're going to be to help playing a role, or we hope they're going to be playing a role. Because there's a lot of energy, battery storage and solar generation, sort of behind the meter, whether it's a farm, or it's a residential customer, or it's a big industrial customer. And so we want to be able to optimize all of those resources into the system to be of benefit to all customers to reduce costs. But we'd have to give an incentive to those customers to participate, no one is going to let you know a utility access their, you know, solar panel generation or their battery storage, unless they're going to be getting paid to do so. And I think that's going to be really important going forward, because we don't want to over build the grid, I mean, the grid is going to be so big, going forward. And we have to find ways to avoid over building it. Because we don't want to be in a situation where you know, customers are having to pay too much for a grid that's not properly optimized. So trying to find solutions behind the meter, that will maybe either avoid or delay bigger generation investments or transmission investments, or even actually distribution investments, we want to optimize that. But right now, there's not really a lot of permission to do that. So we need to get that legislative and regulatory permission to do that, to turn those, you know, more passive customers into prosumers, that they're basically your their proactive customers by selling their energy storage back to the grid. So I'm really optimistic. I think we've got a great foundation work to do on the customer peace, letting them participate as prosumers and the system, but I'm pretty optimistic that that we can get that job done.   Trevor Freeman  58:27   Yeah, I think it really highlights, there's a lot to be excited about when it comes to the change, that's going to happen. There's a lot of opportunity out there both for the LDCs, for the other stakeholders for our customers, that this energy transition, this change is going to bring about, you know, there's some challenges to I know, he talked about the challenges. I wonder, though, what do you see, as you know, one of the single biggest are a series of risks to achieving the vision that you've outlined in the paper, how could this go off the rails and not happen the way we need it to happen?   Teresa Sarkesian  59:03   Well, I always like to be glass half full as opposed to half empty, but you're taking me down that road? Trevor? So I'm going to answer that question.    Trevor Freeman  59:11   It's my job.    Teresa Sarkesian  59:11   So you know, obviously, our vision for the future role is big, but it's practical. The energy transition is upon us now. It's not something to contemplate for the future. So we think that the biggest risk is effectively inaction or kind of, you know, kicking the issue down the road, 510 years. We're seeing this right, nearby jurisdictions in the US are taking action. There's been significant funding out of the Biden administration, for all kinds of initiatives from you know, cybersecurity, to grid modernization down there. They're doing they're very competitive. They want to attract businesses, to the US. And so, you know, that's a major competition for Ontario. So if we don't seize the opportunities to kind of start working on these important issues now, we could lose economic development opportunities, we could lose jobs, we could lose investment, we could lose our talent as well, that may want to move to another jurisdiction. So to mitigate that risk, the LDCs, and policymakers have to work together on developing a shared vision around electrification and grid modernization, develop a plan of action and create a realistic timeline to turn that vision into reality.   Trevor Freeman  1:00:26   Yeah, it's a it's a great point. And I think it's important for people to understand that change is happening, the change is going to happen, whether we want it to or not. And, you know, often sometimes people say, Are we are we really going to see this change? I think we're already seeing it, we're already seeing customers want to change the way they interact with energy. The risk here is if we don't react quick enough or properly enough, the costs of that change becomes higher the reliability of the grid that we're working with, goes down, that general customer experience is not where it needs to be. And then you've highlighted some other ones, you know, we can really struggle with talent if we're not offering them the kind of cool innovative roles that they're looking for. But the neighboring jurisdiction is, so it's not so much that the change may or may not happen, it's how do we react to it in a way that really serves all of our stakeholder the best. So, Teresa, this has been a really great conversation. And I really appreciate you taking the time to join us and chat with us today. I think there's a number of things that we talked about today that really set up future conversations I'm going to have nicely. So thanks for the half for teeing that up. And this is your second time on the show. No doubt, there'll be a third time because I think there's a lot more that down the road, we can we can pick apart. So thanks for that. We typically end our interviews here with some common questions to all our guests. So to start off, what is a book that you've read that you think everybody should read?   Teresa Sarkesian  1:01:56   So one I recently enjoyed it's by a friend too. By Darrell Bricker, he wrote Empty Planet, and that is very, very good talks about actually declining global population. And what that means from everything from, you know, businesses to climate

This week's theme: “Getting” It All Done Explore the powerful mindset shift from ‘having' to do something to ‘getting' to do it and discover the profound […] The post “Getting” It All Done with Laura Casselman appeared first on Heather Hansen Oneill.

Guest:   Barry Casselman, The Prairie Editor.  We will discuss the state of the nation and the US Senate elections....and other stories.... You can check my blog...... Check out Carlos Guedes and his music.  

In this episode of ClickFunnels Radio, co-host Ben Harris welcomes bestselling author and CEO, Laura Casselman, to share her journey and experiences. The conversation touches on online marketing, funnels, making money to achieve personal goals and the importance of sharing knowledge to help progress ourselves and others. Tune in to gain valuable insights from Laura's successful career and entrepreneurial journey. To learn more about Laura, check out her website: https://lauracasselman.com/home/

Join us on 'Got Clutter? Get Organized with Janet' as we embark on a captivating journey with Rebecca Casselman, a multifaceted director, actress, writer, and military spouse originally from North Pole, Alaska. In this episode, we'll explore the intertwining paths of creativity, personal growth, and organization through Rebecca's eyes. From the stress and overwhelm caused by disorganization in military life to the tips and strategies for maintaining order and balance as a wife, mother, and podcaster, Rebecca shares her unique insights and experiences. Plus, we'll dive into her creative ventures, from co-hosting the 'Candy from Strangers' podcast to her upcoming feature film 'Next to North' and her novel 'The Fourth Fate.' Whether you're a creative professional, a military spouse, or anyone looking to infuse more organization into your life, this episode is packed with inspiration and practical advice to help you on your journey." This description aims to capture the essence of Rebecca's journey and the valuable insights she will share on your podcast, making it an enticing listen for your audience. Connect with Rebecca Casselman Instagram: https://www.instagram.com/rebecca.casselman/ Got Clutter? Get Organized!" has officially claimed the #1 spot among the top 35 organizing and decluttering podcasts.

Welcome to the next episode of the Measure Success Podcast, where the extraordinary journey of Laura Casselman unfolds. From the dazzling stages of Radio City to the strategic boardrooms as CEO of JVZoo.com and co-founder of Vita Street, Laura shares her unique trajectory to the pinnacle of business leadership. In this episode, Carl J. Cox delves deep with Laura into the essence of strategic planning, affiliate marketing mastery, and the significance of resilient leadership in carving the path to success. Laura, also a Wall Street Journal bestselling author, enlightens us with her revolutionary insights on overcoming industry barriers, championing customer service, and the meticulous balance between personal life and professional ambition. Key Takeaways: Laura's inspiring transition from performing arts to corporate excellence. Strategies for leveraging affiliate marketing to scale your business. The art of strategic planning for sustainable growth. Cultivating a culture of accountability and innovative leadership. Laura's story is not just about career transformation; it's a testament to the power of vision, determination, and strategic action in achieving success. Her insights are invaluable for anyone looking to elevate their business strategy, leadership skills, or searching for the motivation to turn their visions into reality. Don't miss out on this episode filled with actionable insights and the inspiring journey of a woman who rewrote the rules to master the game of business success.

Andrew interviews their friend Liz Casselman. Liz is a Real estate attorney and partner at her family's law firm Halabu, P.C. She is also owner and Chief Operating Officer of Birmingham Title Agency and American Title Agency of Lenawee. She Earned her designation as a Certified Land Title Professional through the Michigan Land Title Association in 2023. Liz is also a licensed title producer agent in Michigan, Illinois, and Ohio.In addition to her work as a title agent, she founded Birmingham Exchange Company, a qualified intermediary facilitating 1031 exchanges all over the country, earning her designation as a Certified Exchange Specialist through the Federation of Exchange Accommodators. Lastly, Liz is also the Vice President of Gandol Inc., a construction and commercial door company.In 2023, she published her first book, “Not Just a Title: A Journey of Growth in the Title Industry

The World's #1 Personal Development Book Podcast! Join the world's largest non-fiction Book community! https://www.instagram.com/bookthinkers/ In today's episode we have the pleasure to interview for the second time Laura Casselman author of “Trust Your Increments” Laura is a CEO of JVZOO, Wall Street Journal and Amazon Best Selling author, former Rockette dancer, and a great mom! This is our second conversation with Laura and it's packed with value. We talk about everything from her speaking on stage with Tai Lopez in Dubai to becoming a successful human. In this episode, you'll learn about why you need to embrace failure today, how anyone can be successful with the right tools and coaches, about the dangers of TikTok and social media, why you should travel more and how it's not as out of reach as you might think, and why success may actually be very simple. There are a few spots that had a laggy internet connection but it doesn't take away from the conversation. We hope you enjoy this incredible conversation with Laura Casselman, ACTION ITEMS To Implement: ​​- Look into changing up where you live. It could save you money and put you in better energy! Research requirements, costs, neighborhoods, etc. - Brainstorm new challenges, goals, and projects to pursue. - Tap into the energetic "hustle mode" environment. Surround yourself with people pursuing big goals and feed off that motivation. - Don't be afraid to cut off unhealthy relationships that may be holding you back! - Consider organizing a mastermind group or accountability meetings to spark new ideas and momentum. - Explore options for expanding current businesses or launching new projects. Make a list of untapped ideas. - Reflect on being ready for "bigger things" and get clear on what that means for you. Set ambitious vision goals. - Get off social media and live your life. - Schedule time for strategic thinking and planning. Map out next level goals and timelines. To learn more about Laura Casselman and buy her best-selling book “Trust Your Increments” follow the links below: Instagram: https://www.instagram.com/thelauracasselman/ Twitter/X: https://twitter.com/Lauracasselman1 Website: https://lauracasselman.com/ The Book: https://a.co/d/7sWUv3k YouTube: https://www.youtube.com/@thelauracasselman Today's episode is sponsored by Audible. Try Audible for free: www.bookthinkers.com/audibletrial. The purpose of this podcast is to connect you, the listener, with new books, new mentors, and new resources that will help you achieve more and live better. Each and every episode will feature one of the world's top authors so that you know each and every time you tune-in, there is something valuable to learn. If you have any recommendations for guests, please DM them to us on Instagram. (www.instagram.com/bookthinkers) If you enjoyed this show, please consider leaving a review. It takes less than 60-seconds of your time, and really makes a difference when I am trying to land new guests. For more BookThinkers content, check out our Instagram or our website. Thank you for your time!

The current political situation with Barry Casselman.........The US Senate elections 2024.......Biden vs Trump......   ...Check our blog....and follow our friend Carlos Guedes......

In 1975, a body was found floating in the Nation River near Casselman, Ontario, Canada. It would take decades to identify her, and her killer.

The World's #1 Personal Development Book Podcast!  In today's episode we have the pleasure to interview ⁠Laura Casselman⁠ author of “Trust Your Increments” Join the world's largest non-fiction Book community! https://www.instagram.com/bookthinkers/ Laura is a CEO of a billion dollar company, Wall Street Journal and Amazon Best Selling author, former Rockette dancer, and balances all that with being a mom! Laura came from a small town and saw opportunity from a young age, she got to see the Radio City Rockettes and knew that's what she wanted to do, after a fulfilling career there she decided it was time to switch gears by entering corporate America. For better or worse it was filled with challenges from juggling her dance career to the worst kind of sexism, yet she didn't let that stop her undying belief that she was allowed to go after what she wanted. Now years later, she has achieved incredible things and continues on the path to greatness. In this episode, you'll learn about Laura's background and how she went from Rockette to CEO, about the power of being yourself by not compromising your values, how to get what you want in life, how to build confidence, the importance of setting your future self up for success, and how you can have it all. We hope you enjoy this incredible conversation with Laura Casselman! To learn more about Laura Casselman and buy her best-selling book “Trust Your Increments” follow the links below: Instagram: https://www.instagram.com/thelauracasselman/ Twitter/X: https://twitter.com/Lauracasselman1 Website: https://lauracasselman.com/ The Book: https://a.co/d/7sWUv3k Today's episode is sponsored by Audible. Try Audible for free: www.bookthinkers.com/audibletrial. The purpose of this podcast is to connect you, the listener, with new books, new mentors, and new resources that will help you achieve more and live better. Each and every episode will feature one of the world's top authors so that you know each and every time you tune-in, there is something valuable to learn. If you have any recommendations for guests, please DM them to us on Instagram. (www.instagram.com/bookthinkers) If you enjoyed this show, please consider leaving a review. It takes less than 60-seconds of your time, and really makes a difference when I am trying to land new guests. For more BookThinkers content, check out our Instagram or our website. Thank you for your time!

  Guest:   Barry Casselman, The Prairie Editor.....We will review the US Senate races in 2024.....and other stories........   Please check our blog or................. See Carlos Guedes' schedule........      

Welcome back to "Keep What You Earn," the podcast designed to help entrepreneurs like you scale your business, maximize your profits, and create wealth without the waffle. I'm your host, Shannon Weinstein – CPA, business owner, and your guide through the labyrinth of entrepreneurship. Today, brace yourself for an inspirational voyage as we dive into episode 450, titled "Fire Yourself to Find Success," with the extraordinary Laura Casselman.   Laura, the CEO of Jvzoo.com and co-founder of Vita Street LLC, joins us to unfold her journey from a professional dancer to a corporate powerhouse and successful business runner. She'll share her battle stories and strategies for climbing the corporate ladder, her unique approach to team building, and how advocating for fair pay is vital—especially for women in the workplace.   In this episode, we debunk myths surrounding female success and tackle the all-too-common issue of women underselling themselves during negotiation. Laura's advocacy doesn't stop there; she'll also discuss why setting clear goals and a detailed roadmap is essential to intentional planning and career success.   Expect a wealth of actionable advice as we delve into gender-specific communication behaviors, the art of negotiation, and how to maintain focus by anchoring daily tasks to your broader vision. Plus, Laura and I will reveal why it's crucial to "fire yourself" every 90 days to allow your business to flourish, as well as the importance of documenting processes for long-term stability.   Make sure you listen until the end for our special "CFO on demand" offer that's changing the game for financial support, and learn how you can connect with both me and Laura for continued learning and growth.   Strap in as we empower you to do more than just earn – let's ensure you keep what you earn. Let this episode be your starting point for the next leap in your business success story. Website: https://lauracasselman.com/home/ Instagram: https://www.instagram.com/thelauracasselman   What you'll hear in this episode: 08:28 Embrace playing the game, advocate for inclusivity.   10:38 Limiting opportunities, fostering scarcity mentality, urgent need for change.   15:00 Navigating gender dynamics and requesting to speak.   19:08 Establish objectives, document them, and strategize carefully.   21:09 Clearly defining and communicating goals is critical.   25:52 Ensuring documentation of repetitive tasks prioritizes business growth.   28:54 The 90-day cycle allows for refinement and growth.   32:22 Emphasizing transparency, self-care, and teamwork in the workplace.   36:01 Emphasizing the importance of long-term business sustainability. If you like this episode, check out: How to Make Sure Your Pay Aligns with Your Business Structure Tools for Team Accountability How to Hold Your Accountant Accountable   Want to learn more so you can earn more? CFO On Demand click here Visit keepwhatyouearn.com to dive deeper on our episodes Visit keepwhatyouearncfo.com to work with Shannon and her team Watch this episode and more here: https://www.youtube.com/channel/UCMlIuZsrllp1Uc_MlhriLvQ Connect with Shannon on IG: https://www.instagram.com/shannonkweinstein/   The information contained in this podcast is intended for educational purposes only and is not individual tax advice. Please consult a qualified professional before implementing anything you learn.

In this inspiring episode of our podcast, I had the amazing opportunity to chat with Laura Casselman, a dynamo who's danced her way from being a Radio City Rockette to a powerhouse CEO. Laura opened up about her incredible journey, highlighting how teamwork, discipline, and resilience played a huge role in her shift from the stage to the boardroom.She got real about the highs and lows of juggling motherhood with being a top-level exec and reminded us that motherhood really is the great equalizer among us. We dove deep into the nitty-gritty of business too. Laura shared some golden nuggets on managing finances, the importance of small, consistent steps for massive success, and why you shouldn't put all your eggs in the social media basket for business growth.What struck me most was her talk on the power of believing in yourself. Laura's all about self-love and being your own biggest fan, and she shared some personal stories and strategies that have helped her soar in her career. She also dished out some awesome advice on creating a positive, inclusive workplace and how to keep growing personally and professionally.For all of you balancing your entrepreneurial dreams with the rollercoaster of motherhood, this episode is packed with practical tips, heartfelt advice, and a fresh take on making it all work.Did you listen to an episode and love it? Let me know! Tag me with your "aha" moments and Follow me on Instagram and Facebook!

Today we are joined by Laura Casselman. Laura is the CEO of JVZoo.com and co-founder of Vidastreet LLC. Laura climbed the corporate ladder by mastering the rules of the “old boys club.” More often than not, she beat them at their own game. She's been published in Inc. Magazine Entrepreneur, and her book, Trust Your Increments, is a Wall Street Journal Best Seller. Laura's companies have also been featured on the Inc. 5000's list of America's Fastest Growing Companies four times. [Nov 13, 2023]   00:00 - Intro 00:21 - Intro Links -          Social-Engineer.com - http://www.social-engineer.com/ -          Managed Voice Phishing - https://www.social-engineer.com/services/vishing-service/ -          Managed Email Phishing - https://www.social-engineer.com/services/se-phishing-service/ -          Adversarial Simulations - https://www.social-engineer.com/services/social-engineering-penetration-test/ -          Social-Engineer channel on SLACK - https://social-engineering-hq.slack.com/ssb -          CLUTCH - http://www.pro-rock.com/ -          innocentlivesfoundation.org - http://www.innocentlivesfoundation.org/ 03:48 - Laura Casselman Intro 04:30 - From the Stage to the Boardroom 05:24 - Time to Run a Company 07:28 - Plan to Pivot 08:48 - Fire Yourself 09:41 - Room to Grow 12:19 - Respect is Natural 14:29 - Let Them Know 18:23 - Time to Move On 19:45 - Setting an Example 22:04 - Change Your Mind 27:20 - Your Companies -          JVZoo -          VidaStreet 29:04 - Your Book -          Trust Your Increments - Laura Casselman 31:11 - Mentors -          Parents 32:06 - Book Recommendations -          With Winning in Mind - Lanny Bassham -          Winning the Moment - Cody Adent 35:53 - Find Laura Casselman online -          Instagram: @thelauracasselman -          Website: lauracasselman.com 36:10 - Guest Wrap Up & Outro -          www.social-engineer.com -          www.innocentlivesfoundation.org

John's guest this week is the legendary Upper Peninsula of Michigan trial lawyer, Tom Casselman. They talk over his amazing career, full of twists and turns getting to the point where he was the go-to attorney in many great and small cases in the special world of Northern Michigan law.See omnystudio.com/listener for privacy information.

Lindsey Casselman is a veteran homeschooling parent and certified teacher in Ontario. She heads up curriculum and content design for the education company she co-founded, Schoolio Learning. She spends her free time coaching her daughter's riding lessons, organizing field trips and events for her local homeschool community, and managing the family hobby farm and apiary.… The post Nurture Resilience & Big Emotions with Lindsey Casselman of Schoolio Learning appeared first on Capturing the Charmed Life.

You have a position to fill in your business. You place ads on all the job boards. Prospective hires send in their resumes & complete the screening forms. You're excited...And then you're not.  The disappointment kicks in when many applicants don't even show up and some of the ones who do didn't follow the basic printed instructions on the application. Sound familiar? If you own a business or work in talent acquisition, I'm sure it does! Today's guest is Laura Casselman...she's a  CEO, Mom, consultant, WSJ bestselling author & speaker and she shares incredible wisdom in building a team and creating a culture that empowers, rather than takes down.She talks how she got to where she is today and the many obstacles she's had to overcome, including severe illness. She's maintained a "never say die" attitude and continues to inspire people from all walks of life.  We cover a variety of topics including hiring & talent acquisition, working through adversity and treatment of women in the workplace. A little word to all the guys listening - stop interrupting women! Check out Laura's book Trust Your Increments: https://www.amazon.com/Trust-Your-Increments-Consistent-Massive/dp/1636980058A great place to start learning more about Laura: https://lauracasselman.com/Follow & interact with Laura on Instagram & LinkedInhttps://www.instagram.com/thelauracasselman/https://www.linkedin.com/in/laura-casselmanFollow me on Instagram @ johnskomski for daily intrapreneurial motivation and learn more about Investing Inward at https://jskomski.com/Music: Hindsight (Instrumental) by Fivefold (used with written permission)

Welcome to an exciting episode of the Live Better Now podcast, today my guest is Laura Casselman, entrepreneur, CEO of JVZoo, Wall Street Journal best-selling author, and an inspiring figure in the world of business. Laura has recently released her first book, Trust Your Increments: How Small, Consistent Steps Can Lead to Massive Success. In the book, Laura takes us on a journey, from growing up in a small South Carolina town to accomplishing her childhood dream of dancing with the renowned Radio City Rockettes. She rose to become the CEO of a major tech company, earning multiple appearances on the prestigious Inc. 5000 list of America's fastest-growing companies. Trust Your Increments is a transformational guide that challenges us to reflect on our personal mission and prioritize what truly matters. Laura provides a creative blueprint for anyone striving to maximize their potential and achieve ambitious career goals. By embracing small, consistent steps in the right direction. As a host who is passionate about growth and continually improving by 1% each day, I am thrilled to have Laura on our podcast. We dive deep into her captivating story, exploring the challenges she faced and the strategies she employed to reach the pinnacle of success. Enjoy! For more information on Laura connect with her on Instagram @thelauracasselman Website: Lauracasselman.com Her book "Trust Your Increments: How Small, Consistent Steps Can Lead to Massive Success" is available on Amazon. My first book, "Live Better Now" is also available on Amazon: ⁠⁠⁠⁠⁠⁠⁠amzn.to/3csfVGw⁠⁠⁠⁠⁠⁠⁠ Zach Rance, Certified Life Coach | Certified Nutritionist Questions, Comments, or Business Inquiries Visit: ⁠⁠⁠⁠⁠⁠⁠LifeCoachZach.com⁠⁠⁠⁠⁠⁠⁠ Follow me on Instagram: ⁠@zachrancey --- Send in a voice message: https://podcasters.spotify.com/pod/show/zachrance/message

Laura CasselmanTake a walk with me down Fascination Street as I get to know Laura Casselman. Laura had a dream at the age of 3 to become a Radio City Rockette. Fast forward 20 years, and a lot of hard work.... SHE DID IT! In this episode we chat about how this was even possible, and what she decided to do after her Rockette career ended. Laura is currently the CEO of JVZoo, co-founder of VidaStreet, and co-founder of Hestla Trades. She explains what all of these entities are, and what they do. Of course, we discuss Laura's new book Trust Your Increments: How Small, Consistent Steps Can Lead to Massive Success. Along the way, we discuss what it is like for women in the workforce, and what both men & women can do to help make things a little more equal in that area. Laura shares the absolute worst job-related story I have ever heard, and we talk about how to move on from something like that. She shares some tips on how to reframe some of life's jealous moments into some of life's inspirational ones. Plus, Laura explains the difference between 'Work / Life Balance" and "Work / Life Harmony".This show is part of the Spreaker Prime Network, if you are interested in advertising on this podcast, contact us at https://www.spreaker.com/show/4068452/advertisement

Have you ever wondered about how you can achieve equality and joy in your job? In this episode, Camille welcomes Laura Casselman, the CEO of JVZoo, best-selling author of Trust Your Increments, and the co-founder of Vidastreet.Laura shares her journey pivoting from professional dancing to being a CEO of a tech company. She shares her insights on how she was able to achieve her success through small, consistent steps and the issues that she sees women face when it comes to equality and pay in the workforce and how you too can break through those barriers. If you're thinking about how you can find greater success in your work, tune into this episode to hear Laura's tips on how you too can set your own goals and work towards achieving them through consistency and determination.Resources: Interested in becoming a virtual assistant? Join the 60 Days to VA Course:www.camillewalker.co/VAAccess the 5-day email sequence to help you discover your purpose:www.callmeceopodcast.comPurchase Trust Your Increments: www.lauracasselman.com/bookConnect with Laura Casselman:Follow Laura on Facebook: www.facebook.com/thelauracasselmanFollow Laura on Instagram: www.instagram.com/thelauracasselmanFollow Laura on TikTok: www.tiktok.com/@thelauracasselmaFollow Laura on Twitter: www.twitter.com/Lauracasselman1Visit her website: www.lauracasselman.comConnect with Camille Walker:Follow Camille on Instagram: www.instagram.com/CamilleWalker.coFollow Call Me CEO on Instagram: www.instagram.com/callmeceopodcast

This week's guest on the Creating Superfans podcast is Laura Casselman. From broadway to boardroom, Laura is a former professional dancer turned CEO of JVZoo and co-founder of Vidastreet. She's also the author of the new book, Trust Your Increments: How Small, Consistent Steps Can Lead to Massive Success. Companies under Laura's direction have landed on the Inc. 5000 Fastest Growing Companies in America four times. In this episode, we talk about her journey as a female CEO in a male-dominated industry, how she prioritizes the employee experience at JVZoo, and her best tips for sales and affiliate marketing. Show Notes2:15 - How has it been since Laura's new book came out on March 7th2:55 - Laura shares her background in entertainment and how she ended up in her corporate career5:43 - How did Laura learn some key leadership skills at such an early age?8:17 - How did Laura transition from the corporate world to being a CEO?9:25 - One of the many sexist interactions that Laura experienced in her career12:05 - What are some of the standards Laura has set at JVZoo that she would like to see across the board?12:50 - How Laura's team handles “bad” customers16:44 - What is JVZoo and how do they help their customers?17:36 - Why is affiliate marketing such a powerful tool?18:55 - How does JVZoo ensure the integrity of the brand through their affiliate teams?22:10 - The need to over-communicate the vision and expectations of your brand23:11 - The massive move toward Mobile and what this means for your business24:38 - This UX experience may be hurting your mobile success27:25 - Younger generations may trust influencers more than they trust media or review sites29:13 - How can people become an affiliate marketer to earn a new income stream?30:17 - Which products on JVZoo is Laura a SUPERFAN of?31:07 - How may AI change the digital customer experience over the next few years?32:40 - Laura's message to those who are concerned about using AI

Laura Casselman is the CEO of JVZoo, co-founder of media agency Vidastreet, and author of Trust Your Increments. She has nearly two decades of experience in growing sales and revenue, improving customer service, and aggressively controlling expenses in competitive markets. Companies under her direction have landed on the Inc. 5000 Fastest Growing Companies in America four times and increased revenue from $100M to over $2B. Laura is the recipient of Stevie Awards for both Executive and Woman of the Year, a CEO World Award for Female CEO of the Year, and a Pillar World Award for Employer's Diversity Achievement of the Year.

As the saying goes: "A woman who walks on purpose doesn't have to chase people or opportunities. Her light causes people and opportunities to chase after her."If you want to kickstart your career, sprint up the money ladder, or grow your own business, this episode is for you! In this episode, we've invited an extraordinary and inspiring entrepreneur. Her name's non-other than Laura Casselman. Laura is the CEO of JVZoo and co-founder of Vidastreet. She has nearly two decades of experience in growing sales and revenue, improving customer service, and aggressively controlling expenses in competitive markets. Companies under her direction have landed on the Inc. 5000 Fastest Growing Companies in America four times and increased revenue from $100M to over $2B. Laura is the recipient of Stevie Awards for both Executive and Woman of the Year, a CEO World Award for Female CEO of the Year, and a Pillar World Award for Employer's Diversity Achievement of the Year. She has been published in major publications such as Inc. Magazine, Forbes, and Entrepreneur. In this episode, Laura will be sharing: 1) Her advice for entrepreneurs who are having a slow start to the year 2) Her secrets on how you can get paid what you're worth 3) The 15 incremental steps to take control of your life and find success without losing who you are Learn more about Laura: Website: https://lauracasselman.com/home/ LinkedIn: https://www.linkedin.com/in/laura-casselman/ Instagram: https://www.instagram.com/thelauracasselman/ --- Send in a voice message: https://podcasters.spotify.com/pod/show/theraygacyshow/message

Today Gina welcomes Laura Castleman, CEO of JV Zoo, a company that Instantly connect your business with millions of paying customers and the top performing affiliates. She discusses her new best-selling book ‘Trust Your Increments'  and the challenges of being a woman in business. She shares her experiences of systemic sexism in the boardroom and the struggle to gain recognition in male-dominated industries. Her book offers a guide for the next generation of business leaders to achieve their goals with incremental, applicable steps without losing their soul. Laura and Gina also talk about why to decide your own definition of success, working to stop comparing yourself to others you don't really know, how life-changing it is to work on wowing yourself instead of others, teaching your children how to be happy set priorities, that happy employees perform better, and why knowing when to say no is a strong launching point to reaching your goals. Find out more about Laura and JVZoo Get her new book that was just put on the shelves this month, right here Level up with Sales Gravy & Sales Gravy University More about Gina Engagement Expert – Speaker – Sales Trainer – Entrepreneur – Improv Comic Gina is a Master Sales Trainer for Jeb Blount's Sales Gravy who combines street smarts and improv comedy skills with her experience in the corporate and entrepreneurial worlds, which sets her apart from her competition.  “Sass without too much crass” is how Gina Trimarco describes herself. A high energy entrepreneur, engager, speaker, trainer, improv comedienne and podcast producer, Gina credits most of her success on her upbringing by her Italian mobster dad and German immigrant mother. Prior to joining Sales Gravy, Gina founded and operated Carolina Improv Company, an improv comedy school and theater, in addition to Pivot10 Results, a sales training company. Thanks to this podcast, Gina was able to “stalk” her business role model Jeb Blount and convince him to hire her … and sponsor this podcast!

International Women's Day is March 8th. To talk about the state of women in the workplace in 2023, I've invited Laura Casselman on the show. Laura is a former Radio City Rockette who beat the boys club to become CEO of JVZoo.com. Her book "Trust Your Increments" is now available to order. --- Send in a voice message: https://anchor.fm/alyssa-milano-sorry-not-sorry/message

Do you struggle to say no when asked to do something? In this episode, Laura Casselman will discuss the power of saying no. Laura will also cover how to let your strengths become your weaknesses, and you need to focus & work on your plan.

David Casselman is paving the way for a new era of media, and he joins us on the podcast this week for an in depth conversation about Ecoflix, the world's first not-for-profit media group committed to helping animals and the planet. The philanthropist explains how the platform aims to provide its viewers with inspiring, educational content relating to animals that, in… The post Ecoflix w/ David Casselman appeared first on Our Hen House.