Podcasts about Adaptability quotient

It was a pleasure to welcome Alec Litowitz, the Founder of Magnetar Capital and QStar Capital, to the Alpha Exchange. Central to our discussion is an exploration of the ideas in Alec's new book, The Adaptability Quotient. Here, he draws on more than thirty years of investing across multiple market regimes. We begin with Alec's three decades in financial markets, from his early years at Citadel through the founding of Magnetar. Looking back across multiple market cycles, he argues that long-term investing success is driven by more than intelligence alone. Instead, he introduces the concept of Adaptability Quotient, or AQ, emphasizing the ability to revise views, respond to changing conditions, and distinguish between environments defined by risk, uncertainty, and black swans. A central theme throughout the discussion is decision-making under uncertainty. Alec explains why markets spend much of their time in environments where outcomes are possible, but probabilities remain difficult to estimate. He outlines a framework centered on metacognition, simulation, experimentation, and continuous feedback, encouraging investors to develop "strong opinions, weakly held" while remaining willing to revise conclusions as new information emerges. The conversation then turns to practical investing examples drawn from Alec's career. He reflects on building Citadel's risk arbitrage business by developing proprietary research processes around regulatory uncertainty, and later discusses Magnetar's emphasis on sourcing, structuring, and risk management in areas undergoing structural change. Examples include investments tied to energy infrastructure and AI-related computing capacity, illustrating how the firm approached evolving industries through the lens of uncertainty rather than prediction. I hope you enjoy this episode of the Alpha Exchange, my conversation with Alec Litowitz.

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

What separates the investors and founders who thrive in moments of radical change from those who don't? According to Alec Litowitz, it isn't intelligence or emotional maturity - it's adaptability.Alec is the founder of Magnetar Capital, one of the most respected multi-strategy hedge funds in the world, and the founder and managing partner of QStar Capital, his single family office and investment platform. Over a 30-year career that began at J.P. Morgan, continued as a founding partner and global head of equities at Citadel, and culminated in building Magnetar from scratch, Alec developed a framework he calls the Adaptability Quotient - AQ - for making decisions under genuine uncertainty. His book, The Adaptability Quotient, publishes September 15th.Today, through QStar, Alec invests with no fund mandate and no LP constraints - thematically across both public and private markets, in everything from CoreWeave and SpaceX to top-tier VC and PE managers. That unconstrained vantage point, combined with three decades of pattern recognition across market regimes, gives him a distinctive lens on where venture capital sits inside the current moment of change.Nick and Beezer dig into the core distinction Alec draws between risk and uncertainty - a difference he argues most investors collapse at their peril - and how the AQ framework maps directly onto how founders build, how VCs back them, and how the venture ecosystem itself needs to adapt. They also get into what he calls the second cognitive revolution: why AI isn't just a new tool but a system-level regime change, what that means for the capital stack and liquidity timelines in venture, and why the answer for smaller players isn't resistance - it's remapping.Quotes"What entrepreneurs get paid for is not risk. They get paid for uncertainty, for resolving the uncertainty. People may stay at some stranger's house or they may not, but I don't know the probability. If it's high, I have a business. If it's zero, I don't have a business. Let's go resolve that probability. And when someone does a startup and tests it, raises money, probes around it, and gets feedback loops - the answer is yes. That's what they get paid for, for resolving that uncertainty."Time Stamps00:00 What Entrepreneurs Actually Get Paid For00:31 Introducing Alec Litowitz: Citadel, Magnetar, and QStar02:49 Three Career Chapters and the Through Line: A Systematic Approach to Uncertainty06:09 The Book: Why Alec Wrote The Adaptability Quotient07:29 AQ Defined: Why IQ and EQ Aren't Enough When the Frame Itself Changes9:40 Why QStar: No Constraints, No Mandates, Just Mapping the Moment12:22 QStar's Investment Framework: Thematic, Top-Down, Technocentric and Anthrocentric14:51 Why Venture Still Matters: The Venture 20, the Mag Seven, and Where Disruption Lives17:03 Risk vs. Uncertainty vs. Black Swan: The Framework Most Investors Get Wrong22:30 Applying AQ in Venture: MVPs as Probes, Pivots as Feedback Loops22:51 A Case Study in Failing Without Feedback Loops24:33 The Second Cognitive Revolution: Why AI Is a Regime Change, Not a Tool29:20 Is SaaS Uninvestable? What Becomes Abundant and What Becomes Scarce32:53 Mapping the Venture Ecosystem: Capital Intensity, New Entrants, and IRR Pressure37:08 The Liquidity Problem Reframed: DPI, TDPI, and Timeline Mismatch40:12 Secondary Markets as a Structural Response43:48 Final Advice: Upgrade Your Operating SystemLinksConnect with the guest and hosts on LinkedIn!Alec LitowitzBeezer ClarksonNick ChirlsLearn more about:The Adaptability Quotient (pre-order on Amazon)QStar CapitalMagnetar Capital⁠⁠Early Adapters Newsletter⁠⁠Asylum Ventures⁠⁠OpenLP

This is the second episode of [comebacks], and the guest is Liz Tran. I'm a huge fan of her work, so I loved getting to speak with her again in this new format, where we walk through a specific comeback in someone's life and focus on the messy middle of it. In this episode, Liz talks about divorce, reinvention, dating, and what it actually takes to rebuild your life after the version you planned for falls apart. We talk about how loneliness can change you when you stop trying to outrun it, how avoidance can look productive, as well as AQ (adaptability quotient), timelines, and learning to trust that your life can expand in ways you couldn't have planned for.   SHOW NOTES: Explore more from Katie Dalebout: Katie Dalebout Substack + Let It Out Lists Katie's Instagram: @letitouttt + @katiedalebout My Zine Shop and My Creative Clinic Find Liz on the Web | Instagram | Podcast Order Liz's book, The Karma of Success If you liked this episode, try this one from the archive: Karma Success with Liz Tran, Founder of Reset NYC

IQ may land you the job.EQ helps you connect with people.But it's AQ — your ability to adapt, evolve, and stay agile — that truly defines long-term success.In a world where skills expire fast and digital transformation keeps rewriting the rules, adaptability isn't just an advantage — it's a necessity.The future belongs to those who can learn quickly, unlearn what no longer serves them, and grow through change.

How well can you adapt? Deal with the unknown, uncertain, uncomfortable, unfamiliar and unpredictable (all the 'uns')? According to Dr. Carlos Davidovich (MD), in terms of real-world function, success and survival, our ability to adapt (AQ), might even be more important than IQ and EQ (it's more renowned cousins - lol). This chat with the Doc (a new TYP guest) was super enjoyable and we covered a myriad of relevant and fascinating topics. **BIO: Carlos Davidovich, MD, is an executive coach, TED speaker, and the author of Five Brain Leadership: How Neuroscience Can Help You Master Your Instincts and Build Better Teams. With over 20 years of coaching experience across Europe and North America, Carlos works with executives from Google, Netflix, and global biotech firms - guiding them to master decision-making, emotional regulation, and adaptability by understanding the real drivers behind performance: the brain.carlosdavidovich.comSee omnystudio.com/listener for privacy information.

Send us a textIn this energizing interview, Mallory Mejias is joined by leadership legend John Spence to unpack the three essential quotients of leadership—IQ, EQ, and AQ (Adaptability Quotient)—and why AQ might be the most critical of all in today's AI-driven world. With decades of global experience, John shares how leaders can foster resilience, embrace change, and build cultures that thrive in uncertainty. From AI pilot projects to emotional pulse checks, this episode is packed with practical wisdom (and a few gut-check moments) for association leaders ready to adapt and grow.

In dieser Folge des EducationNewscast ist Diana Gajic, executive Recruiterin bei SAP zu Gast. Sie teilt wertvolle Tipps für Bewerber und einstellende Manager, diskutiert wichtige Skills der Zukunft und beleuchtet den Einfluss von künstlicher Intelligenz auf Recruitingprozesse. Dabei geht es nicht nur um Tips zur Gestaltung des CVs oder für Interviews. Diana teilt auch warum das eigene persönliche Plus und der Cultural Add wichtig ist, was der Adaptability Quotient ist und welche unerwarteten Fragen Sinn machen können in Interviews. Mehr wie immer im EducationNewscast Podcast.

Do you know what the top 3 health issues causing death in Americans today is? You can probably guess them - but we can boil it down to one simple culprit. What is it and what can we do, practically, about it?  It all boils down to our AQ - Adapbility Quotient. AQ is a measure of an our ability to adapt to new situations, challenges, and changes in our environment and it is increasingly recognized as a critical skill for success in today's fast-paced, ever-changing world. In our world-view it is an essential measurement for your health. So how do we build our AQ and help build our body's ability to thrive in this often toxic environment we live in? Tune in to today's episode to hear all about it from the BrainStim gang. As always, if you want more information or to schedule a phone call with Dr. Richard Aplin, visit: www.invisionchiropractic.com

We have all heard about IQ and maybe even EQ, Emotional Intelligence but many have not heard about AQ. In this episode we talk about AQ why it is important and how it impacts the major areas of life. Enjoy the episode. --- Support this podcast: https://podcasters.spotify.com/pod/show/paradigmsandperspectives/support

From adapting to the AI age to redefining success on your terms, Samantha McLean advocates embracing change as it may bring great opportunity.

Adaptability Quotient ความฉลาดในการแก้ไข รับมือกับปัญหา และการปรับตัว ซึ่งถือเป็นทักษะที่สำคัญที่จะช่วยเป็นหลักประกันว่าเราจะอยู่รอดได้หรือไม่ ท่ามกลางกระแสที่เปลี่ยนแปลงในยุคที่ AI มาแรง Key takeaways: 1) การเปิดใจยอมรับการเปลี่ยนแปลงด้วย Outward Mindset 2) กลุ่มที่มี AQ สูงเป็นกลุ่มคนที่หลายๆ องค์กรต้องการ

In this episode of Coaching In Session with host Michael Rearden, we dive deep into the realm of business coaching with the esteemed Jeanne Omlor, a Certified Business Strategist and Online Business Coach. Jeanne shares her no-fluff guidance and training to empower coaches, consultants, experts, and service providers to achieve ultimate success.As a natural motivator and encourager, Jeanne operates as a catalyst, infusing her Intelligent Leadership accreditation into all her trainings. Specializing in coaching Visionaries, she and her team provide cutting-edge training in Social Media Marketing, Leadership, Communication, Mindset, Productivity, Personal Negotiation, and Adaptability Quotient. The goal is clear – to help you maximize profits, grow a vastly profitable business, and stay true to your vision and mission.Discover how to sharpen decision-making skills, optimize productivity, and step into your leadership as the CEO of your own business, whether you're a solopreneur or have a team. Jeanne's passion lies in helping professionals find their "Genius Zone" for sustained growth, tailoring strategies to individual business needs.All coaching sessions are online, making them accessible globally for those serious about maximizing their business potential. If you're ready to take action and move from neutral to fifth gear, gaining clarity on your pathway to profits, this episode is a must-listen.Jeanne OmlorWebsite: https://jeanneomlor.com/LinkedIn: https://www.linkedin.com/in/jeanneomlor/Instagram: https://www.instagram.com/jeanneomlor/?hl=en___________________________________Michael ReardenWebsite: www.Revenconcepts.comReview, Follow, & Subscribe to the Podcast on your Favorite App: https://coachinginsession.buzzsprout.com/Support the Show: https://www.buzzsprout.com/1882580/supportInterested in working with me? www.Revenconcepts.com/memberships/Email Me: Coachinginsession@gmail.com----------------------------------#BusinessCoaching, #OnlineBusiness, #LeadershipTraining, #SocialMediaMarketing, #ProductivityTips, #EntrepreneurialSuccess, #VisionaryLeadership, #ProfitMaximization, #BusinessGrowthStrategies, #CoachingInSession, #GeniusZone, #IntelligentLeadership, #ProfessionalDevelopment, #GlobalBusiness, #SuccessMindset, #AdaptabilityQuotient, #EntrepreneurialJourney, #CEOmindset, #StrategicBusiness, #VisionAndMissionSupport the show

In the latest episode of Hiring On All Cylinders, Talentful's CEO and co-founder, Chris Abbass, dives deep with Carla McIntosh, VP of Global Talent Acquisition and Contingent Workforce at Reddit, on the nuances of candidate assessment. Beyond the conventional parameters of IQ and EQ, they explore the significance of Adaptability Quotient “AQ”. Carla, drawing from her unique experiences, including her time in the Air Force, discusses the importance of adaptability in navigating challenges and ensuring success. As talent strategies evolve, so should our approach to recognizing and valuing adaptability. This episode is sponsored by ⁠Talentful ⁠- Subscription talent solutions for the world's most innovative

Do you know your adaptability quotient? No??? In this economy?!? In today's episode, our guest, Liz Tran, shares why she believes that (in this economy) your Adaptability Quotient (AQ) is more valuable than your IQ. For the next few weeks, our Tuesday episodes will feature guests and conversations on the topic of, “Doing Things Differently”. We'll be in conversation with guests discussing how they've overcome and adapted to some of their toughest challenges, and found alternative paths for creative a fulfilling life. Liz Tran is the founder of Reset, a podcast and executive coaching company to CEOs and founders. Before Reset, Liz spent over a decade working in the tech industry, most recently as the only female executive at a leading venture capital firm. Liz Tran is releasing her book, THE KARMA OF SUCCESS, on July 25th. Covered in this episode: Liz opens up about her IVF journey, the rise and fall of her business, and the invaluable lessons that led her to relaunch her business during the pandemic The idea behind Liz's work prayer, and how it helps her connect with her intuition and move past her ego as she forges her own path We explore the limitations of future-visioning from our current state of mind and share stories about the perfection in the collapse of our best laid plans How to use your natal chart to guide you when making big career changes We muse on the saying, “Millionaires don't believe in astrology, billionaires do!” Liz introduces her theory of “the reverse incentive learning curve” and how to adopt this mindset when tackling new challenges What did you think of the episode? Let us know by ⁠⁠⁠⁠⁠sending us a note here⁠⁠⁠⁠⁠! We'd love to hear from you. Add yourself to the early-access waitlist to get 10% off the ⁠⁠⁠⁠CREATIVE MARKETING EXPANSION PACK⁠⁠⁠⁠ and access before the rest of the list on May 17th

If you work for a company that gets acquired by a bigger company, work the way you knew it is probably going to change. Experts state that Adaptability Quotient (the capacity to adapt to new ways of thinking and letting go of old habits) is crucial if you want to keep your job during a transition phase.For today's episode, we talk with Jordan Stratton, Editor and Social Media Manager for The Dad, the #1 Most Engaged Family Media Brand on the internet. Jordan also writes, shoots, and produces The Dad's celebrity interview series, “Gettin' Grilled,” which has led to conversations with the likes of Ryan Reynolds, Matthew McConaughey, and former WH Press Sec, Jen Psaki.  And even more importantly, he's VERY FUNNY. Jordan shares his experience navigating the acquisition process when the company he worked for was acquired.  Spoiler alert! It wasn't easy. He also reveals what Ryan Reynolds is like in real life.  You won't want to miss this one!HIGHLIGHTS01:29 Why your Adaptability Quotient is crucial to survive an acquisition or leadership change.4:48 Meet our guest, Jordan Stratton.13:12 The acquisition happens and oh boy!20:33 Is there a silver lining to the acquisition process?31:15 Key learnings35:40 Corporate confessionsRESOURCESSteve Cadigan's amazing book, “WorkQuake: Embracing the Aftershocks of COVID-19 to Create a Better Model of Working."

Welcome to the Keto Mom page. My name is Stephanie and I have not been here for over a week but it wasn't by choice, so I had to be adaptable. The goal here is to help support, guide, and teach you. To share with you what has happened in our lives over the last seven years. Our family mission statement is to help people live healthy, faith-filled lives. I often tell people to stay in their lanes. Don't compare yourself to other people when you are focusing better. Some people might try to pull you down and be negative about it. Some will try to make you stop because inside it makes them feel like they're not doing enough. I want you to know that "Hurt people, hurt people". And so we're going to talk about your emotional quotient and your adaptability quotient. You have your EQ, which is how well you handle your emotions. And your AQ, which measures how adaptable you are in a given situation. Let's learn and read more about EQ and AQ. What goal are you striving for? Feel free to share your thoughts in the comments. Visit our Website: https://beacons.ai/ketomom Grab your Mom Fuel Trial Packs: 3 Pack Trials: www.MomFuelTrials.com 5/10 Pack Trials: https://www.ketomomsecrets.com/shop CONNECT WITH ME: * Facebook: http://facebook.com/KetoMom * Facebook: http://facebook.com/stephy.mielke * Instagram: http://instagram.com/ketomomsecrets * Pinterest: https://www.pinterest.com/KetoMomSecrets * Blog: http://KetoMomSecrets.com * YouTube: http://www.youtube.com/c/ketomom * Email: stephanie@ketomom.com RESOURCES: Keto Mom Blog: http://www.KetoMomSecrets.com Mom Fuel Trials: www.MomFuelTrials.com Drink Ketones Challenge: https://www.ketomomsecrets.com/10-day-challenge Purchase our Mom + Dad Fuel: http://www.KetoMom.com 60 Hour KetoReboot: https://www.ketomomsecrets.com/keto-reboot More info on the Keto Lifestyle: http://www.facebook.com/KetoMom * Rumble: https://rumble.com/c/c-325815 -- KetoMOM was founded with a very simple philosophy. Make. People. Better. Our family hopes to provide as much value as possible by taking your questions about keto lifestyle, homeschooling, social media, entrepreneurship, and family business and giving you our answers based on a lifetime of building successful relationships, teams, and experience. --- Send in a voice message: https://anchor.fm/ketomom/message

Adaptability isn't just about surviving more punches, it is a key skill in being able to manage change effectively and thrive on both a personal and business level. CEO and founder of 3 companies Charles MacLaughlan discusses the Adaptability Quotient, and why it is both measurable and something we can see increase. One key concept within adaptability is being able to unlearn assumptions that have led to our default actions. Charles explains ways to measure both the internal and external environment in relation to adaptability, including factors such as mental health, and psychological safety within the workplace. He challenges the concept of resilience as sometimes being an excuse for business leaders expecting people to do more with less, and relates the "Big Resignation" to lost human connectivity in the workplace. This podcast will challenge current practices and inspire you to develop adaptability, both for yourself and for your teams.   Watch the full episode on YouTube: https://www.youtube.com/watch?v=hPy-AEEIk2g   Connect with Charles: LinkedIn: https://www.linkedin.com/in/charlesmclachlan/ Website: https://ceogrowth.biz/ceo-growth-academy/ Email: charles.mclachlan@futureperfect.company Twitter: https://twitter.com/2ndhalfcareer     Helping SME's build resilient, high performing teams and businesses, quickly, so they can innovate, deliver, and thrive.   The SME's I work with typically struggle/suffer/ with one or more of these challenges: - no clear strategy - dysfunctional team dynamics - not knowing their vision or mission - feeling stuck and procrastinating - business not growing - leadership challenges   If you want support in helping your organisation thrive, do get in contact with me: https://www.julianrobertsconsulting.com

What is AQ and can you develop it? What makes someone more adaptable and less adaptable? AQ is a bit of a hot button topic, and today the team bring out their ideas on not only what it is, but how you can be better at it. The ML Recommendation: Adam Grant - Think Again https://adamgrant.net/book/think-again/ All Magical Learning podcasts are recorded on the lands of the Kulin, Ngunnawal and Wiradjuri nations, and we pay our respect to their elders past and present. As always, if you are having trouble, you can always send us a message. Listen to/watch this podcast here: https://open.spotify.com/show/128QgGOlt293SnJkqN1w6e?si=805eef704962447b To find out more about our free content, sign-up for future webinars as well as our other services, go to https://magicallearning.com/ and sign up! You can also find us on our socials: Instagram: https://www.instagram.com/magical_learning/ Facebook: https://www.facebook.com/magicallearningteam/ Linkedin: https://www.linkedin.com/company/magicallearning/ Youtube: https://www.youtube.com/channel/UCb70j5K0EE1DLlCLCvqdsVQ? On today's Podcast: Jez F.M, Danette Fenton-Menzies, Grahame Gerstenberg Have a Magical day! --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app

Being adaptable is essential to the success of a business as well as a person's ability to cope with change.  In this episode, Rae explores exactly what your adaptability quotient is and how it can be useful for your career journey - in particular, how it can help you to deal with a fast-paced and ever-changing workplace.   

Dr. Paul Brewerton, The Strengths Guy, discusses the emerging idea of Adaptability Quotient with Scott Christie, Head of Training and Integration from Strengthscope. They will talk about what AQ is and how it can be developed. Plus, how you can develop AQ using strengths. There will also be some bonus material.  Listen to Maximise your Adaptability Quotient using strengths with Scott Christie.

In this HCI Podcast episode, Dr. Jonathan H. Westover talks with DanRam about Adaptability Quotient (AQ), the new superpower. See the video here: https://youtu.be/mQ6pc4lpjns. DanRam (https://www.linkedin.com/in/iamdanram/) travels the globe as an Event MC & Speaker at over 100 events a year. Hosting changemakers like President Barack Obama, billionaire founders Sir Richard Branson and Reid Hoffman, F1 champion Nico Rosberg, Grammy-winning artists and celebrities, he works on 4 continents from college campuses to parliaments to in-house corporate innovation days for Fortune 500 companies to the biggest tech conferences in the world. His passion is to inspire people with his motto 'Start Now Start Simple' in building a future we all want to live in. Please leave a review wherever you listen to your podcasts! Get 3 months of GUSTO free when you run your first payroll, at Gusto.com/hci Check out the HCI Academy: Courses, Micro-Credentials, and Certificates to Upskill and Reskill for the Future of Work! Check out the LinkedIn Alchemizing Human Capital Newsletter. Check out Dr. Westover's book, The Future Leader. Check out Dr. Westover's book, 'Bluer than Indigo' Leadership. Check out Dr. Westover's book, The Alchemy of Truly Remarkable Leadership. Check out the latest issue of the Human Capital Leadership magazine. Ranked #5 Workplace Podcast Ranked #6 Performance Management Podcast Ranked #7 HR Podcast Ranked #12 Talent Management Podcast Ranked in the Top 20 Personal Development and Self-Improvement Podcasts  Ranked in the Top 30 Leadership Podcasts Each HCI Podcast episode (Program, ID No. 592296) has been approved for 0.50 HR (General) recertification credit hours toward aPHR™, aPHRi™, PHR®, PHRca®, SPHR®, GPHR®, PHRi™ and SPHRi™ recertification through HR Certification Institute® (HRCI®). Learn more about your ad choices. Visit megaphone.fm/adchoices

This episode is one that will be of great value for years to come. Host Josh Nelson gives you   a few different strategies to help you through when the markets are turbulent. He gives you a real and honest understanding of how the flow of the market has moved from Bear to Bull over the years.  In this is good news for you. He says that there are things that we actually have control over, as opposed to most of the stuff we see in the news and on social media. He encourages you to be willing to know about what he calls your Adaptability Quotient. He explains in detail what they really means as it pertains to financial planning. You will get some great info from this episode and we thank you for listening, liking, subscribing, downloading and sharing. Contact Josh Nelson with any questions, comments or suggestions at:https://www.keystonefinancial.com/podcast

Are you interested in learning strategies that will help you and your workforce prepare for a rapidly changing future of work? In this episode of The Staffing Show, Ira Wolfe, president of Success Performance Solutions, talks about starting his professional career as a dentist and eventually starting his own HR consulting firm. Wolfe shares tips and advice for preparing to work and lead in the “world of never normal” where an adaptable mindset will be key to adjusting to this world of ever-present change.

This episode is also available as a blog post: https://nudgecare.wordpress.com/2020/07/27/the-adaptability-quotient/

Companies want to hire individuals with a high adaptability quotient because they need employees who can not only survive, but thrive, in challenging and ever-changing situations.As a result, the adaptability quotient has bypassed IQ and EQ (emotional intelligence) as the primary means of evaluating job applicants.Candidates who are curious, willing to learn, and unlearn, in other words, challenge what they know and embrace an alternative mindset, are quickly becoming the most in-demand with hiring managers.Learn more about how to showcase yourself as a job candidate with a high level of adaptability quotient in this week's episode.Have you grabbed your copy of the 4 Facts High Achievers Need to Know to Take Control of Their Careers and Obtain a Job They Love? Click here to get your copy: https://masterthejobsearch.com/subscribe/Visit the episode website for the full show notes: https://masterthejobsearch.com/34

Welcome to another episode of the DNA Of Purpose Podcast, and the last episode for 2021. A year that has been defined by a way of thinking that we at Future Crunch call the Adaptability Quotient. With that in mind, I want to share a few words that sum a year of Adaptability for Future Crunch.This has been a year where life has happened, in all its ups and downs, and through it all, every single one of us, did what we do best. We adapted, gained survival skills, expanded our horizons, and harnessed the strength to overcome one of the greatest challenges of our time. We grew in our pursuit to live a purposeful life lined with meaning.We acknowledged that with the full force of the outside world, just how lucky we are to be here, and to have the chance to experience life, in all of its nuances, all of its unfairness, all of its beauty.We accepted that none of us know what's coming next, and yet we had the ability to face it. To transform it into something that's of benefit for people, and our planet. That it was an opportunity to grow ourselves, our business... and perhaps even learn to love both the science and magic of change.As we move forward we have so many reasons to be excited - it doesn't matter where you start - embracing the amateur mindset, realising our opinion has room to evolve, or just remembering - that we are remarkable, and we are built for this. This is in our DNA. We are never too old, and we are never too young, to set out on an adventure, to try one new thing.Overall in 2022, We have it in us, to be stronger, smarter and kinder. So Let's do it better this time around. Let's keep stepping into our purpose acknowledging that if we are ever lost in this complex and crazy, just remember this one thing: collaboration always trumps genius!I know that for me this podcast would not be possible without the power of collaboration, and today's guest is another partner in purpose, I am proud to introduce.His name is Thomas Kolster and he is a marketing activist on a mission to make business put people and the planet first. Thomas is the founder and director of The Goodvertising Agency, and one of the pioneers in shaping brands for good. He's an internationally recognised keynote speaker who's appeared in more than 70 countries at events like TEDx, SXSW, D&AD & Sustainable Brands; and is a columnist for the Guardian, Adweek, The Drum and several other publications, as well as regularly judging at international award shows such as Cannes Lions and D&AD.Today we will be talking about Thomas's latest book which is called The Hero Trap. In the book, Thomas takes a hatchet to his earlier beliefs and warns brands about purpose: The essence of the book's message is that purpose is not a promotional stunt and the brand is never the hero. Purpose is all about the people, and the people are the DNA Of Purpose. This is why we need to put the people first, and make them the hero. From there a brand can build purpose. His belief is that a large majority of brands get stuck in what he calls the hero trap.Thomas believes that brands need to focus on the promise of transformation. ‘Who can you help me become?' is the one essential question you need to be asking and acting on to chart a new course for your brand, changing behaviours at scale and unlocking sustainable growth that benefits all. Thomas heralds the beginning of a new post-purpose era, where brands will be seen as villains if they don't put people's dreams, aspirations and creativity first.Before signing off, we will be on air on Wednesday the 13th of January, by which time I will be a married lady and coming back to the podcast Mrs Rebecca Maklad. New year, a new era and a year that I hope is the best one yet. I wish all of you a merry Christmas and a wonderful holiday season full of love, light and happiness. Love from me and the team at Future Crunch.Welcome to the last episode of the DNA Of Purpose Podcast for 2021!

What's your adaptability quotient? Richard chats with Sara Caldwell and Angela Dugan about the ideas behind the adaptability quotient - the ability to respond to change. The pandemic certainly forced a lot of change on a lot of folks - and different people coped with the changes in different ways. Sara talks about thinking about your ability to adapt and strengthening that ability, starting with asking for help where needed. Angela digs into the changes that have happened for her and Sara just recently with the acquisition of their company - more opportunities to adapt! Change is inevitable. It's just a question of what we keep from the past and what we let go of: How are you adapting?Links:Adaptability QuotientMiro3 Cloud SolutionsRecorded October 25, 2021

How you handle change, uncertainty, and ambiguity has a big effect on your personal life and your business. So, in this episode, I'm breaking down the concept of the Adaptability Quotient (AQ) and how it can help us in all areas of life. Knowing how to determine your AQ—or someone else's—and being able to develop and grow your AQ is extremely important in today's world, so make sure to tune in. You can find show notes and more information by clicking here: https://bit.ly/3DvWR1O

This episode is also available as a blog post: https://nudgecare.wordpress.com/2020/08/14/part-2-the-adaptability-quotient/

Change is inevitable, and never has that fact been more relevant than today. Teams and individuals no longer have a choice about whether to adapt and change, because the alternative is getting left behind. That means the number one skill entrepreneurs need if they want to support their teams and continue growing their business is[...] The post How To Increase Your Adaptability Quotient, with Ross Thornley appeared first on Your Team Success.

Are you struggling to keep up with the ever changing world? Are you looking for skills to keep you adaptable? In today's episode, Danette gives you some great skills to remain adaptable and ready for the future, for both your work, and life! To find out more about our free content, sign-up for future webinars as well as our other services, go to https://magicallearning.com/ and sign up! You can also find us on our socials: Instagram: https://www.instagram.com/magical_learning/ Facebook: https://www.facebook.com/magicallearningteam/ Linkedin: https://www.linkedin.com/company/magicallearning/ Youtube: https://www.youtube.com/channel/UCb70j5K0EE1DLlCLCvqdsVQ? We have also launched Magical Learning Academy, which has free and paid courses you take to improve yourself and your resume, from the comfort of your own home. Have a Magical day!

How well can you adapt? Mike Raven introduces the Adaptability Quotient, and its relevance today and for the future of work. If we explore our relationship with uncertainity we can have a greater impact on how we perform.  Key insights include: build new neural pathways, consider you environment and what you consume, and do something different every day. Connect with Mike on LinkedIn, and with your host Fred Copestake at linktr.ee/fredcopestake.  Podcast sponsored by Remaster Media.

Today's discussion is a LinkedIn LIVE recording of the Data Binge Podcast featuring Dr. Angus Hervey, Political Economist and co-founder of Future Crunch. Future Crunch, based out of Australia, is a think-tank focused on fostering intelligent and optimistic thinking, inspiring enthusiasm and excitement for technology, and empowering people to contribute to an inclusive future.I came across Gus in a Global MBA learning event where he led a presentation focused on the adaptability quotient, or one's ability to overcome challenges by quickly determining what's relevant in the current era of knowledge. The interest of Gus's work doesn't stop there, Future Crunch is really trying to get people excited about technology again, as it exists within every layer of our lives, and as it tends to get mostly negative attention - there is another story to tell. Future Crunch disperses a phenomenal newsletter based on optimistic events happening in and around our planet, in an attempt to change the stories of the 21st century, by changing the stories we tell ourselves. In this discussion, Gus brings together his interests across economics, politics, and science, to weave together a new perspective on human kinds future, how to prepare for it, how to understand it, and how we can all look to empathize, entertain, and contribute to a novel and wonderful, narrative for our species. Key Takeaways [10:11] The mission of Future Crunch, optimism, story-telling, and technology[09:53] Why “Giving a Damn” is different than talking about impactful causes – the Fondo Guadalupe Musalem, and other groups and charities of importance. [15:56] The history of story-telling, and the criticality of stories and their importance to the human existence across the 21st century [18:50] Modern journalism and how it has evolved [23:36] 5G and the opportunities represented by a new future of data movement [28:46] On understanding the future of technology: Language, Fire, and Medicine [37:53] The applicability of the Language, Fire and Medicine Framework and how it can help leaders and organizations navigate in both business and innovation [45:37] Why change moves very slowly, until it moves very quickly: the Adaptability quotient [49:15] On efficiency and adaptability in adjusting to change, examples of how the US Navy is building talent pools to handle more fluid work environments. [54:04] What people and organizations can do to embrace unexpected and high-velocity change [55:03] How to contact Angus and Future Crunch [56:10] Given unlimited resources, what global challenges would Angus attempt to solve Quotes [08:27] “If you're working at IT, if you're working in digital, you can always keep on improving. There is always another line of code that you can write; there is always another optimization that you can put in there. But I think when it comes to designing built environments or when it comes to developing new energy systems when it comes to just figuring out a way that people work together, sometimes it is possible to say, “okay, we nailed that. That's fixed, and we can move on.” - Angus Hervey [15:21] “So really, it is a community thing. I'd love to take credit for it, but the reason that we can support these charities is that we have around 2,000 subscribers that think that the content that we produce is worth paying for, and then we can take some of that money and put that money where our mouth is and give a damn than just talking the talk.” – Angus Hervey [34:06] “Energy touches everything. You look in the room around you wherever you are right now, every single object in this room, if you can have the cost of energy required to produce that object, you're suddenly talking about a whole new type of economy.” – Angus Hervey Resources: Future Crunch Website: https://futurecrun.ch/ Future Crunch Twitter: https://twitter.com/future_crunch Future Crunch Facebook: https://www.facebook.com/futurecrunch/ Additional Featured Podcasts: Open the Pod Bay Doors: https://podcasts.apple.com/us/podcast/e106-angus-hervey-future-crunch/id1246074250?i=1000505737408 Dr Angus Hervey - Future Crunch: Purpose and The Adaptability Quotient: https://www.rebeccatapp.com/decodingpurposepodcasts1/2019/12/10/dr-angus-hervey-future-crunch-purpose-and-the-adaptability-quotient Chemex Coffee Maker (the ultimate example of perfect design): https://www.chemexcoffeemaker.com/coffeemakers.html *The views and opinions expressed in this discussion are those of the guests and do not necessarily reflect the official position of their employer, Microsoft"  ____ Thank you for listening! --------------------------------   Join the **New Monthly Newsletter** - Data Binge REFRESH: https://www.derekwesleyrussell.com/newsletter   Interested in starting your own podcast? Some candid advice here: https://www.linkedin.com/pulse/how-start-podcast-3-step-gono-go-beginners-guide-derek-russell  Learn more about the Data Binge Podcast at www.thedatabinge.com   Connect with Derek: LinkedIn: https://www.linkedin.com/in/derekwesleyrussell/Youtube: https://www.youtube.com/channel/UCN1c5mzapLZ55ciPgngqRMg/featured Instagram: https://www.instagram.com/drussnetwork/ Twitter: https://twitter.com/drussnetwork Medium: https://medium.com/@derekwesleyrussell Email: derek@thedatabinge.com

Tijdens het TV programma De Nationale IQ-test haalde een BN-er ooit een IQ van 58 punten. Ze bleef daarmee ver achter bij het IQ van een Orang Oetang. De BN-er was woest en zei dat intelligentie veel meer is dan het resultaat van een test. Misschien had zij een hoge EQ score; het Emotioneel Quotient? Misschien was haar haar empathisch vermogen wel de sleutel tot succes? Sinds kort hebben we nog een nieuwe quotiënt: de adaptability quotiënt; het AQ. Hoe meet je de veranderbereidheid, het aanpassingsvermogen van iemand? Wat kan je ermee – en is het te ontwikkelen? Glenn van der Burg vraag het aan Frédérique Bruggeman, Managing Director van Robert Half Nederland.

In this episode of Quit Bleeping Around®, awesome superachiever, author, and self-improvement guru Christina Eanes interviews Ira Wolfe. Ira is president of Poised for the Future and founder of Success Performance Solutions. He is also a TEDx speaker and host of the podcast Geeks Geezers Googlization and the Crazy SHIFT Show. In this episode, Ira...Read More The post 294: The Adaptability Quotient with Ira Wolfe appeared first on Christina Eanes - Quit Bleeping Around®.

We have heard about IQ, the Intelligence Quotient, a measure of our intellectual capability – our book smarts. More recently, we came to understand the critical complementary role of EQ – Emotional Quotient, or people skills. Now there is a new Q on the block – AQ, Adaptability Quotient, our ability to adapt to unanticipated changes in the landscape of our lives. Boy, do we all need a hefty helping of AQ right now. There is a lively tradition of debate as to how much of our IQ, EQ, and AQ are innate, and how much we can grow along any of these tracks. Follow this link to view the sermon and watch the live streaming version on our website https://www.templeemanuel.com/rabbi/rabbi-michelle-robinson/aq/

Dr. Marisa Porges, known for her work on leadership, education, and national security talks about her book, “What Girls Need: How to Raise Bold, Courageous, and Resilient Women.” She provides lessons learned from her time in the Navy, serving in national security at the White House, and now as she heads The Baldwin School, a 130 year old all-girls school outside of Philadelphia renowned for academic excellence and for preparing girls to be leaders and changemakers. In this episode, Dr. Porges references the importance of competition and why collaborative problem-solving skills are critical for the future workforce. She speaks to academic research on empathy and how key leaders in national security reference its importance. Lastly, Marisa makes great points on why cognitive flexibility remains pertinent to our adaptability quotient and how we handle uncertainty. Enjoy the great tips on how to better parent and raise courageous women. Dr. Porges aptly ends with great advice to remember that little things make a big difference. For more leadership interviews go to www.https://colonelcandid.com/

Dr. Heidi Hanna is the Chief Energy Officer of Synergy Brain Fitness, a company providing brain-based health and performance programs to individuals and organizations, a Founding Partner of the Academy for Brain Health and Performance and a Fellow and Advisory Board Member for the American Institute of Stress. She is a NY Times bestselling author of several books, including The Sharp Solution, Stressaholic, and Recharge. Her next book, The Adaptability Quotient will be published in 2022. Heidi has been featured at many global conferences including the Fortune Magazine Most Powerful Women in Business Summit, ESPN Leadership Summit and the Million Dollar Round Table. Her clients have included Google, Starbucks, Microsoft, Morgan Stanley, and WD40 as well as the PGA Tour and the National Football League. Heidi is also a Certified Humor Professional with the Association for Applied and Therapeutic Humor although she won’t admit she’s funny. 7:18 Defining stress, resilience, and "positive adaptability." 11:10 How can we increase our capacity to handle stress? 15:29 The unique challenges that COVID-19 brings to our ability to handle stress—and insightful solutions for these challenges.  17:56 Being present can increase our capacity. Some tips on being in the moment, especially when others around us aren't doing so. 24:22 The cumulative effects of stress on your brain and body. 28:42 The epigenetics of stress; how it can be passed down generationally.   31:52 How "finding the funny" (cultivating a helpful sense of humor) can increase your resilience. 32:56 Small, actionable steps you can take to change your relationship with stress. 36:07 Cultivating a supportive mindset to bring more self-care into your life. Links mentioned in this episode: http://www.heidihanna.com/ (Website) https://www.linkedin.com/in/heidihanna (LinkedIn) Two books Dr. Hanna recommends for further reading: https://www.amazon.com/Body-Keeps-Score-Healing-Trauma/dp/0143127748 (The Body Keeps the Score) by Bessel van der Kolk M.D. and https://www.amazon.com/Why-Zebras-Dont-Ulcers-Third/dp/0805073698 (Why Zebras Don't Get Ulcers) by Robert M. Sapolsky This episode is sponsored by http://www.getchews.com/ (TotumVos Collagen Chews). You can find TotumVos at www.getchews.com. *Use code DRDIVA for an additional 10% off your first order.

My top 3 Takeaways from Ira Wolfe - Thriving during the pandemic using the adaptability quotient. Do valedictorians change the world? Two articles referenced below: https://www.cnbc.com/2017/05/24/what-happened-to-your-class-valedictorian-probably-not-much.html https://apple.news/AZ-Q71OVlSkONQK4eXd9dOQ

Turning dreams into reality: In 2014 I turned my life upside down in pursuit of happiness and started my own business.At the time I had no idea what I was doing or where it was going to take me. All I knew to be true was that I wanted to positively impact the lives of others, be more humanly connected and live more in each moment.At the time I also had a dream that one day my work and its impact would be validated.I would write an article for the esteemed Harvard Business Review on how I was helping make people’s lives happier in my business.Again, I had no idea what it looked like, how it would happen, but I wrote that dream down and popped it away in a drawer.In this podcast, I share with you how this small act of writing down a crazy dream with no clear plan on how to make it happen made it happen.This is not one of those bullshit overnight success stories of how I made millions and how I can teach you to do the same.Instead, it's a story of persistence and experimentation that evolved into the creation of my dream business and life.This story is designed to inspire you to put your own dream in a drawer now and to take one small action that moves you closer towards it today!Take the free Hacking Happy Assessment I mention in this episode via hackinghhappyassessment.com to shine a spotlight on where your opportunities for simple intentional action lie!If anything I shared in today’s episode struck a chord with you, slide into my DMs on Instagram (@hackinghappy.co) to let me know all the details!Subscribe & Review The Hacking Happy PodcastThanks for listening to this week's episode! If this podcast helped you in your journey to injecting more of what matters into each day, please head over to iTunes, subscribe to the show, and leave us an honest review. Your reviews help us to continue to create content that enables meaningful change and reach more amazing humans like you.ResourcesTake the Hacking Happy Assessment HereRead my HBR article What You Were Taught About 'Happiness' Isn't TrueFind out more about the Intentional Adaptability Quotient and how it can help youRead the HBR Article on the Adaptability Quotient that helped guide my researchWhere To Find PennyEmailInstagramLinkedInFacebook

On this episode of Mindful Impact with Justin Francisco, our host speaks with Ira Wolfe, a millennial in a baby boomer body, speaker, president of success, and blogger. Listen as they talk about pandemic at large, the fixed vs. growth mindset, including adaptability quotient, and much more.    3 Key Points: The ability of the person to adapt to change depends on personality and behavior. There are those who adapt well or thrive for change.  There are two economies happening now due pandemic, and there’s great difference in the socio-economic status of people in both economies.  Adaptability Quotient provides different dimensions that help people learn how to survive and thrive despite the change.    Episode Highlights:  42:18 Ira Folfe is an older baby boomer who is still learning and growing.  3:42 Carol Dweck's studies show that the most successful kids in the class weren't always successful. 4:48 The fixed mindset is, we are trying to live our bubble trying to protect our image. 4:54 The growth mindset is constantly learning and unlearning. 7:00- We don't go backward, so going back to normal after the pandemic is not going to happen.  8:45 People must be comfortable with change and uncertainty because the new normal is not as predictable as it was.  9:54  We learned in the present, but it conflicts with what we've learned in the past.  11:00 Personalities and behaviors are absolutely impacting change. 13:30 The problem is not the amount of change but the phase at which we experience so much change.  14:50 There are two economies happening amidst the pandemic.  16:51 Front liners are now essential workers and have a more secure job than professionals who are struggling.  22:26 Adaptability Quotient gives different dimensions that helps people get comfortable with change.  24:01 Dealing with ambiguity is by listening to opposing points of view. . 34:00 Adaptability Quotient covers mental flexibility, growth mindset, and unlearning dimension, as well as grit and resilience.  36:00 Resilience is the biggest driver of adaptability.   37:30 The more adaptability you have, the higher is your EQ.  37:55 Adaptability provides courage to have hope for a better future.  38:11 EQ gives hope, courage, positivity in life, and allows us to see challenges as opportunities.  41:02 Change is happening, the pandemic just accelerated that change.   Tweetable Quotes: “You can either look at every3thing as a challenge or everything as an opportunity, and I tend to look at everything as an opportunity. “- Ira Wolfe "What's interesting in these 2 economies, we have a whole group that's thriving and a whole group who's suffering. The socio-economic differences are not great. "- Ira Wolfe ‘Today is the slowest phase of change that we experience in our lives, which is frightening some people and exciting for others. "- Ira Wolfe “We as a leader, not only keep an eye on the ball but also need to be resilient. That's the setback, and we have to learn how to be smart and navigate around that."- Ira Wolfe “You can either decide you gonna be in despair and try to fight the world or help find the courage to thrive in this new world.”- Ira Wolfe   Resources Mentioned: Justin Francisco: LinkedIn, Website Ira Wolfe: LinkedIn Website An Obituary for Normal 

How do we shift the narratives of business so that it becomes part of the solution, not the core of the problem? Mike Raven of AQAI explores the ways business can adapt - and become part of a genuinely regenerative future. More at https://accidentalgods.life

2020 has been challenging for many individuals and businesses. However, it is undeniable that all of us will need to not just accept, but embrace new realities. That’s why adaptability is at the top of the charts for employers, and the forefront of conversations even among friends. Dr. Paul Stoltz, who is considered the world's leading authority on the integration and application of Radical Adaptability, tells us about the Adaptability Quotient and how it can help businesses and people.

2020 has been challenging for many individuals and businesses. However, it is undeniable that all of us will need to not just accept, but embrace new realities. That’s why adaptability is at the top of the charts for employers, and the forefront of conversations even among friends. Dr. Paul Stoltz, who is considered the world's leading authority on the integration and application of Radical Adaptability, tells us about the Adaptability Quotient and how it can help businesses and people.

“There is nothing certain, but the uncertain.” – Proverbs   About This Episode:   In this episode of “#WalkWithMe” I talk about our AQ (Adaptability Quotient) and walk through some thoughts and principles on how we can raise our AQ so that we not only survive but thrive in times of great change, confusion and uncertainty.    ***   For show notes, visit alivebydesign.com    *** If you enjoy the podcast, please consider leaving a short review on Apple Podcasts/iTunes. It takes less than 1 minute, and it really makes a difference in helping spread this message.   ***   Drop by and say “Hi!”   Instagram: instagram.com/blakemallen Facebook: facebook.com/blakemallen.page  Twitter: twitter.com/blakemallen LinkedIn: linkedin.com/blakemallen YouTube: youtube.com/blakemallen   ***   Additional Resources:   Subscribe to my Newsletter at BlakeMallen.com   Watch my TED Talk: ShiftTheScript.com   Interested in sponsoring the podcast?  alivebydesign.com/sponsor

On this episode of Mortgage X, James Robert Lay joins Jason Frazier to discuss the power of the Adaptability Quotient. James also discusses how brands can shift their practices to rethink the customer journey, improving relationships, the fear wall, how mortgage companies can be more agile, and embrace change.

In this podcast, I talk about the top 20 industries that have been majorly affected by COVID-19. And if you happen to be in any one of those 20 industries, it's time for you to turn on your AQ or Adaptability Quotient.If you want to learn how to take your knowledge and turn it into a super-profitable business in the next 90 days, go to http://sidz.co/formula

Do you know your AQ?  AQ is a new(ish) way to measure how adaptable you are.  You are probably familiar with IQ (Intelligence Quotient) and EQ (Emotional Quotient).  AQ rounds out this trio, measuring your ability to adapt to and thrive in an environment of change. So, here’s the cool thing… Moms ROCK when it comes to AQ.  Because motherhood makes even the most Type A, perfectionistic control freak (like me!) more adaptable.  Annnnd, COVID if boosting your AQ #everydamnday - because have you ever had to be more adaptable??? I just started learning about AQ, but I’m so intrigued by this measure and how moms can use it to gain power in our communities.  Tune in to learn why your AQ matters, your personal AQ score, and specific steps to boost your AQ.  Links mentioned: Register for our Construct Your Core Values Workshop Nancy Kane article: How Adaptable Are You?   

From commanding the stage with President Obama, Richard Branson, and Jessica Alba, to advising heads of state and coaching top entrepreneurs, Dan Ram is an international voice on living a creative adaptable life with purpose and passion. He speaks on how, in one weekend he lost over 30 bookings and resorted to creative thinking to rebuild his platform and focus during this pandemic. He is an expert on the adaptability quotient (AQ) and shares the top skills, strategies and tips to living a creative joyful life with purpose. Enjoy the show and his amazing energy! DanRam's Website DanRam LinkedIn   Thanks to our sponsor LetfordMedia for sponsoring this show!   Follow us on social media! Facebook IG: @CreateAndGrowRich Twitter: @RichCreate

In Career 360, Howie Lim and Rachel Kelly spoke to Dr. Paul. G Stoltz, CEO of Peak Learning on why the Adaptability Quotient is the new gauge of well-being and success. In a recent survey conducted by NTUC Learning Hub, it found that Adaptability and Resilience are the most coveted skills by employers today.

In this ever-changing world that we live in, remaining stagnant no longer works. For this reason and many others, Ross Thornley and Mike Raven founded AQai. In this episode, Ross and Mike talk about what drew them into the adaptability space and how they ended up working together. They discuss how their work focuses on discovering adaptability, and share some of the things they see that will remain the same as well as those that will be different, considering the world we live in now. To further explain, they then give an overview interpretation of Dr. Diane Hamilton’s adaptability assessment scores and what she can improve. Mike and Ross also debunk the potential myths and misconceptions around the whole area of assessments. Love the show? Subscribe, rate, review, and share!Here’s How »Join the Take The Lead community today:DrDianeHamilton.comDr. Diane Hamilton FacebookDr. Diane Hamilton TwitterDr. Diane Hamilton LinkedInDr. Diane Hamilton YouTubeDr. Diane Hamilton Instagram

As infants we want to belong and feel safe, so we adjust ourselves to fit in. As we grow into adulthood, we are confronted with our internal programming and its effects on our self-image. A strong and harsh inner critic prevents us from treating ourselves with empathy. The Energy Management Compass is an awareness tool, created so you can implement self-acceptance, self-appreciation, and self-love. To be able to adapt and embrace change and disruption requires you to overcome your internal blocks. This week's podcast dives deep into how to update your programming towards unconditionally loving yourself. Knowing how to re-ignite your ability to love yourself creates the clarity to enhance your Adaptability Quotient. Two fundamental blocks to think about for implementing your Energy Management Compass: 1. Characteristics of your personal internal language of love 2. Fear based signals: the gremlin inside us These two cornerstones are part of my methodology of updating how you experience safety, freedom, and connection. Tune in for Amor Muto Discovery if you are looking to change how you treat yourself. Share your biggest take-away from the podcast so far and tag me in your post to win 3 free coaching sessions worth 600 Euro. Message me why you want coaching, the 2 winners are announced at the end of the month. #mentalhealthawareness #kindness #energymanagement #coaching #executivecoach #breakthrough #progress #podcast #selflove #unconditional #loveyourself Find me on IG https://www.instagram.com/amor_muto/ FB https://www.facebook.com/amormuto1 TW https://twitter.com/amormuto YT https://youtube.com/amormuto --- Send in a voice message: https://anchor.fm/amor-muto/message

Relationships matter – more than money, more than status, more than material things. ~ Arlan Hamilton, It’s About Damn TimeFounders have characteristics that are not based on gender or race – they are extreme problem solvers with the ability to withstand high levels of uncertainty. They have tenacity, grit, resilience, and a high AQ! Adaptability Quotient. They follow their North Star, and they love the process.One does not need a degree or pedigree to be a funder, but when you’re underrepresented and underestimated, you have to watch out for unconscious bias.Our guest, Arlan Hamilton, is the founder and managing partner of Backstage Capital, a venture capital firm that exclusively invests in companies founded by women, people of color and LGBTQ entrepreneurs. Her journey from Tour Manager for music groups to founder of a VC firm, is extraordinary. She had a backpack, a laptop and a dream of becoming the Robin Hood of venture capital.In her recently published book, It's About Damn Time (https://amzn.to/2SGKn2u), Arlan shares how she turned her big, hairy, audacious vision of launching her own investment firm into reality despite all the evidence that shouted "oh hell no!" Arlan was so committed to her mission, that she was homeless when Backstage Capital's raise was finalized!From the opening line to the final piece of advice, I was consumed by Arlan’s stories, strategies, solutions, insights and inspiration for founders and for anyone pursuing a dream. As a founder of 4 businesses and a mentor/coach to newbie founders, I was delighted to find terrific reminders and new ways of viewing the startup journey. Given my deep knowledge of and experience with Venture Capital, it is JAW-DROPPING to read how Arlan built Backstage Capital! Throughout It’s About Damn Time (https://amzn.to/2SGKn2u ) she shares strategies, tactics and mindset hacks that helped her persevere without a smidgen of “traditional” experience, connections, and let’s be honest “the VC look.”The chapter on Resilience helped me go even deeper into accepting a painful, scary time in my life that required a lot of forgiveness. This period absolutely prepared me for my work in the world, as nothing else could prepare me. Thank you Arlan for reminding me these were “experiences built just for me.”Being a founder is hard work, and in moments of profound discouragement, we need reminders of why we're building a business, and why we are uniquely qualified to build our business for our customers. We need role models like Arlan Hamilton who share their struggles and stories so we can forge forward under enormous levels of uncertainty and constraints.Dear Founders - I gratefully share this interview with Arlan and It's About Damn Time so you may be reminded and inspired to continue bringing your gifts to the world. ♥Grab your copy of It's About Damn Time here: https://amzn.to/2SGKn2u To learn more about Backstage Capital, please visit: https://backstagecapital.com/Please follow Arlan Hamilton and Backstage Capital everywhere they GLOW:Twitter: https://twitter.com/ArlanWasHere and https://twitter.com/Backstage_CapInstagram: https://www.instagram.com/arlanwashere/ and https://www.instagram.com/backstagecapital/LinkedIn: https://www.linkedin.com/in/arlanhamilton/ and https://www.linkedin.com/company/backstage-capital/If you’d like to receive an alert whenever I post a new episode, please follow the Startup Life Show wherever you listen to podcasts, including: Stitcher, Spotify or Apple/Google Podcasts… and let’s connect on social media! You’ll always find me hanging out at my favorite social media bar – Twitter! https://twitter.com/AndeLyonsTo receive an alert for my live show airing every Tuesday at 7pm EST, please join my Meetup group here: https://www.meetup.com/Startup-Life-LIVE/Do you have a startup story you’d like to share on the Startup Life Show podcast? Please reach out to me via email – ande@andelyons.com. You'll find tons of curated DIY startup advice on my YouTube Channel Andelicious Advice: https://www.youtube.com/user/AndeliciousAdvice and please subscribe to my bi-monthly newsletter, Let’s Stick Together -> http://bit.ly/AndeliciousNewsletterDo you need a pitch deck reviewed? I've raised millions from VC and thousands from Angels... and I'm a co-host of a monthly pitch event in Boston. I can make sure your deck is ready for investors and a pitch event. Click this link to learn more: http://bit.ly/PitchDeckAuditDo you need an “Urgent Care for Startup Founders” coaching session? You can schedule me by the minute here: https://andelyons.as.me/ Need an audio or video transcribed? Use Otter.ai: https://bit.ly/StartupLifeOtter Listeners - thank you so much for tuning in - I am genuinely grateful for your time and presence. Stay strong, stay focused – and please remember – you’ve got this – Cheers!Ande ♥

In this episode, Jeff and Ron discuss: • Ron's impressive career journey from wanting to quit the business to his innovating and pioneering path in financial advising.• The dimensions of trust and how to move up the dimensions.• The evolution of digital connection to the future of the financial advising industry.• Putting yourself, your physical health, and your mental health as a priority.  Key Takeaways: • Think about the heirarching between customer, client, and advocate with those that you work with and serve. How are you moving your customers to become clients then to advocates?• People crave connection. Even in times like these where we are so isolated, we need to find ways to connect with one another however we can.• Complacency is the most common form of business cancer - you must be able to adjust and challenge yourselves to better yourself and your company.• Balance leads to growth, growth leads to balance.• Build whitespace into your calendar - thinking is something we should all spend more time doing.  "Reinvent yourself before your competition forces you to." —  Ron Carson 

Has anyone ever pushed you into a cold lake you were too scared to jump into? Once you get over the initial shock, you find yourself happy to be in the water.  Well, COVID-19 has pushed people into new financial waters — and they’re already getting over the shock.  At least, that’s how my guest, Jim Marous, Host of the Banking Transformed Podcast, sees our current situation. I sat down — remotely, of course — to learn why he believes the “new normal” we’ve adapted to will eventually just become, well... normal.  We went over: -Why your adaptability quotient trumps EQ or IQ -Why the changes brought by COVID-19 are here to stay -Why now is the best time to try something new You can find this interview, and many more, by subscribing to Banking on Digital Growth on Apple Podcasts, on Spotify, or here.

Today's guest came into my world towards the end of last year when I was blessed to meet her at The Singularity U conference in Sydney. Her name is Penny Locaso and when we started working together - I knew that the right person had entered my life at exactly the right time.At that time, on a personal level I was working around the clock and I was struggling to balance the long list of priorities that came with being an entrepreneur, along with being a relatively new mum, a fionsai, daughter and friend. In many ways I had never been more ‘successful’ in the traditional sense of the world - but in other ways I was tired and feeling pretty overwhelmed.I want to use a galloping horse here as a metaphor. Let's call this galloping horse quote unquote ‘busy’. While dismounting from a standing horse is easy getting off a galloping one feels dangerous and scary. It is a landing that is undeniably going to hurt. Sometimes it feels easier just to hang on for dear life….but that choice is stressful. I know that feeling! And while I leave you pondering the galloping horse - lets add some context. I am on the galloping horse and covid 19 hits. It's a crisis yes - but it is also the one thing that makes that horse come to a halt. Finally I can get off the horse.I use this busy horse metaphor today because if you are like me….you may not want to get back on that galloping horse without any breaks. And definitely not with the same speed or in the same way.For me - I want to use this time to adapt and to build the foundations of what happiness is in my world and then I will be ready to ride again. But this time on a horse where I feel safe. This is the exact reason why I knew Penny Locaso was the person I wanted to get some advice from on what that horse looks like. After all it's not often we get the chance to choose again.Voted one of the most influential female entrepreneurs in Australia Penny is the world’s first Happiness Hacker, on a mission to teach 10 million humans, by 2025, how to intentionally adapt in order to future-proof happiness.Penny Locaso is the Founder of BKindred and the creator of The Intentional Adaptability Quotient. IAQ is a world-first education program and measurement tool that decodes the skills required to thrive in an age being redefined by two trends: the busyness epidemic alongside the impact of disruptive emerging technologies.In order to take IAQ out into the world Penny founded Bkindred in 2015 which is a ‘do tank’ with a core focus on unleashing the power of Adaptability. Since its inception, Penny has grown BKindred from a one-woman show to a tribe of unlike minds, entrepreneurs, pioneers, researchers and visionaries who deliver a selection of keynote presentations, workshops and long term training programs within corporate and educational organisations.Alongside Penny's entrepreneurial endeavours, she is a faculty member at the esteemed Singularity University. This position has her working alongside some of the best technology and Artificial Intelligence innovators in the world enabling her to gain valuable insights into emerging technology in addition to decoding the human implications of rapid change. She has partnered with prestigious brands including Google, Atlassian, Microsoft, Bookings.com SalesForce, Deloitte and KPMG, to name a few.Today Penny is an International keynote speaker, educational innovator, and author preparing to release her debut book in 2020, titled Hacking Happiness. On stage Penny has an aura of authority, born from in depth research and acquired mastery on the subject of Adaptability. She has a natural charisma and her message will strike a chord with any audience addressing one key question. How do we cease reacting and start intentionally adapting?Welcome to the podcast Penny Locaso.

Desiree Grace is the 2017 NAED Trailblazer Award winner and hosts the "Riveting Exchanges" podcast with Andrea Olson. Andrea Olson is a strategist, speaker, author, and customer centricity expert.

“Be willing to change because life won’t stay the same.” Anonymous When Emanuel Thomas and I sat down to record this podcast, Covid-19, Pandemic, and Outbreak were absent from headlines. The main concern that Tuesday afternoon early in the month of March was whether we'd continue to see rain all week or if sunshine would grace us and usher in an early Spring. Little did either of us know that when this podcast would air, many people will be in the midst of the most uncertain and volatile time of their lives. Regardless of the environment that day, our focus was on adaptability. Emanuel Thomas is a TEDx Speaker, Transformational Mindset Coach, Columnist, and the author of "The Power Of Thinking Inside The Box." When exploring the topic of today's podcast, Emanuel educated me on the concept of AQ. If you're reading this, chances are you have a basic understanding of what IQ is and what it measures. I'm even willing to venture you've explored the meaning and importance of EQ at some point as well. These two terms respectively translate into Intelligence Quotient and Emotional Quotient. When it comes to growth and development, we typically focus on these two measurements and increasing them at some point in our lives. However, what if there was another variable to consider? We're talking about your Adaptability Quotient. (AQ) How good are you at adjusting to your environment? How aware are you of your current stress level? These are the questions Emanuel and I pose when discussing AQ. One thing we knew for sure that early March afternoon is that life is going to happen. We will be tested and those challenges lurk right around the corner. How will you prepare for it? Here we are being tested by a Pandemic that doesn't have an expiration date posted. How will we come out on the other side? Take a listen to today's episode as Emanuel and I discuss the importance of going through it, documenting your movements, and accepting weakness as strength. In Emanuel's words; "The peaks can't teach you what the valleys can." We're all in the valley now. What are you learning? Be sure to connect and read more of Emanuel's work below: Website: https://www.empowersight.com/ Facebook: https://www.facebook.com/emanuel.thomas.1272 Instagram: https://www.linkedin.com/in/mremanuelthomas/ Twitter: https://twitter.com/etthemotivator/ LinkedIn: https://www.linkedin.com/in/mremanuelthomas/ Also, be sure to pick up the book on Amazon today! If you enjoyed this episode, I encourage you to join our Patreon Page and help us continue to bring you more great content. If you are unable, no worries! You can show your support by sharing this with a friend or leaving us a review on iTunes. Every little bit helps! Become a Patron! This Podcast was filmed in the studio at ComRADery: A collaborative Work Space in Greenville, SC. If you live in the Greenville area, connect with ComRADery and find out how you can try the space for FREE! Be sure to mention you found them through the No Rain… No Rainbows Podcast! I hope you enjoy this episode of No Rain… No Rainbows. #LetsGrow

40% of the jobs that exist today will not exist in 10 years’ time. Fuelled by technology, change is coming at a rate that exceeds our ability to adapt. What got past generations here, won’t get the next to where they want to be. Rapid technological change means we must all keep learning. Our ability to adapt can be measured by our adaptability quotient (AQ) which is becoming a big talking point for those serious about their future career success. In today's episode of Tech Talks Daily, I want to learn more about AQ, or adaptability quotient which is the first-ever holistic metric of adaptability in the workplace. At Adaptai, their aim is to not only quantify and provide insight into AQ but also to help individuals and organizations to improve their ability to adapt in the fastest period of change in human history via their future coaching and digital training programs. They measure adaptability across three core dimensions (ACE): Ability (your adaptability skills), your Character (the innate aspects of Self that determine the ways in which you may approach adapting), and Environment (how your environment can help or hinder your adaption). Together with twelve sub-dimensions, such as Grit, Resilience, Mindset, and Learning Drive, they can give an accurate picture of where you are in terms of your AQ journey. AQai are working collaboratively with experts, universities, professors, leaders in psychology, people analytics, and human behaviour to build a robust and accurate measure of human adaptability in the workplace. Ross Thornley, co-founder of Adaptai joins me to talk about they are making a difference. I learn why people are moving from EQ to AQ and why it’s the key to the future of work.

Welcome to another episode of the Decoding Purpose Podcast!Today I am feeling the buzz of the festive season upon us, so what better time to have a little bit of fun and to celebrate your tribe — those extraordinary human beings who make your world go round. And in my case, that tribe happens to consist of some of the brightest minds on the planet. Scientists, technologists, entrepreneurs and musicians who fundamentally believe through intelligent optimism we can change the world ...and that the world is already changing in the most miraculous of ways. That tribe is known as Future Crunch.Collectively we believe that science and technology are creating a future that is more peaceful, connected and abundant. We’re determined to share that story - via epic newsletters jam-packed with good news stories from all over the world, keynote presentations even fusing music with meaning as we lean into the intersection between performance and purpose — creativity and Thought Leadership.Today's guest on the podcast is the co-founder of Future Crunch and my business partner - the Incredible Dr Angus Hervey. Gus and I were both incredibly excited to come together for this podcast to firstly celebrate the birth of his newborn daughter and newest member of our tribe but to also decode turning points, mindset, the media and movements in our pursuit to unlock the power of both purpose and intelligent optimism.The most exciting part is that we also unpacked Futures Crunch brand new keynote launching in 2020 - The Adaptability Quotient. Why might you ask? Two reasons: because at Future Crunch we believe that adaptability is an essential skill for navigating the 21st century, and purpose is the anchor by which adaptability can thrive. You’ve heard of IQ and EQ; this century belongs to those that are quick to read and act on signals of change.To give you a brief recap of Angus's formal bio - he is a political economist specialising in the impact of disruptive technologies on society. Along with founding Future Crunch, he was the founding community manager of Random Hacks of Kindness, a global initiative from Google, IBM, Microsoft, NASA and the World Bank to create open-source technology solutions to social challenges. He was also the first editorial manager for Global Policy, one of the world's leading international policy journals. He holds a PhD in Government and a Masters in International Political Economy from the London School of Economics, where he was also the Ralph Miliband Scholar from 2009 to 2012.Now to stay in the spirit of Adaptability - today, I wanted to shake things up with the intro and have some creative fun. It just so happens that I am also joined in the studio by the most creative member of The Future Crunch team - our in house philosopher Will Tait. Will is the creative genius behind the keyboard performing with Future Crunch at prominent events in 2019 including Tedx Melbourne and SingularityU Australia, and he has created a special surprise intro for Dr Angus Hervey.Welcome to the Decoding Purpose Podcast!

How refined are your adaptability skills? In this episode of Shannon Waller’s Team Success, Shannon is joined by the creator of the Adaptability Quotient, Ross Thornley. Discover how un-learning and letting go of what got you here is key to understanding what will you get there. The post What’s Your Adaptability Quotient? – With Entrepreneur And Expert Ross Thornley appeared first on Your Team Success.

There's a new intelligence on the block and everyone wants a piece of it. Do you have a high one? Do you have a high AQ? Listen to today's podcast to get into the know about the Adaptability Quotient and why it's important for you to start work on increasing yours now. Article mentioned: https://www.fastcompany.com/40522394/screw-emotional-intelligence-heres-the-real-key-to-the-future-of-work Book mentioned: Play Bigger: How Pirates, Dreamer, and Innovators Create and Dominate Markets by Al Ramadan: https://amzn.to/2F6Jbic http://michellespiva.com/Amz-AlRamadan-PlayBigger Don't forget to use our Amazon link to support the podcast by using our Amazon Shopping link! http://MichelleSpiva.com/Amz For Interviews, sponsorship, or coaching/consulting, please send inquires to: MichelleSpiva at gmail dot com (no solicitation-spam; *You do not have permission to add this email to any email list or autoresponder without knowledge or consent) _____________________________ Further support this podcast, please do so by using any of these methods: All your Amazon shopping: http://michellespiva.com/Amz Venmo: @MichelleSpiva1 CashApp: $MichelleSpiva PayPal: http://bit.ly/Donate2Michelle Patreon: https://Patreon.com/MichelleSpiva Don't forget to like, comment, subscribe, rate, and review. Follow Michelle here: Facebook: facebook.com/FollowMichelleSpiva Twitter: @mspiva IG: @MichelleSpiva Find out more about Michelle's alter-ego fiction writer side: Amazon Author Page: http://amzn.to/2lIP6Om Facebook: facebook.com/MychalDanielsAuthor Twitter: @mychaldaniels IG: @MychalDaniels Website: MychalDaniels.com/connect --- Send in a voice message: https://anchor.fm/michelle-spiva/message Support this podcast: https://anchor.fm/michelle-spiva/support

เท้าความจากตอนที่แล้วเราได้พูดถึง Adaptability Quotient หรือความสามารถในการปรับปรุง เปลี่ยนแปลง ปล่อยวาง และไปต่อ ว่ากุญแจสำคัญอันดับหนึ่ง ในการมีชีวิตแบบ Healthy & Wealthy นะครับ และสิ่งที่จะเพิ่ม AQ ได้คือการเริ่มมีจินตนาการ

Episode 183: Chuck Garcia, Founder of Climb Leadership International.Tune in to hear Chuck discuss: How to motivate your employees to reach new height. The importance of mentoring and how to master it. The “Client Development Mindset”. How to develop exceptional communication skills. How “Emotional Intelligence” and “Adaptability Quotient” are effecting leadership development

Episode 183: Chuck Garcia, Founder of Climb Leadership International.Tune in to hear Chuck discuss: How to motivate your employees to reach new height. The importance of mentoring and how to master it. The “Client Development Mindset”. How to develop exceptional communication skills. How “Emotional Intelligence” and “Adaptability Quotient” are effecting leadership development Learn more about your ad choices. Visit megaphone.fm/adchoices

How do you prepare yourself or your business for the future? With the advancement in technologies today, it’s easy to feel stressed and overwhelmed. So how do you keep up? Find out the answers on today’s episode as Jon interviews Nancy Giordano, a strategic futurist, speaker and founder of Play Big Inc. It is a company that helps businesses define and shape their future. They delve into the topics of AQ (Adaptability Quotient), self-awareness and curiosity and how these factors help us adapt to the future and prepares us for success in this dynamic and unpredictable world that we live in.   “When you asked me about the one thing that we need to cultivate in kids, it's curiosity and wonder.” -Nancy Giordano Subscribe to the podcast on: Apple Podcast Stitcher Castbox PodBean TuneIn Radio   Timestamps: 00:59 - Background on Play Big Inc. and how it help companies define and shape their future  03:35 - What is AQ (Adaptability Quotient) and how it can help us in this fast-changing, dynamic world 08:21 - Proper mindset to be productive and innovative and why unlearning is the harder part of adapting 11:58 - The importance of self-awareness and mindfulness to adaptability quotient 16:10 - Collaborating and learning how to learn with others 19:38 - Benefits of having employees with self-awareness plus tips on how to build self-awareness 27:07 - Why it’s important to cultivate curiosity and why some employers are not supportive of it 29:48 - The important role of the environment and the people around us to our curiosity and success 31:40 - Removing the fear of technology and having the ability to manage it   Resources: Agility CMS Play Big Inc. Amin Toufani Tedx Myers Briggs Strengths Finder Enneagram Jacqueline Novogratz Agile Living Episode 1 - The Overlooked Power of Curiosity with TedX Speaker Cameron Brown   Connect with Nancy: nancygiordano.com LinkedIn Twitter   Connect with Jon: Facebook LinkedIn

Perpetual Learning = To Thrive ….. Happiness Hacker and Human First host Penny Locaso shares her hacks on developing the skills needed to thrive in an unprecedented future of artificial intelligence and technology.As we enter the fourth industrial revolution, uncertainty is becoming the new normal, how do we remain relevant in the context of change? How can we help our children to adapt in this new world we find ourselves in?This Week Happiness Hacker and Human First host Penny Locaso shares her perspectives on:· Why your Adaptability Quotient is critical to thriving in a world of exponential technological growth· Six foundational pillars to focus on if you want to amplify your AQ, or that of your children· Simple hacks to support the amplification pillars, and remain relevant

The ability to re-invent one’s self is arguably one of the most important qualities that anyone can have. With the world changing as quickly as it is these days you essentially you need more than IQ and EQ to be successful – you now need something called AQ or what the Singularity University calls the Adaptability Quotient i.e. how quickly can you adapt to a changing world and to either solve a problem or fill a gap. In this episode, I chat to Ran Neu-Ner who is most known for the sale of this agency to the Publicis Group for north of a billion rand (for my US listeners that is just shy of $100 million). After the exit, Ran spent some time studying at the Singularity University and at Harvard in the states and it was this experience that lead to him founding a new passion for cryptocurrencies and the blockchain. Today Ran is the host of Crypto Trader on CNBC Africa – and it represents the first show of its kind in the world which is making big waves in the #cryptocurrency community. I chat to Ran about his journey with the show and how he approached reinventing himself to fill a gap in the global cryptocurrency trading market http://www.digitalkungfu.co.za/ran-neu-ner-co-ceo-creative-counsel/