Podcasts about Wright

As we travel the paths of unseen existences in our long pilgrimage through life, we do so in the company of angels.

CheckoutThe God Centered Concept Academy Training Community to learn what growth in Christ ishttps://api.tuvu.com/redirectGroup/6a2ac0e2c9f728027338244cCheck out this link to view Kingdom Cross Roads on TV.https://jesussaid.tv/?affiliate=tswright_gccTo get a copy of our new book "Embracing the Truth" or to have TS Wright speak at your event or conference or if you simply want spiritual or life coaching or just a consultation visit:www.tswrightspeaks.comVisit our website to learn more about The God Centered Concept. The God Centered Concept is designed to bring real discipleship and spreading the Gospel to help spark the Great Harvest, a revival in this generation.www.godcenteredconcept.comKingdom Cross Roads Podcast is a part of The God Centered Concept.What changes when you stop defining yourself by your failures and begin seeing yourself as God sees you?On this episode of Kingdom Cross Roads Podcast, T.S. Wright welcomes Tom Anderson, author of From Sinnership to Sonship: The Story of Becoming. Tom shares how God transformed his marriage, deepened his faith, and led him from feelings of inadequacy into the security of biblical sonship.Drawing from the lives of Adam, Abraham, and Peter, Tom explains why spiritual transformation is a journey. Abraham began as a man who believed in God but struggled to believe what God said about him. Through waiting, testing, surrender, and “hoping against hope,” Abraham grew into his God-given identity.You will discover:What Tom means by the “I am not” mentality of sinnershipHow sonship provides worth, significance, and spiritual securityWhy God often sends a word before meeting a needHow God used Isaiah 43:18–19 to bring restoration to Tom's marriageWhat Adam's garden teaches us about purpose, service, and stewardshipWhy your marriage, family, workplace, and relationships are gardens entrusted to your careHow Abraham's journey illustrates believing, hoping, surrendering, and becomingWhy trials may be part of God's process of teaching you to trust HimHow knowing you are loved by the Father changes the way you live and serveYour identity is not based upon your achievements, possessions, position, or past failures. In Christ, you are called, loved, and kept. God is inviting you to move beyond striving and rest securely in your identity as His beloved son or daughter.Scriptures DiscussedIsaiah 43:18–19; Genesis 1–2; Genesis 15; Genesis 22; Psalm 139; Romans 4; 2 Corinthians 5:20; Jude 1Connect with Tom AndersonLearn more about Tom, read about From Sinnership to Sonship: The Story of Becoming, and find links to purchase the book at TomAnderson.in.KeywordsTom Anderson, From Sinnership to Sonship, identity in Christ, biblical sonship, Christian identity, sons and daughters of God, spiritual transformation, Christian personal growth, trusting God, faith in difficult times, hope against hope, Abraham and faith, Adam and the Garden of Eden, Christian marriage testimony, hearing God's voice, God-given purpose, beloved by God, Kingdom Cross Roads Podcast, T.S. Wright, Christian podcast, Bible teaching, discipleship, Isaiah 43, Romans 4, Psalm 139

On this episode of The Steve Dangle Podcast, 00:00 Pack openings 08:00 Bedard signs 33:00 Fantilli and Jet Greaves 40:00 Cap and expansion talk 1:00:00 Kirby Dach signs for one year in Montreal 1:07:30 Where does Laine play next year? 1:15:00 Wright to Pittsburgh? 1:26:00 NHL broadcast training camp 1:41:00 Pack openings Visit this episode's sponsors: Sign up for a free trial period at https://shopify.com/sdp. Go to https://shopify.com/sdp now to grow your business–no matter what stage you're in. Watch all episodes of The Steve Dangle Podcast here: https://www.youtube.com/playlist?list=PLLk7FZfwCEidkgWpSiHVkYT7HrIzLPXlY Watch clips of The Steve Dangle podcast here: https://www.youtube.com/playlist?list=PLLk7FZfwCEieOJuIrqWyZPWSIJtVMCbLz Buy SDP merch https://sdpnshop.ca/ Visit https://sdpn.ca/schedule to see when our next live stream airs! Check out https://sdpn.ca/events to see The Steve Dangle Podcast live! Watch hockey with us! Live on YouTube: https://www.youtube.com/playlist?list=PLLk7FZfwCEifCTX0vkKEaGg9otrW4Zl2k Subscribe to the sdpn YouTube Channel: https://www.youtube.com/@sdpn?sub_confirmation=1Join Subscribe to SDP VIP!: YouTube: https://www.youtube.com/channel/UC0a0z05HiddEn7k6OGnDprg/join Apple Podcasts: https://apple.co/thestevedanglepodcast Spotify: https://podcasters.spotify.com/pod/show/sdpvip/subscribe - Follow us on Twitter: @Steve_Dangle, @AdamWylde, & @JesseBlake Follow us on Instagram: @SteveDangle, @AdamWylde, & @Jesse.Blake Join us on Discord: https://discord.com/invite/MtTmw9rrz7 For general inquiries email: info@sdpn.ca Reach out to https://www.sdpn.ca/sales to connect with our sales team and discuss the opportunity to integrate your brand within our content! Learn more about your ad choices. Visit megaphone.fm/adchoices

What happens once a society finds a way to turn a human body into an energy source, and decides that's a good deal? Podcaster and TruStory FM co-founder Pete Wright joins Matthew and Paul to talk about “Lattice,” his debut science fiction novella, and the death penalty, corporate power, and family loyalty questions Wright built into its plot from the very first chapter.Wright talks about writing the book's bones as a teenager and only now finishing it, while Matthew and Paul push on why the story never lets its villains twirl a mustache, they just sign off in a procurement meeting. They get into the Kobayashi Maru, the Batman choice, and a death penalty scene with no last-second rescue. What does it cost a person to have power and refuse to use it?Full show notes and resourcesConnect with Pete Wright: Website**************************************************************************This episode is a production of Superhero Ethics, an Ethical Panda podcast and part of the TruStory FM Entertainment Podcast Network. Check out our website to find out more about this show and our sister podcast Star Wars Generations.We want to hear from you! Keep up with our latest news and send us feedback, questions, or comments via social media or email.TikTok · Twitter/X · Instagram · Facebook · EmailJoin the conversation in the Star Wars Generations and Superhero Ethics channels on the TruStory FM Discord.Want even more content while supporting the podcast? Become a member! For $5 a month or $55 a year you get access to bonus episodes and bonus content at the end of most episodes — and you can even give membership as a gift. Sign up here.You can also support us through our sponsors:Purchase a lightsaber from Level Up Sabers, run by friend of the podcast Neighborhood Master Alan.Use Audible for audiobooks. Sign up for a one-year membership or gift one through this link.Purchase any media discussed this week through our sponsored links.

In the long-awaited Round 4 of our "Ludwig von Mises vs. A Christian Scholar" series I examine one of the most important questions at the intersection of biblical theology and economics: what is the relationship between justification, righteousness, and social justice? In the first half of this episode, I review James D. G. Dunn's understanding of righteousness and justification as presented in The Justice of God: A Fresh Look at the Old Doctrine of Justification by Faith. In the second half, I critically evaluate and challenge Alan Suggate's chapter in the same volume, arguing that while he rightly recognizes that justification has profound social implications, he reaches mistaken economic conclusions that are inconsistent with both Scripture and sound economics. Beginning with the Old Testament and Paul's letter to the Romans, I argue that Dunn is right to emphasize that righteousness is both vertical and horizontal, encompassing our relationship with God and our relationships with others. Those who are justified by grace through faith are incorporated into God's covenant family and transformed by the Holy Spirit, meaning that justification necessarily has social consequences. I then argue that Suggate incorrectly concludes that these social implications justify coercive government redistribution, whereas the biblical vision of righteousness is better embodied through voluntary cooperation, peaceful exchange, and Christian charity. Drawing on the Austrian School of economics, particularly the work of Ludwig von Mises and Friedrich Hayek, I critique Suggate's analysis of markets, wealth, and social justice, contending that free markets foster social harmony, reward service to others, and provide the conditions for genuine charity without resorting to state coercion. Ultimately, I argue that Paul's vision of justification calls the church to embody the cruciform righteousness of Christ through lives of sacrificial love, demonstrating that biblical concern for the poor is not only compatible with economic liberty but is best realized through voluntary rather than coercive means. Media Referenced:Mises Round 1, Michael Gorman: https://libertarianchristians.com/episode/ludwig-von-mises-vs-christian-scholar-round-1-michael-gorman/Mises Round 2, James K.A. Smith: https://libertarianchristians.com/episode/ludwig-von-mises-vs-christian-scholar-round-2-james-k-a-smith/Mises Round 3, N.T. Wright: https://libertarianchristians.com/episode/ep-178-ludwig-von-mises-vs-a-christian-scholar-round-3-n-t-wright/ The Protestant Libertarian Podcast is a project of the Libertarian Christian Institute and a part of the Christians For Liberty Network. The Libertarian Christian Institute can be found at www.libertarianchristians.com.Questions, comments, suggestions? Please reach out to me at theprotestantlibertarian@gmail.com.  You can also follow the podcast on Twitter: @prolibertypod, and YouTube, @ProLibertyPod, where you will get shorts and other exclusive video content. For more about the show, you can go to theprotestantlibertarianpodcast.com. If you like the show and want to support it, you can! Go to libertarianchristians.com, where you can donate to LCI and buy The Protestant Libertarian Podcast Merch! Also, please consider giving me a star rating and leaving me a review, it really helps expand the show's profile! Thanks!

In this episode of the Daily Mastermind, host George Wright III delves into the crucial role of networking in achieving entrepreneurial success. He emphasizes that a network is not just a component of success but the foundation of it, offering access to opportunities, wisdom, resources, and collaboration. Wright discusses common networking pitfalls, such as treating relationships transactionally and not investing time to maintain them. He provides actionable advice on building a strong network through genuine, value-driven relationships, becoming a connector, and focusing on long-term investment in people. Additionally, he highlights the importance of personal growth and how elevating one's identity can help attract high-level connections. Wright also celebrates the podcast's achievement of ranking at the top of the Apple Podcast charts for entrepreneurship and business, and invites listeners to join the Authority Media Network for further growth.01:23 The Importance of Your Network02:47 Common Networking Mistakes04:11 Building Genuine Relationships06:50 Elevating Your Network and IdentityThanks for listening, and Please Share this Episode with someone. It would really help us to grow our show and share these valuable tips and strategies with others. Have a great day.George Wright III“It's Never Too Late to Start Living the Life You Were Meant to Live”FREE Daily Mastermind Resources:CONNECT with George & Access Tons of ResourcesGet access to Proven Strategies and Time-Test Principles for Success. Plus, download and access tons of FREE resources and online events by joining our Exclusive Community of Entrepreneurs, Business Owners, and High Achievers like YOU.Join FREE at DailyMastermind.comFollow me on social media Facebook | Instagram | Linkedin | TikTok | YoutubeGrow Your Authority and Personal Brand with a FREE Interview in a Top Global Magazine HERE.

Can a publication first released in 1818 really predict the weather months or even years in advance?In this episode of MX3 Podcast, we explore the history and surprising popularity of the Farmers' Almanac, its claimed 80–85% forecasting accuracy, and the methods behind its long-range predictions. We also break down its fall 2026 forecast for Oklahoma, Texas, the Ohio Valley, Alaska, Hawaii, the Pacific Northwest, the Atlantic Corridor, and other parts of the United States.How does an old-fashioned annual publication compete with satellites, computer models, and modern meteorologists? Why do so many farmers and ranchers still swear by it? And should you trust its predictions when planning crops, vacations, festivals, or outdoor events?Tell us in the comments: Do you trust the Farmers' Almanac more than your local weather forecast?

How did a nation with less than 5% of the world's population come to publish over half of all the newspapers? This week Author Alex Wright discusses his new book, Empire of Ink: The Printers, Rogues, and Radicals Who Invented the American Newspaper. Wright takes us on a journey through the explosive, footloose growth of 19th-century American print media. From the early "gift economy" of open-source story sharing and the lucrative media empire of Benjamin Franklin, to the dangerous world of gunslinging editors and Mark Twain's disastrous tech investments, Wright details how an unruly young democracy leveraged bold public policies and a distinct mania for news to forge its national identity.

Hosted by Tim Zipoy, Business Service Coordinator for Wright and Sherburne Counties at Central Minnesota Jobs & Training Services. Join Tim as he highlights opportunities for employment and a better quality of life in and around Wright County!  

Some great racing from SDL with one of the most incredible finishes in recent memory in the 250's, Wright domation in the 450's, Rempel making up ground, some crashes, a few big DNF's and a bit of everything else.  Race Tech!!! CJR Suspension KTM, Husqvarna and GasGas Heavy Metal Equipment & Rentals Hall race Fuels and Renegade Gopher Dunes Yamaha Motor Canada Matrix Concepts Canada AMO Grip 'N' Rip MX SECO Seat Covers As always, the best way to support us, is to support them!  

"Every one of us is shadowed by an illusory person: a false self. This is the man that I want myself to be but who cannot exist, because God does not know anything about him. And to be unknown of God is altogether too much privacy. My false self is the one who wants to exist outside the reach of God's will and God's love—outside of reality and outside of life. And such a self cannot help but be an illusion."–Thomas Merton, New Seeds of Contemplation

All Home Care Matters and our host, Lance A. Slatton were honored to welcome Dr. Vicki Wright-Hamilton as guest to the show.   About Dr. Vicki Wright-Hamilton:   Dr. Vicki Wright Hamilton is the founder of VWH Technology, LLC and the creator of PeacefulCare, the AI-powered Caregiver Command Center. She's spent more than four decades in executive leadership, including time as a Chief Operating Officer, an Interim CIO, and a transformation strategist guiding senior leaders through the most disruptive technology shifts of their careers. Through her firm VWH Consulting, she works with executives navigating disruptive technology, with AI front and center right now, always keeping people first through change management and adoption.   Here's how PeacefulCare came to be. As Vicki worked with leader after leader, she kept hearing the same thing under the surface. They were exhausted trying to lead at work and care for someone at home at the same time. Often a parent. Sometimes a spouse, a sibling, or a child with complex needs. Nobody was talking about it, but it was costing them everything. So she started VWH Technology, LLC and built PeacefulCare for caregivers, drawing on a lifetime of caregiving experience that started in childhood when she helped her mother care for her grandmother and great aunt. Her great aunt passed away holding her hand.   She and her husband then cared for his brother for 26 years, and during a seven-year stretch she became the simultaneous primary caregiver for four additional loved ones, including one in Ohio she traveled to every three weeks. Based in Georgia, Vicki is a strategist, builder, speaker, and advocate who's lived every version of caregiving most families ever face.   About PeacefulCare.ai:   PeacefulCare is the AI-powered Caregiver Command Center for families managing the real work of care. Records, schedules, medications, documents, providers, appointments, patterns, risk signals, all in one place and intelligently connected. The platform lives under VWH Technology, LLC, the technology company founded by Dr. Vicki Wright Hamilton to bring AI-powered tools to the people who need them most. You can find it at PeacefulCare.ai.   The company was born from two things happening at once in Vicki's life. On one side, decades of caregiving. As a child, she helped her mother care for her grandmother and her great aunt, and her great aunt passed away holding her hand. As an adult, she and her husband cared for his brother for 26 years, and during a seven-year stretch she became the simultaneous primary caregiver for four additional loved ones while raising her kids and running her career. On the other side, her work through VWH Consulting, where she advises senior executives on disruptive technology and AI adoption with a people-first lens. Leader after leader kept telling her the same quiet truth.   They were trying to lead at work and care for someone at home, and the weight of doing both was breaking them. PeacefulCare was the answer to a question she kept hearing from both sides of her life. There was also one specific night that sharpened the mission. Vicki was sitting with her mother in the hospital, something shifted, she pushed, and her mother is alive today because a daughter who refused to go home saw something no system flagged and no algorithm caught. Technology can't replace the love and instinct of a caregiver. Technology should carry everything else.   What sets PeacefulCare apart is the AI analytics engine, and it's watching two people at once. The loved one and the caregiver. On the loved one's side, the platform tracks wellness patterns across medications, sleep, mood, vitals, appointments, and daily behaviors, and surfaces the small signals that usually go unnoticed until they turn into a hospital visit. Sudden changes in routine.   PeacefulCare's promise is simple and personal. You bring the love. PeacefulCare holds everything else.   The Prescription for Relief Summit:   Registration: https://summit.peacefulcare.ai   Hosted by: Dr. Vicki Wright Hamilton, founder of VWH Technology and creator of PeacefulCare.ai   Date: Saturday, July 25, 2026 Time: 10:00 a.m.–1:00 p.m. Eastern Time    Location:  Live online via Zoom    Audience: Family caregivers, veterans, family decision-makers, professionals, advocates, and others carrying significant personal or caregiving responsibilities.

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

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

If this resonated with you, here are additional resources: APPLY TO SHIFT: https://sidehustlepro.co/shiftIn this episode, I sat down with Jamila Wright, co-founder of Brooklyn Tea, to trace the full story of how she and her husband Ali turned tea dates into a business. Jamila walked me through leaving a career in education, emptying her retirement savings, and fighting a two year trademark battle before they ever opened their first location.We got into the real financial decisions behind building out that first shop, including an SBA loan that arrived late, putting up her own home as collateral, and the lesson she learned about the difference between being an investor and being an owner operator. Jamila also shared how a relationship with a fellow Brooklyn business owner led to their current Lewis Avenue location.From there we picked up with how Brooklyn Tea's verticals came together, the financial setbacks along the way including a six figure loan and a partnership that fell apart, and the moment she and Ali finally started paying themselves. Main TakeawaysBig opportunities often come from saying yes rather than a master plan, so be ready to rise to the moment when it arrives.Waiting on outside funding like an SBA loan can force you to dip into personal savings, so plan for delays before signing a lease or starting construction.Choosing between taking on debt or equity investors should depend on your long term goal, whether that is building a legacy brand or eventually selling it.Paying yourself is a milestone that often comes after years of sacrifice, so figuring out that number is part of building a sustainable business.Highlights Include(00:32) How Jamila and Ali went from dating over tea to business partners(08:12) The financial decisions behind opening the first Brooklyn Tea location(16:16) Why Jamila had to put up her Atlanta home as collateral for their SBA loan(19:38) Debt versus equity, and deciding what kind of business you want to build(24:13) The real lesson foot traffic taught them about their first location(29:45) How a relationship with Monique Greenwood led to their current Lewis Avenue location(37:33) Saying yes to wholesale and e-commerce almost by accident(47:39) Landing a licensing and franchising deal with an airport(52:12) The Saks Fifth Avenue partnership that fell apart(1:07:45) Paying themselves for the first time after two and a half yearsWatch & ListenSpotify: https://open.spotify.com/show/13qDj08lBR4ymzGhXIKy8tApple Podcasts: https://podcasts.apple.com/us/podcast/side-hustle-pro/id1126021323Social MediaWebsite: brooklyntea.comBrooklyn Tea Instagram: @brooklynteaJamila's Instagram: @jamilawright21 Hosted on Acast. See acast.com/privacy for more information.

Glenna Wright-Gallo is the Vice President of the Office of Strategic Research and Policy at Everway, a global neurotechnology software company. She has previously served as the Assistant Secretary for Special Education and Rehabilitative Services at the U.S. Department of Education. Glenna is also a person with a disability, a parent, and a former state Director of Special Education. Her extensive experience across educational roles at state and federal levels positions her as an influential figure in shaping inclusive education policies and practices.In this riveting episode of Think Inclusive, Tim Villegas speaks with Glenna Wright-Gallo about the pressing need to shift from a compliance-focused model to outcomes-focused education within special education systems. Glenna brings a wealth of knowledge from her extensive career in education advocacy, emphasizing the importance of aligning educational practices with the intent of IDEA (Individuals with Disabilities Education Act) to create systems that genuinely serve all learners. This episode delves into how educational structures, often hampered by outdated schedules and siloed learning environments, can truly realize the promise of inclusive education by focusing on system-wide solutions rather than ad-hoc heroics. Complete show notes and transcript: https://mcie.org/think-inclusive/shifting-focus-from-compliance-to-outcomes-in-education-with-glenna-wright-gallo-1336/

(Riverton, WY) – Riverton High School’s Tessa Kenyon joined the County 10 Podcast after returning from Washington D.C. where she attended the FCCLA National Convention. FCCLA or Family, Career and Community Leaders of America, turned into a passion for Tessa in 8th grade. Kenyon told us that it was instructor Kelli Gard who first inspired her to join the club. What started as a simple suggestion turned into a multi-year effort that culminated with the organization’s most prestigious honor in the nation’s capital. Kenyon was chosen as an FCCLA National Officer. Specifically, she’s National Vice President of Programs. To put the honor into a little perspective, there’s over 270,000 members in the country. Tessa was the only selection from the state. Wyoming’s last representative for a national officer position was when Wright’s Shelby Smith achieved it in 2021. Tessa and her team pose in front of the United States Capitol Kenyon knew that she was a candidate, but most don’t receive the high ranking designation. After the candidates received a letter revealing their fate, Tessa waited to open hers until she was in her hotel room surrounded by her mom, her sister and her advisor. “I literally got to ‘Dear Tessa Kenyon. Congratulations, you’ve been’ — and I couldn’t stop crying. I cried all my makeup off that I had put on that morning.” Tessa Kenyon holds her congratulatory letter. She’ll now work to represent those 270,000+ members. Next month she flies back across the country to Virginia for an FCCLA planning meeting. She’ll go to Disney’s Imagination Campus, help plan the 2027 National Convention and much more along the way. Kenyon speaks at the FCCLA National Conference Hear our full interview with Tessa by clicking the player below or wherever you get podcasts by searching for the County 10 Podcast! Tessa Kenyon, FCCLA National Officer Tessa Kenyon, FCCLA

Boomer, Pinder and Rhett discuss what's next for Shane Wright as reports suggest the Seattle Kraken are looking to move the former fourth-overall pick. The guys debate why things haven't worked out in Seattle, whether a fresh start with a new organization could unlock Wright's potential, and which teams make the most sense if he does hit the trade market. Could a change of scenery be exactly what Shane Wright needs?Video Links: https://youtu.be/cCuxm-Wyy78#nhl #nhlshorts #nhlplayoffs #nhlpredictions #nhlhockey #nhlpicks #stanleycup #stanleycupfinal #detroitredwings #seattlekraken CHECK OUT OUR STUFF ⬇️BARN BURNER MERCHhttps://nationgear.ca/collections/shirts/FlamesnationBARN BURNER SHORTS https://youtube.com/playlist?list=PLj_bcGtvvo-cW2DHEDZ6dEO5ePDmlhZc9&si=jo8iNGxT4ImhS2Y8

Leave an Amazon Rating or Review for my New York Times Bestselling book, Make Money Easy! Check out the full episode: https://lewishowes.com/podcast/navy-seal-mindset-for-living-your-best-life-with-chadd-wright/ Chadd Wright shares insights from SEAL training, emphasizing the importance of breaking challenges into smaller, manageable pieces to avoid feeling overwhelmed. He discusses the significance of focusing on the present moment, using examples from SEAL training, ultra-running, and his business ventures. Chadd highlights the concept of the "steady state," a mental space where pain remains constant, but the mind simplifies, enabling a primal focus on the task at hand. Sign up for the Greatness newsletter! Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of Fabulous Folklore Presents, I chat to Dr Andrea Wright about the fairy tale film as a concept, Jim Henson's career in film and television, the influence of the Muppets on fairy tales on screen, and what Jareth would have made of Miss Piggy! Andrea Wright is a Senior Lecturer in Teaching and Learning Development at Edge Hill University. She leads the Professional Standards Framework CPD Scheme, teaches on the PGCert Teaching in Higher Education and is involved in staff development across the University. Her discipline expertise is in screen studies and fantasy/fairy tales, New Zealand cinema, and British television costume dramas are central to her research interests. She has written on production design, landscape, gender representation, and national identity. Recent publications include chapters on the New Zealand short films Possum and Nature's Way for the collection Haunted Soundtracks, and The Frankenstein Chronicles and The Alienist for the collection Diagnosing History: Medicine in Television Costume Dramas. Andrea is also the author of the monograph The Fairy Tales of Jim Henson: Keeping the Best Place by the Fire. Buy a copy of The Fairy Tales of Jim Henson: Keeping the best place by the fire here, using the code EVENT30 to get a discount: https://manchesteruniversitypress.co.uk/9781526166111/ Contact Andrea at wrighta@edgehill.ac.uk Get your free guide to home protection the folklore way here: https://www.icysedgwick.com/fab-folklore/ Become a member of the Fabulous Folklore Family for bonus episodes and articles at https://patreon.com/bePatron?u=2380595 Get weekly articles and bonus content at Substack: https://fabulousfolklore.substack.com/ Buy Icy a coffee or sign up for bonus episodes at: https://ko-fi.com/icysedgwick Find the Fabulous Folklore Bookshop, Icy's social media links, and other useful bits at: https://icysedgwick.com/start-here

In this episode of Beyond the Campaign, Lindsey Patrick Wright shares her inspiring journey from career librarian to Tennessee State Senate candidate. She discusses why public libraries are essential to strong communities, the power of grassroots activism, and her commitment to protecting human rights in a challenging political landscape. The conversation explores civic engagement, public service, and the importance of standing up for equitable policies that strengthen communities across Tennessee and beyond.What We're Talking About...Lindsey Patrick Wright's journey from librarian to Tennessee State Senate candidateThe vital role of public libraries in strengthening communities and protecting democracyThe impact of book banning, censorship, and intellectual freedom in schoolsGrassroots campaigning strategies that increase voter engagement and civic participationHow social media shapes political campaigns, public discourse, and electionsWhy community representation matters in state and local governmentStrategies for flipping political seats and building momentum in Tennessee electionsHow national political issues influence local races and voter prioritiesChapters00:00 Introduction to Lindsey Patrick Wright and her background02:00 Lindsey's journey from theater to librarianship03:52 The multifaceted role of public libraries09:03 Community activism and fighting book bans12:50 The rise of Moms for Liberty and their impact16:11 Lindsay's personal story and coming out as LGBTQ+19:50 Deciding to run for office and the low bar for candidates26:00 Gerrymandering and the fight to flip Tennessee seats28:59 Engaging young voters and grassroots efforts33:01 The role of social media in modern campaigning36:10 How to support Lindsey's campaign and get involvedLinks MentionedLindsey Patrick Wright's campaign website: https://www.lindseyfortn.comInstagram: @‌lindseypatrickwright

What happens when church leaders acknowledge a serious failure, but meaningful action never follows?In this follow-up to “When Church Accountability Breaks Down,” we discuss the strong response from listeners and examine who should act when internal leadership fails. We explore the responsibilities of deacons, congregations, ministry leaders, former law-enforcement officers, and outside authorities when concerns involving alleged misconduct, financial oversight, safety, or possible legal violations arise.We also discuss 501(c)(3) accountability, ministry safety policies, the obligation to investigate concerns, and why institutional silence can damage trust far beyond a single congregation. This episode discusses claims and concerns as described by the hosts and does not identify the church or individuals involved.Where should internal church discipline end and outside accountability begin? Share your opinion in the comments, subscribe to MX3 Podcast, and send this episode to someone who believes accountability should apply to every institution.At MX3 Podcast, we discuss money, motivation, and relevant events.Visit us at www.mx3.vipSupport the showMX3 Podcast on Youtubewww.youtube.com/@mx3podcastContact MX3 PodcastTweet us: @mx3podcastEmail us: info@mx3.vipLinkedIn: https://www.linkedin.com/in/michael-w-wright-9397b23a/Thanks for listening & keep on living your life the Wright way!

The gap between Beijing's stated growth rates and actual economic performance is widening considerably, says expert Synopsis: Every third Friday of the month, The Straits Times gets its US Bureau Chief to analyse the hottest political and trending talking points. In this episode, US Bureau Chief Bhagyashree Garekar chats with Dr Logan Wright, an expert on the Chinese economy. He is based in Washington, DC, after living and working in Beijing and Hong Kong for over two decades. Wright is a partner at Rhodium Group, a US research and advisory group. He leads the firm’s China markets research work. He is also a senior associate of the trustee chair in Chinese Business and Economics at the Center for Strategic and International Studies (CSIS). His book Broken China: How the Economic Miracle Shattered and What it Means for the World hits the stores in September 2026. In this episode, he points out that most analysts treat the Chinese economy differently from other economies. “They tend to look at the Chinese system and say this is a different political system, it produces outputs that are long-term plans. Therefore, we filter incoming data in terms of how China is doing based on its long-term plans and its declared goals. From a financial system perspective, it looks entirely different,” he says. He also sketches out what strikes him as the most troubling aspect of the Chinese economy today. Highlights (click/tap above): 1:20 Analysis of China's actual growth vs. official reports 2:50 Is that a minority opinion? 5:00 The most troubling aspects of the Chinese economy 9:10 Evaluating the quality of Chinese economic data 13:00 AI's impact on returns in the Chinese economy 17:00 When will the property sector rebound? 22:00 Will policy efforts to boost domestic consumption succeed? 25:00 Will China’s low birth rates, high death rates have a large impact on growth? 27:00 The worsening problem of excess industrial capacity 29:10 Reasons South-east Asia must pay attention to China Read Bhagyashree Garekar’s articles: https://str.sg/whNo Bhagyashree Garekar’s LinkedIn: https://str.sg/gD6E Sign up for ST’s weekly Asian Insider newsletter: https://str.sg/sfpz Host: Bhagyashree Garekar (bhagya@sph.com.sg) Produced and edited by: Fa’izah Sani Executive producer: Ernest Luis Follow Asian Insider Podcast on Fridays here: Channel: https://str.sg/JWa7 Apple Podcasts: https://str.sg/JWa8 Spotify: https://str.sg/JWaX Feedback to: podcast@sph.com.sg --- Follow more ST podcast channels: All-in-one ST Podcasts channel: https://str.sg/wvz7 Get more updates: http://str.sg/stpodcasts Asian Insider YouTube: https://str.sg/rF3qR --- Get The Straits Times app, which has a dedicated podcast player section: The App Store: https://str.sg/icyB Google Play: https://str.sg/icyX --- #STAsianInsiderSee omnystudio.com/listener for privacy information.

The gap between Beijing's stated growth rates and actual economic performance is widening considerably, says expert Synopsis: Every third Friday of the month, The Straits Times gets its US Bureau Chief to analyse the hottest political and trending talking points. In this episode, US Bureau Chief Bhagyashree Garekar chats with Dr Logan Wright, an expert on the Chinese economy. He is based in Washington, DC, after living and working in Beijing and Hong Kong for over two decades. Wright is a partner at Rhodium Group, a US research and advisory group. He leads the firm’s China markets research work. He is also a senior associate of the trustee chair in Chinese Business and Economics at the Center for Strategic and International Studies (CSIS). His book Broken China: How the Economic Miracle Shattered and What it Means for the World hits the stores in September 2026. In this episode, he points out that most analysts treat the Chinese economy differently from other economies. “They tend to look at the Chinese system and say this is a different political system, it produces outputs that are long-term plans. Therefore, we filter incoming data in terms of how China is doing based on its long-term plans and its declared goals. From a financial system perspective, it looks entirely different,” he says. He also sketches out what strikes him as the most troubling aspect of the Chinese economy today. Highlights (click/tap above): 1:20 Analysis of China's actual growth vs. official reports 2:50 Is that a minority opinion? 5:00 The most troubling aspects of the Chinese economy 9:10 Evaluating the quality of Chinese economic data 13:00 AI's impact on returns in the Chinese economy 17:00 When will the property sector rebound? 22:00 Will policy efforts to boost domestic consumption succeed? 25:00 Will China’s low birth rates, high death rates have a large impact on growth? 27:00 The worsening problem of excess industrial capacity 29:10 Reasons South-east Asia must pay attention to China Read Bhagyashree Garekar’s articles: https://str.sg/whNo Bhagyashree Garekar’s LinkedIn: https://str.sg/gD6E Sign up for ST’s weekly Asian Insider newsletter: https://str.sg/sfpz Host: Bhagyashree Garekar (bhagya@sph.com.sg) Produced and edited by: Fa’izah Sani Executive producer: Ernest Luis Follow Asian Insider Podcast on Fridays here: Channel: https://str.sg/JWa7 Apple Podcasts: https://str.sg/JWa8 Spotify: https://str.sg/JWaX Feedback to: podcast@sph.com.sg --- Follow more ST podcast channels: All-in-one ST Podcasts channel: https://str.sg/wvz7 Get more updates: http://str.sg/stpodcasts Asian Insider YouTube: https://str.sg/rF3qR --- Get The Straits Times app, which has a dedicated podcast player section: The App Store: https://str.sg/icyB Google Play: https://str.sg/icyX --- #STAsianInsiderSee omnystudio.com/listener for privacy information.

July 16, 2026 - Lacey Wright joined Byers & Co to talk about the 2026 Warrensburg Corn Festival. Listen to the podcast now!See omnystudio.com/listener for privacy information.

Chicago Bears right tackle Darnell Wright finally reached his potential last season and became one of the NFL's best right tackles during an All-Pro season. Here's why Wright will be the No. 8 most-important Bear for the 2026 season.Become a supporter of this podcast: https://www.spreaker.com/podcast/shaw-local-s-bears-insider-podcast--3098936/support.

This is the official VIC 4 VETS Honor Roll, highlighting our Honored Veterans SUBMITTED BY: The Soldiers Memorial Archives St. Louis, MO JOHN WILLIAM WRIGHT Lance Corporal United States Marine Corp Company K, 3rd Battalion, 4th Marine Regiment, 3rd Marine Division VIETNAM Born: 11-10-1946 Died: 09-02-1967 Died of artillery/rocket wounds in Quang Tri, South Vietnam; Served as a machine gunner; Awarded ★ Purple Heart ★ Combat Action Ribbon ★ National Defense Service Medal ★ Vietnam Campaign Medal ★ Vietnam Service Medal ★ Marine Corps Presidential Unit Citation ★ Vietnam Gallantry Cross Parents were Mr. and Mrs. Leonard Wright; John William Wright is buried at Valhalla Cemetery located at 7600 St. Charles Rock Road, St. Louis, MO 63133 John William Wright was serving his country during the Vietnam War when he gave his all in the line of duty. He had enlisted in the United States Marine Corps. Wright had the rank of Lance Corporal. His military occupation or specialty was Machine Gunner. He was born on 10 November 1946. According to our records Missouri was his home or enlistment state and St Louis county has been included within the archival record. We have St Louis listed as his city. During his service in the Vietnam War, Marine Corps Lance Corporal Wright experienced a traumatic event which ultimately resulted in loss of life on 2 September 1967. Recorded circumstances attributed to: Hostile, died of wounds, Artillery, rocket, or mortar. Incident location: Quang Tri Province, South Vietnam. ________________________________________________________________ Today's VIC 4 VETS Honor Roll Inductee, Honored Veteran on NewsTalkSTL.With support from our friends at: Alamo Military Collectables, Gemini Wealth Group H.E.R.O.E.S. CARE, Inc. Michel's Funeral Home and Freddie's Market See omnystudio.com/listener for privacy information.

Andy is joined by Erika Wright (Oklahoma Appleseed & Oklahoma Rural Schools Coalition) to discuss SQ844 & SQ846 that will be on the August 25th ballot. What seems complicated on the surface may in fact be quite harmful to local government and school board budgets!

Adam Stoker talks with Will Wright, managing partner of UK-based Destination Core, about the content-centric, owned-media-first website platform they've quietly built together. They dig into why traditional destination websites function as glorified directories, how their first joint client, Play Golf Myrtle Beach, put the concept to the test, and why the best DMOs now win by answering travelers' questions and inspiring them, rather than just chasing bottom-of-funnel metrics. Subscribe to our ⁠⁠⁠⁠newsletter⁠⁠⁠⁠! The ⁠⁠⁠⁠Destination Marketing Podcast⁠⁠⁠⁠ is a part of the ⁠⁠⁠⁠Destination Marketing Podcast Network⁠⁠⁠⁠. It is hosted by Adam Stoker and produced by Brand Revolt. If you are interested in any of Brand Revolt's services, please email ⁠⁠⁠⁠adam@thebrandrevolt.com⁠⁠⁠⁠ or visit ⁠⁠⁠⁠www.thebrandrevolt.com⁠⁠⁠⁠.To learn more about the Destination Marketing Podcast network and to listen to our other shows, please visit ⁠⁠⁠⁠www.thedmpn.com⁠⁠⁠⁠. If you are interested in joining the network, please email ⁠⁠⁠⁠adam@thebrandrevolt.com⁠⁠⁠⁠.

The Miami Hurricanes score a huge win on the recruiting trail with elite quarterback Israel Abrams, sparking buzz about their 2027 class's championship potential. Can Mario Cristobal's strategy and top prospects like DOnte Wright, Nick Lennear, and Jaiden Bryant deliver an edge within the college football arms race? Brian Smith breaks down Miami's impressive class balance, detailing the depth chart impact of versatile signings across the trenches and skill positions. The conversation highlights under-the-radar talents such as defensive end Jayvon Dawson and tight end DeMarcus DeRoche, questions about how Miami plans to attack recruiting class sizes and player development in the new five-for-five eligibility era, and why the Canes can maximize hidden gems like Josh Johnson and DeMarco Jenkins. Miami's recruiting momentum and their aggressive pursuit of top prospects position the Hurricanes as a program to watch in college football's NIL-driven era. Support us by supporting our sponsors! Indeed Listeners of this show get a $75 Sponsored Job Credit to help give your job the premium placement it deserves at http://Indeed.com/podcast FanDuel Today's episode is brought to you by FanDuel. Right now new customers can bet just five dollars and get one-hundred and fifty dollars in bonus bets if your first bet wins. Visit https://FANDUEL.COM to get started — Play Your Game. FANDUEL DISCLAIMER: 21+ in select states. First online real money wager only. Bonus issued as nonwithdrawable free bets that expire in 14 days. Restrictions apply. See terms at sportsbook.fanduel.com. Gambling Problem? Call 1-800-GAMBLER or visit FanDuel.com/RG (CO, IA, MD, MI, NJ, PA, IL, VA, WV), 1-800-NEXT-STEP or text NEXTSTEP to 53342 (AZ), 1-888-789-7777 or visit ccpg.org/chat (CT), 1-800-9-WITH-IT (IN), 1-800-522-4700 (WY, KS) or visit ksgamblinghelp.com (KS), 1-877-770-STOP (LA), 1-877-8-HOPENY or text HOPENY (467369) (NY), TN REDLINE 1-800-889-9789 (TN) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Part 2 of my conversation with Pam Oken-Wright explores reciprocal provocation, flow, small group work, and the courage to embrace uncertainty alongside children. We close with a heartfelt tribute to the remarkable Lella Gandini and the lasting legacy she leaves for educators around the world.Visit Pam's website at⁠ https://pokenwright.com/blog/through-the-kaleidoscope-reframing-challenges-in-early-childhood-education-a-new-course-in-the-studio-for-playful-inquiry/

Fabian Alefeld interviews certified prosthetist/orthotist and EastPoint Prosthetics VP Brent Wright about his career path into O&P, his shift from being anti-digital to adopting scanning and additive manufacturing, and the impact on patient care and global access. Wright describes traditional fabrication workflows (casting, plaster positives, vacuum forming thermoplastics for orthoses, and carbon fiber/resin layups for prostheses) as artistic but time-consuming, hazardous, and lacking records. His digital journey accelerated after a Guatemala trip with Life Enabled highlighted the need to scale care; he focused on scanning, digital modification, and later powder-bed fusion, moving toward SLS with materials like PK5000 and TPU. He emphasizes pressure casting for prosthetic sockets, the value of digital records for insurance, and how AM can change socket “dynamics” to improve comfort and heal wounds. The discussion also covers RADii's data-driven fitting approach, Life Enabled's mix of traditional and 3D-printed solutions (including pediatric feet), modular “kit” concepts for developing regions, and barriers to sensors/actuators in the US due to reimbursement.02:33 Brent Origin Story09:30 Why Go Digital11:17 Scaling Global Access17:32 Traditional O&P Workflow20:02 Casting And Fabrication Steps24:07 Digital Workflow And Scanning33:22 Benefits Of Digital Records36:36 Flexible Liner Heals Wound40:47 RADii Data Meets Craft46:06 Life Enabled Model01:01:50 Democratizing via Manufacturing01:08:01 Sensors vs Simplicity

In this episode IOWN Global Forum board members Chris Wright (Chief Technology Officer and Senior Vice President of Global Engineering, Red Hat) and Jefferson Wang (Chief Strategy & Innovation Officer, Cloud, Accenture) talk through the accelerating shift towards photonics-based networks and how this next-generation technology can help unlock the full potential of the AI economy. Replacing electrical-based connectivity with optics promises to drastically increase processing speeds, reduce latency, and lower power consumption for high-demand AI, cloud computing, and financial networks.

Bon Jovi is back onstage after years of uncertainty surrounding Jon Bon Jovi's voice, recovery, and future as a live performer.In this episode of the MX3 Podcast, we discuss Bon Jovi's return to touring, the early history of the band, the unlikely radio breakthrough of “Runaway,” and the stories behind classics such as “Livin' on a Prayer,” “Wanted Dead or Alive,” “Bad Medicine,” and “Blaze of Glory.”We also explore how Jon Bon Jovi assembled the original lineup, Richie Sambora's near connection to KISS, Dave “Snake” Sabo's role in the story, the exhausting tours that nearly broke the band apart, and the remarkable comeback that followed. Plus, we share memories from seeing Bon Jovi live and debate whether the group is still truly Bon Jovi without Richie Sambora.MX3 Podcast discusses money, motivation, and relevant events with honest conversation, personal stories, and a little humor along the way.What is your favorite Bon Jovi song, and do you still consider the current lineup the real Bon Jovi? Leave your answer in the comments.

The Chicago Bears are getting national attention heading into the 2026 season — but not all of it is praise. On today's episode of Chicago Bears Central, Haize breaks down the latest leaguewide rankings and reactions around Caleb Williams, Darnell Wright, Colston Loveland and Kyler Gordon.

Our pilgrim journey through life need not be one of constant sorrow, but from time to time our earthly sojourn will pass through a vale of tears. And that's when Jesus weeps with us.

You might remember Katryn from episode 292, where we dove deep into the behavioral blueprint for inclusion. Well, a lot can happen in a year—or in our current case, since the wild ride of the 2026 election—and the DEI landscape is shifting beneath our feet. I'll admit, when I first started this work ten years ago, I thought we could just shout from the rooftops that inclusion matters and everyone would just magically get it. But as we look at the headlines today, it's clear that "shiny object syndrome" has left us with a lot of noise and not enough real, systemic change. Katryn and I sit down to unpack what global leaders are actually doing right now to push past the performative and get to the heart of what makes workplaces genuinely fair. Key Themes from the Conversation Moving from Noise to Systemic Change. Organizations frequently focus on highly public, performative declarations of inclusivity rather than restructuring the underlying processes that perpetuate bias. "Organizations were doing a lot of the shiny stuff... doing what we would call noisy things, right? Proclaiming, saying, being public... but obviously that not necessarily translating to real-world change." — Katryn Wright The Problem with Unconscious Bias Training. Treating broad, one-size-fits-all training modules as a standalone solution is ineffective and can create artificial metrics that trigger cultural backlash. "An awful amount of money was spent on something that the science shows is... ineffective at best, counterproductive at worst." — Katryn Wright Inclusion as an Aspiration, Not a Default Value. Framing inclusion as a predefined company value mistakenly implies that the work is already complete, whereas framing it as an ongoing aspiration invites employees to actively participate in closing the gap. "When we talk about inclusion as a value, it is not as effective as when we talk about inclusion as an aspirational goal... it suggests that we've been missing a trick to be bringing people on as much as we can." — Katryn Wright Precision and Data Science in Workplace Fairness. True progress requires identifying the exact inflection points in employee experiences—like hiring, promotion, and retention stages—where disparities emerge, and applying targeted behavioral interventions. "Let's go and be as precise as possible about changing behavior in that exact situation... when we are able to be as precise as possible about which specific behaviors need to change, we can get to those outcomes." — Katryn Wright Actionable Takeaway for Listeners Stop trying to de-bias your entire team all at once with sweeping declarations. Instead, pick one specific process in your daily workflow—whether it's how you audit resumes, run performance reviews, or distribute project assignments—and analyze the data to find where the equity gaps lie. Designing small, targeted interventions at precise moments is how real cultural evolution happens. Follow Katryn at https://www.morethannow.co.uk/

Description Written By Fable/Max: Robert Wright interviewed Geoffrey Hinton in 1983 and, by his own account, got the story 180 degrees wrong. Forty years later Hinton is the "Godfather of AI," two of the three godfathers are frightened of their own creation, and Wright has written The God Test to figure out what he missed and what's coming. We talk about how these machines evolved rather than being programmed - nobody fully understands them, including the people who build them - why "fancy autocomplete" was always wrong, the best case (an AI caught a radiologist's error in his cancer MRI), the worst case (a bioweapon that incubates silently for six weeks), why racing China to superintelligence may cause the war it's meant to prevent, and whether unplugging a machine could ever be murder. Plus an experiment of my own: I put a legal dispute in front of the AI and handed the laptop to the other side. 0:00 Intro - Robert Wright and The God Test 2:13 A 27-ton computer and a buried headline 4:11 Interviewing the Godfather of AI in 1983 - and missing it 10:15 Not programmed - evolved 17:27 The "fancy autocomplete" myth 24:17 Dukakis, Reagan, and how minds file words 35:49 Best case: medicine, education, and an MRI story 42:38 Worst case: bioweapons, jailbreaks, designer babies 48:51 An AI that believes what the Ayatollah believes 50:30 The China race - overdone and dangerous? 57:33 Nazis, the Hamas charter, and bombing over AI 59:46 Authoritarianism through the back door 1:03:35 Sociopaths, the ship of Theseus, and machine morality 1:14:34 Is it sentient? Should you be nice to it? 1:21:54 AI as judge: my legal experiment 1:26:20 The God Test

Is Waffle House coming to Hammond, Indiana; Tom talks Chicago Bears and more on a recent panel with other state leaders and IN Governor Mike Braun in attendance; another business relocates to Hammond from Illinois; Belgium's reaction to beating the USA in the World Cup goes viral; Trump's latest misspeak; author and former EU and United Nations diplomat Richard Fassam-Wright calls in from London and talks with Tom and Kevin about the Russia-Ukraine war, meeting Vladimir Putin almost 30 years ago, his latest book "The Triangle of Death", and more.

Mike Zakarian sits down with Nathaniel Wright fresh off elimination. Nathaniel breaks down his submission origin story, how he found his footing on camera, and what he learned from Duo Week. He weighs in on the PPR Tyler comeback and Toxic Tower politics, gives an honest critique of Debate Week, and closes with his acting and improv background.Follow Mike Zakarian over on ⁠⁠⁠⁠⁠⁠ @NBABIT ⁠⁠⁠⁠⁠⁠. ⁠⁠⁠⁠⁠⁠Subscribe to About The Touts.⁠⁠⁠⁠⁠⁠

Coldwired Podcast (Come and say hello facebook.com/ColdwiredMusic). Live every Tuesday 8PM (UK)! www.twitch.tv/coldwired July 2026 Selection. Tracklisting: [00:00] 01. Maze 28 - Tell Me Again (Extended Mix) [Anjunadeep Explorations] [04:19] 02. UnbrokenOne - Absolution [Stripped Recordings] [09:23] 03. Matty Wright - Fond Memories [AFFILIATE] [15:44] 04. Jaydee - Plastic Dreams (Kebin van Reeken Unofficial Remix) [Bootleg] [20:49] 05. Jerome Isma-Ae - Encounter (Extended Discotheque Mix) [Jee Productions] [24:53] 06. Dominion - 11 Hours (James Harcourt) [Lost Language] [29:58] 07. Last Rhythm - Last Rhythm (Framewerk Anthemic Rewerk) [Bandcamp] [34:30] 08. Gorge - Loophole (Extended Mix) [Global Underground] [38:45] 09. PlayKate - Missing Station [White] [42:59] 10. Unknown Artist - Closer [Bandcamp] [46:09] 11. Fred Baker, Mr. Sam - Forever Waiting (Jamie Baggotts Extended Remix) [Black Hole Recordings] [51:06] 12. deadmau5 - Not Exactly (Rinzen Remix Extended) [mau5trap] [54:58] 13. Midland - All Crews [GRD LTD] [1:01:11] 14. Roman Smith, Christina Monoxrom - X-Night (UNWA Remix) [Inspired Virtu] [1:03:05] 15. Riotbot - Cloud Step [SehNebel Records] [1:05:02] 16. Bart van Wissen - Distant Region [Extrema] ***Defrosted from 2003*** [1:07:58] 17. Above and Beyond - Major Drop (Extended Mix) [Anjunabeats] [1:11:58] 18. Hernan Cattaneo and Marc Romboy - The insanity of infinty (Frank Sonic and Drumcomplex Remix) [Bandcamp] [1:16:33] 19. Binary Finary - 1998 (Dan Graham Bootleg) [Bootleg] [1:23:07] 20. Ovnimoon - Freedom Frequency (Enlusion Remix) [Forescape Digital] [1:29:17] 21. Nomas - Residual Self [JOOF Recordings] ***Gold Star Track*** [1:35:24] 22. Jirah, E11even, Stranger Than Fiction - Let It All Go (DnB Mix) [Athereal Music]

"The opposite is always the medicine. You people-please to others — so how do you people-please to you?" — Kari Brunson WrightThere's a particular kind of exhaustion that comes from bending yourself into whatever shape a room needs you to be. Kari Brunson Wright knows it well — from a ballet stage, to a restaurant line, to running her own businesses. It took three full reinventions before she learned how to stop.In this episode, Kari shares the honest story of walking away from a decade-long career as a professional ballerina, building and eventually selling a cafe and an ice cream company, and becoming a Psycho-Spiritual Leadership Coach. This is real conversation and authentic storytelling about identity, boundaries, and the whispers that show up long before the big changes do — the kind of personal growth for women that doesn't come with a tidy bow.If you've ever bent yourself into a shape that wasn't really yours, this one's for you. New episodes every Thursday on all major podcast platforms.Connect with Heather: WebsiteFacebookInstagramLinkedInYouTubeTimestamps00:00 — Introduction — Heather welcomes Kari Brunson Wright6:02 — Kari's decade as a professional ballerina and the injury that led her to walk away12:52 — From the ballet stage to the restaurant line — falling into food16:20 — Building a cafe and an ice cream company, and the decision to finally sell her shares19:43 — "I want to be you" — the moment coaching became the next chapter29:48 — Boundaries, energy, and what it means to "keep your shape"About Kari Brunson WrightKari Brunson Wright is a psycho-spiritual leadership coach and regenerative business consultant who works with founders, executives, and leaders navigating the gap between who they've become and how they're actually living. Her work centers on alignment, integrity, and self-trust — helping people make decisions they can actually stand behind. She brings fifteen years of experience working alongside people through growth, pressure, and change, plus her own background as a co-founder of multiple businesses. Kari writes the Substack newsletter The Recipe for Being Well, and lives in Seattle, Washington, with her husband, their two kids, and a Great Pyrenees/Lab mix puppy named Bean.Connect with Kari Brunson WrightInstagram Website LinkedInSubstack Support the show

It's new show day! Stephanie Ruff joins us to tell us about her new show on the Horse Radio Network, the Feeding Horses Nutrition Podcast. Also, Glenn is co-hosting a brand new non-horse show called “Did I Hear That Right?” His co-host Scott Johnson stops by to talk about this new show that answers the question “What's the one unusual thing you've done that no one else you know has?” Listen in….HORSES IN THE MORNING Episode 3991– Show Notes and Links:Hosts: Jamie Jennings of Flyover Farm and Glenn the GeekJamie and Glenn's Amazon StoreSpecial Co-Host: Lisa WysockyTitle Sponsor: ChewyPic Credit: NAGuest: Stephanie Ruff, host of Feeding Horses PodcastGuest: Scott Johnson, co-host of Did I Hear That Right?Link: 4000th Episode Facebook InviteSponsor: Care CreditSponsor: Spalding Labs Fly Predators Coupon: HRN10 for 10% off your first order.Additional support for this podcast provided by: Equine Network and Listeners Like YouTime Stamps: 03:08 - 4,000th episode Zoom plans05:56 - Daily Whinnies10:44 - Cat & Wright movie update & podcast14:26 - Colby's Army & jumper gelding antics19:50 - Scott Johnson joins; Did I Hear That Right?33:53 - Stephanie Ruff's “Feeding Horses” podcast46:02 - Equine history, Lisa's books & Glenn's fiber upgrade (pre–post show)

It's new show day! Stephanie Ruff joins us to tell us about her new show on the Horse Radio Network, the Feeding Horses Nutrition Podcast. Also, Glenn is co-hosting a brand new non-horse show called “Did I Hear That Right?” His co-host Scott Johnson stops by to talk about this new show that answers the question “What's the one unusual thing you've done that no one else you know has?” Listen in….HORSES IN THE MORNING Episode 3991– Show Notes and Links:Hosts: Jamie Jennings of Flyover Farm and Glenn the GeekJamie and Glenn's Amazon StoreSpecial Co-Host: Lisa WysockyTitle Sponsor: ChewyPic Credit: NAGuest: Stephanie Ruff, host of Feeding Horses PodcastGuest: Scott Johnson, co-host of Did I Hear That Right?Link: 4000th Episode Facebook InviteSponsor: Care CreditSponsor: Spalding Labs Fly Predators Coupon: HRN10 for 10% off your first order.Additional support for this podcast provided by: Equine Network and Listeners Like YouTime Stamps: 03:08 - 4,000th episode Zoom plans05:56 - Daily Whinnies10:44 - Cat & Wright movie update & podcast14:26 - Colby's Army & jumper gelding antics19:50 - Scott Johnson joins; Did I Hear That Right?33:53 - Stephanie Ruff's “Feeding Horses” podcast46:02 - Equine history, Lisa's books & Glenn's fiber upgrade (pre–post show)

Quentin Wright sits down with Shane Sparks to tell some Stories from the Resilite

In this listener-inspired mini episode of Wonderland on Points, we're heading to Dayton, Ohio, to uncover one of the Midwest's most underrated destinations. From its rich aviation history and connections to the Wright brothers to fascinating museums, beautiful parks, and family-friendly attractions, Dayton has far more to offer than many travelers realize. We also share recommendations for where to stay, local restaurants worth seeking out, and hidden gems submitted by one of our listeners. If you're looking for an easy road trip destination filled with history, great food, and unique experiences, this episode will give you plenty of inspiration for your next adventure.Find Us On Online:Girl's Trip Interest Form (April 7-10, 2027)Summer Road Trip Submissions ARE BACK!Sign Up for the Y! Wonder Travel NewsletterWonderland on Points Youtube ChannelMary Ellen | JoFacebook GroupAffiliate Links:Rakuten- Mary Ellen (Get 5000 AMEX or Bilt POINTS)Rakuten- Joanna (Get 5000 AMEX or Bilt POINTS)Comfrt.com 15% OFFSeats.AeroCardpointersHalara (use code "Wonderland" for 10% off)Our Favorite Credit CardsOur Favorite Travel NecessitiesWe receive a small commission when you choose to use any of our links to purchase your products or apply for your cards! We SO appreciate when you choose to give back to the podcast in this way!

CheckoutThe God Centered Concept Academy Training Community to learn what growth in Christ ishttps://api.tuvu.com/redirectGroup/6a2ac0e2c9f728027338244cCheck out this link to view Kingdom Cross Roads on TV.https://jesussaid.tv/?affiliate=tswright_gccTo get a copy of our new book "Embracing the Truth" or to have TS Wright speak at your event or conference or if you simply want spiritual or life coaching or just a consultation visit:www.tswrightspeaks.comVisit our website to learn more about The God Centered Concept. The God Centered Concept is designed to bring real discipleship and spreading the Gospel to help spark the Great Harvest, a revival in this generation.www.godcenteredconcept.comKingdom Cross Roads Podcast is a part of The God Centered Concept.In this episode of Kingdom Cross Roads Podcast, host T.S. Wright welcomes back Joshua Spatha for a deep biblical conversation on Moses, Pharaoh, the Exodus, and the wilderness journey of Israel.The discussion begins with Moses at the burning bush, where God confronts Moses' reluctance and calls him into a divine assignment. From there, the conversation moves into Egypt, where Moses stands before Pharaoh in what becomes a direct confrontation between the God of Israel and the false authority of Pharaoh.T.S. and Joshua unpack the meaning of the ten plagues, the hardening of Pharaoh's heart, and why God used this confrontation to reveal His glory, power, and authority. They also address difficult theological questions about suffering, divine justice, God's authority over life and death, and why believers must recognize that God's ways are higher than man's ways.The second half of the episode focuses on Israel's wilderness journey. T.S. and Joshua discuss the Red Sea, manna, spiritual amnesia, Israel's repeated grumbling, and the importance of building memorials of remembrance when God proves Himself faithful. They connect Israel's wilderness testing to the believer's own walk of faith, showing how trials can produce endurance, spiritual maturity, and deeper trust in Christ.This episode is a strong reminder that God never loses, His authority is absolute, and His faithfulness remains even when His people struggle to trust Him.Key Topics CoveredMoses and the burning bushMoses' reluctance and God's callGod versus PharaohThe ten plagues of EgyptThe hardening of Pharaoh's heartGod's authority over life and deathWhy God allows suffering and hardshipIsrael crossing the Red SeaThe wilderness journeyManna, grumbling, and spiritual amnesiaJoshua and Caleb's faithThe danger of forgetting God's faithfulnessMemorials of remembranceTrials, endurance, and spiritual maturityEmbracing the cross instead of pursuing comfortGuest InformationJoshua Spatha is the author of Mere Spirituality and can be found at mperspective.org. His book is also available on Amazon.KeywordsMoses and Pharaoh, God versus Pharaoh, Exodus Bible study, Moses in Egypt, ten plagues of Egypt, hardening of Pharaoh's heart, Israelites in the wilderness, Red Sea crossing, wilderness journey Bible, Joshua and Caleb, spiritual amnesia, remembering God's faithfulness, biblical suffering, divine justice, God's authority, Kingdom Cross Roads Podcast, TS Wright, Joshua Spatha, Mere Spirituality, Embracing the Truth, Christian podcast, Bible teaching podcast, Torah discussion, Exodus Leviticus Numbers Deuteronomy, God Center Concept Academy

Get up to $200 off Square hardware when you sign up at square.com/go/Wright! #squarepod #ad All lines provided by Hard Rock Bet. Nick Wright breaks down the USMNT’s 4-1 loss to Belgium and being knocked out of the World Cup. Then, Nick weighs in on the impact this World Cup has had on soccer in America. Later, Nick dives into Brazil being upset by Haaland and Norway, England surviving in The Azteca against Mexico, and Cristiano Ronaldo’s final World Cup appearance. Finally, Nick and Damonza answer your questions. #VolumeSee omnystudio.com/listener for privacy information.

Tell all the truth but tell it slant—Success in Circuit liesToo bright for our infirm DelightThe Truth's superb surpriseAs Lightning to the Children easedWith explanation kindThe Truth must dazzle graduallyOr every man be blind—–Emily Dickinson

A chef and cookbook author takes a look at idioms that are shared across diverse languages. Then the head of the Rock & Roll Hall of Fame and Museum updates us on what's happening this summer at Cleveland's top attraction. And the late historian David McCullough reflects on the Wright brothers and how their dream changed the world. For more information on Travel with Rick Steves - including episode descriptions, program archives and related details - visit www.ricksteves.com.