Podcasts about Robertson

Martin heroically steps in when Jase's plan to fulfill Miss Kay's urgent request suddenly falls apart. Jase turns a chaotic weekend of surprise houseguests, strange boyfriends, and overflowing trash into a bigger conversation about what genuine faith looks like in everyday life. The guys compare Abraham and Rahab, showing how two deeply flawed people can act with courage because they trust God.  In this episode: James 2-3; Joshua 2; Genesis 12-22; Matthew 1; Romans 9; 1 Corinthians 1; Hebrews 11; Hebrews 13:12-16 “Unashamed” Episode 1382 is sponsored by: https://smartcredit.com/unashamed — Get a 7-day trial for just $1, see how many points you can add to your credit score! https://cozyearth.com/unashamed — Get up to 20% off when you use our link and code UNASHAMED! http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://podcasts.apple.com/us/podcast/at-home-with-phil-robertson/id1835224621 Chapters 00:00 Jase's Bachelor Diet of Frog Legs & Donuts 03:37 Young Houseguests Leave a Big Mess 09:19 Miss Kay's Request Finally Gets Fulfilled 13:55 Zach's Gate Becomes a Lesson about Freedom 17:13 Garbage Exposes a Cultural Breakdown 21:10 Rahab & Faith That Takes Action 26:16 Rahab Risks Everything for the One True God 33:50 The Scarlet Cord Points Ahead to Jesus 37:05 Abraham & Rahab Had a Lot in Common 42:31 Faith Is Proven by What Comes Next 46:18 Giving Your Life Starts with Acts of Service 50:28 Legalism Misses the Entire Point of the Gospel — Learn more about your ad choices. Visit megaphone.fm/adchoices

Jase, Al, and Zach return to Genesis to answer the question culture and even a Supreme Court justice struggled to define, tracing what Scripture says about men, women, their differences, and every person bearing the image of God. The guys dive into church favoritism, empty “thoughts and prayers,” and the difference between simply believing in God and living out a faith that is truly alive. Zach and Jase can't decide who's the poorer listener, and Jase decides Zach's new hairstyle is proof that his midlife crisis has officially arrived.  In this episode: Genesis 1:26-28; Genesis 2:18-23; Matthew 5:13-16; Matthew 22:37-40; Mark 16:20; Romans 8:19-28; 1 Corinthians 1:9; 1 Corinthians 3:9; 1 Corinthians 16:16; 2 Corinthians 6:1; 1 Timothy 2; James 2:1-26 “Unashamed” Episode 1381 is sponsored by: Upgrade your wallet today! Get 10% Off @Ridge with code UNASHAMED at https://www.Ridge.com/UNASHAMED #Ridgepod #sponsored https://helixsleep.com/unashamed — Get 27% off sitewide and make sure you enter our show name after checkout so they know we sent you! http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://podcasts.apple.com/us/podcast/at-home-with-phil-robertson/id1835224621 Chapters 00:00 Jase's DIY Haircut Sparks a Midlife-Crisis Debate 04:14 Can Hats Be Worn in Church? 08:02 Modesty, Gender & God-Given Differences 14:51 Three Warning Signs of a Dead Faith 22:12 Why Fear of God Isn't Enough 30:15 “Thoughts and Prayers” Without Action 35:18 Every Human Bears the Image of God 40:11 God Created Us to Work Alongside Him 44:03 The Powerful Synergy of Faith & Action 48:26 God's Plan to Restore Creation Through His People — Learn more about your ad choices. Visit megaphone.fm/adchoices

Give to help Chris make Truce Jimmy Swaggart was caught in a major controversy in the late 1980s. It involved the famous American televangelist, who was a leading figure in Pentecostal Christianity. In 1988, Swaggart publicly admitted to “moral failure” after reports surfaced that he had been involved with a prostitute, behavior that directly contradicted the strict moral standards he preached. The revelation led to his suspension by the Assemblies of God, his church denomination, and caused significant damage to his reputation and ministry. Swaggart delivered a widely televised, tearful confession, which became one of the most memorable moments in religious broadcasting, symbolizing broader concerns at the time about hypocrisy, accountability, and power among high-profile televangelists. This proved to be a problem for Pat Robertson, who was running for president. Just as he needed his conservative brothers and sisters on his side... they disappeared or chose another politician. When he lost the race, he continued his streak of being shelved by politicians. He and other evangelicals with large followings placed their hope in politicians to save them. Only to find disappointment. Sources: The Evangelicals by Frances Fitzgerald Reaganland by Rick Perlstein Pat Robertson: A Life and Legacy by David Edwin Harrell Jr. Andrews, T. M. (2017). The Rev. Marvin Gorman, who prompted Jimmy Swaggart's downfall in the '80s, dies at 83 Art Harris, W. P. (1988, Feb 26). Jimmy Swaggart's secret life in the world of no-tell motels 'shouting, weeping' Preacher was just another man on prowl. Toronto Star RNC National Convention speeches 1988, around 2:35:00 God's Own Party by Daniel K Williams PETER STEINFELS (1989, Jun 12). Moral majority to dissolve; says mission accomplished. New York Times Rolling Stone Magazine article on Jay Sekulow. By Andrew Perez, January 3, 2024 Washington Post article about Robertson's death Discussion Questions How did success become a problem for the Moral Majority and Christian Coalition? Why is it a problem that we keep being marketed to with fear? How could conservative evangelicals argue both that they were the majority AND a persecuted minority? Why does it matter? Learn more about your ad choices. Visit podcastchoices.com/adchoices

The folk and easy-listening quartet gained international fame during the late 1960s and early 1970s for their wholesome sound, which specialized in waltzes, polkas, and nostalgic dance music.

Jase, Al, and Zach confront the fear-driven control that keeps parents hovering long after their children need room to grow. Jase recounts the radical prayer he prayed when his own kids rebelled and explains why parents must ultimately trust God with the people they love most. The guys connect Abraham's obedience, living faith, and the hope of resurrection to the difficult work of letting go without giving up. They also challenge Christians to move beyond merely believing in God and begin living as though they truly believe him. In this episode: Genesis 1:28; Genesis 2:15; Genesis 3:15; Genesis 9:1; Genesis 11:4; Genesis 12:1–3; Genesis 26:4; Matthew 1:1–16; Luke 20:27–38; John 12:23–32; James 2:14–26 “Unashamed” Episode 1380 is sponsored by: https://myphdweightloss.com — Find out how Al lost 80+ pounds. Visit the website or call 864-644-1900 and mention "Al Robertson" to get 2 weeks free in the program! https://chministries.org/unashamed — Get a better solution at half the cost of traditional healthcare! http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://podcasts.apple.com/us/podcast/at-home-with-phil-robertson/id1835224621 Chapters 00:00 Faith Without Action Is Dead 04:18 Why Abraham Was Called God's Friend 08:28 Bruising the Heel & Crushing the Head 13:42 Humanity's Original God-Given Purpose 16:49 Rahab's Surprising Place in Jesus' Family Line 21:58 Faith Means Believing God, Not Just Believing in God 26:16 Jase's Hardest Prayer for His Children 32:35 The Single Seed That Produced Eternal Life 38:42 Death Is Not a Problem for God 44:45 Authentic Faith Requires Bold Action 49:18 Baptism as an Abraham & Isaac Moment — Learn more about your ad choices. Visit megaphone.fm/adchoices

How did Duck Dynasty become the most popular reality series of all time? What really happened behind the cameras? Why was it so successful? And what is the Robertson family doing next?In this must-watch episode of The Resilient Show, Chad sits down with a special guests Jase and Willie Robertson from the Duck Dynasty family for an honest, behind-the-scenes conversation about faith, family values, building an empire from a Louisiana swamp, navigating massive fame, and staying grounded through it all. From humble beginnings to cultural phenomenon — this episode is packed with inspiring stories, life lessons, and resilient wisdom you don't want to miss.Key Topics:-The real origin story of Duck Dynasty-Faith, family, and staying true to your values in the spotlight-The power of authenticity and hard work-What's next for the Robertson family and their mission-Practical resilience lessons for life, business, and raising a strong familyWhether you grew up watching Duck Dynasty or just love stories of faith-fueled success, this episode will encourage and equip you. We hope you enjoy this interview and, of course, encourage you to engage with us here and on our social channels.Learn more about Duck Dynasty:Follow on IG: @duckman_stone@realjaseduckman@realwilliebosshog@officialduckcommander——Stay up-to-date with all things Resilient by subscribing to our Resilient Times Newsletter: https://resilienttimes.substack.comRESILIENT:Follow Us On Patreon: ⁠https://patreon.com/theresilientshowFollow Us On Instagram: ⁠https://www.instagram.com/resilientshowFollow Us On Twitter:⁠ ⁠https://twitter.com/resilientshowFollow Us On TikTok:⁠ ⁠https://www.tiktok.com/@resilientshowLIVE RESILIENT STORE:https://shop.theresilientshow.comFollow Chad: ⁠⁠https://www.instagram.com/chadrobo_officialhttps://x.com/ChadRoboSPONSORS: Smith & Wesson: ⁠⁠https://www.smith-wesson.com⁠⁠Vortex Optics: ⁠https://vortexoptics.com⁠Gatorz Eyewear: ⁠⁠https://www.gatorz.com⁠⁠Allied Wealth: ⁠https://alliedwealth.com⁠BioPro+: ⁠⁠https://www.bioproteintech.com/CHAD30⁠⁠BioXCellerator: ⁠https://www.bioxcellerator.com⁠Core Medical: https://coremedicalgrp.com/chadpodcastcmg------The Resilient Show is a proud supporter of military and first responder communities in partnership with ⁠Mighty Oaks Foundation⁠.

Feeling stuck after a sudden job loss or career shift? Get inspired by a real-life story of resilience, reinvention, and the pursuit of purpose.On this episode of Looking Forward Our Way, hosts Brett Johnson and Carol sit down with Randy Robertson, who candidly shares how he navigated an unexpected end to his 30-year corporate journey and found new meaning as a regional storyteller at Special Olympics New York.From managing global creative teams to rediscovering his early love for writing, Randy walks us through his step-by-step approach to tackling unemployment, overcoming self-doubt, and building an authentic new career path.Learn firsthand how Randy harnessed the power of networking (both online and in person), leveraged learning platforms and job resources, and turned personal experiences—including those with his adult daughter living with autism—into a powerful storytelling platform that helps others. You'll come away with real strategies you can use, no matter where you are in your career journey.If you like this episode, please let us know. We appreciate the feed back, and your support of offset costs of producing the podcast!Key Takeaways:How to approach sudden job loss with resilience and a proactive mindsetPractical tactics for networking, using LinkedIn, and making coffee chats countEmbracing new skills and staying technologically relevant at any ageLeveraging personal experience and unfinished business in creating a meaningful career pivotThe value of community support, volunteering, and purpose-driven workIf you're facing a career crossroads, feeling stuck, or hunting for inspiration to reignite your professional life, this conversation is a must-listen.Frequently Asked QuestionsWho is Randy Robertson and what is his role at Special Olympics New York?Randy Robertson is a regional storyteller for Special Olympics New York. He previously worked for 30 years in global creative services for a business consulting firm, and now shares stories about Special Olympics athletes and events, focusing on the special needs community 00:20, 29:44.What role did networking and LinkedIn play in his career transition?Networking—both direct outreach on LinkedIn and personal connections—was crucial. Randy Robertson messaged hundreds of contacts and found many were receptive and willing to help.How did Randy Robertson approach learning new skills and technology?He used online resources like LinkedIn Learning, took targeted courses (such as SEO and WordPress), and embraced new tools relevant to his evolving career goals.What is Randy's blog “Life with Mary” about, and how does it support the special needs community?“Life with Mary” is Randy's Substack blog sharing stories about daily life with his daughter Mary, who has moderate autism. The blog provides insights for families with special needs children and raises awareness for both those inside and outside the autism community 19:13–21:17, 31:03–41:33.What advice does Randy Robertson offer older job seekers facing a career pivot?Focus on networking, don't hesitate to reach out to contacts, use job boards for research (not as your only strategy), and be open to reimagining what fulfilling work might look like in your next chapter.We would love to hear from you.Give us your feedback, or suggest a topic, by leaving us a voice message.Email us at hello@lookingforwardourway.com.Find us on Bluesky and Facebook.Please review our podcast on Google!And of course, everything can be found on our website, Looking Forward Our Way.Recorded in Studio C at 511 Studios. A production of Circle 270 Media® Podcast Consultants.https://creativecommons.org/licenses/by-nd/4.0/Copyright 2026 Carol Ventresca and Brett JohnsonMentioned in this episode:Listener DisclaimerThe views and opinions expressed by the experts interviewed on this podcast are their own and do not necessarily reflect the views of the podcast hosts or any affiliated organizations. The information provided in these interviews is for general informational purposes only and should not be considered as professional advice. Listeners are encouraged to consult with qualified professionals for specific advice or information related to their individual circumstances. The podcast host and producers do not endorse or guarantee the accuracy, completeness, or reliability of any information provided by the experts interviewed. Listener discretion is advised.

A rundown of fun facts about the Holy Bible. 

Spring Cleaning – Dallas StarsThe Dallas Stars entered the 2025-26 season with Stanley Cup expectations after three consecutive trips to the Western Conference Final and four straight 100-point seasons. Instead, Dallas suffered another painful postseason disappointment, falling to the Minnesota Wild in six games during the opening round. Neil Smith and Vic Morren examine the Stars' dramatic swings in performance, the devastating injuries that depleted their lineup, and the difficult decisions awaiting General Manager Jim Nill as he attempts to extend the championship window of one of the NHL's most talented—but increasingly veteran—teams.IN THIS EPISODE:[00:00:00] The Dallas Stars finish second in the Central Division before losing to Minnesota in six games during the opening round of the Stanley Cup Playoffs. Neil and Vic discuss the consistently high expectations surrounding a team that has averaged more than 107 points over the last five full seasons.[00:01:00] The conversation turns to Dallas' repeated playoff disappointments after three consecutive trips to the Western Conference Final. Glen Gulutzan returned for his second stint behind the Stars' bench, following a long line of respected coaches who were also unable to lead the organization back to the Stanley Cup Final.[00:01:45] Neil explains how the strength of the Central Division and the NHL's current playoff format creates an extremely difficult opening-round matchup for any team finishing second or third. Dallas knew for months that Minnesota would likely be its opponent, but still could not find a way through one of the league's deepest teams.[00:02:00] Vic reviews the Stars' wildly inconsistent regular season. Dallas followed a 14-1-2 stretch with a 2-6-4 slide, then produced a 14-0-1 run that included 10 consecutive victories before struggling again late in the year. The panel discusses why the Stars can look unbeatable at their best and completely vulnerable when their game disappears.[00:03:00] Dallas' recent playoff history is placed under the microscope. The Stars surrendered a 2-1 series lead against Edmonton in 2024, struggled offensively against the Oilers again in 2025, and then lost another 2-1 series advantage against Minnesota after allowing a late lead to slip away in Game 4.[00:04:00] Jason Robertson and Wyatt Johnston each score 45 goals, but the offense drops sharply after the two young stars. Mikko Rantanen is revealed to have suffered a torn MCL during the Olympics, limiting his effectiveness after returning for the final 10 games of the regular season.[00:05:00] The Stars' extensive injury list is examined. Tyler Seguin suffers a season-ending torn ACL, Roope Hintz tears his hamstring shortly after returning from the Olympics, while Miro Heiskanen, Radek Faksa, Michael Bunting, and Nils Lundkvist also deal with significant injuries during the playoff push.[00:06:00] Neil and Vic debate how much the injuries contributed to the first-round exit. While every playoff team deals with health issues, Dallas lost several high-impact players whose absence significantly reduced the club's offensive depth and ability to compete with Minnesota.[00:07:00] Attention shifts to the offseason facing three-time General Manager of the Year Jim Nill. Dallas owns only five selections in the 2026 NHL Draft, with no picks in the first or third rounds after aggressively trading future assets to acquire veteran help.[00:07:45] The Stars enter the offseason above the projected salary cap before the July reset. Their unrestricted free agents include captain Jamie Benn, Michael Bunting, Adam Erne, Nathan Bastian, Alex Petrovic, and Kyle Capobianco.[00:08:00] Jason Robertson headlines Dallas' restricted free agent class after another elite goal-scoring season. Neil describes Robertson as one of the NHL's premier natural finishers and expects his next contract to become one of the largest and most important negotiations of Jim Nill's tenure.[00:09:00] The discussion turns to the aging portion of the Stars' core. While Robertson and Johnston remain young franchise pillars, longtime veterans Jamie Benn and Tyler Seguin are approaching the final stages of their careers, forcing Dallas to consider when and how to begin retooling the roster.[00:10:00] The episode concludes with a difficult question surrounding Jamie Benn's future. Neil praises Benn's leadership, toughness, and lasting impact as captain, but acknowledges that Jim Nill must eventually decide whether to continue with the veteran core or transition the team toward a new generation of leadership.

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

July 16th, 2026 Follow us on Facebook, Instagram and X Listen to past episodes on The Ticket’s Website And follow The Ticket Top 10 on Apple, Spotify or Amazon MusicSee omnystudio.com/listener for privacy information.

The film producer and distributor was a prominent figure in the so-called "Poverty Row" era of the Golden Age of Hollywood. Editor's Note: Edward L. Alperson was born in 1895, not 1905. 

The wrestler turned politician is best known for his flamboyant in-ring persona, his Hollywood acting roles, and his historic tenure as the 38th Governor of Minnesota from 1999 to 2003.OAD: July 15, 2026

Based in Hot Springs, Arkansas, Dr. Lacie Cupani is the CEO and Fashion Designer with Cupani Fashion Producer of CMG Worldwide Fashion Weeks.OAD: July 14, 2026

The 18-time Grammy winner had led arguably the greatest polka band in the world for more than 50 years. OAD: July 13, 2026

A man's lifelong hope to die while worshiping becomes reality when he collapses during a song based on Psalm 90, giving Jase, Al, and Zach a sobering reminder to number their days. The guys contrast that peaceful view of eternity with a billionaire biohacker's costly quest to reverse aging and escape death, then connect Phil's final years to Al's growing urgency to leave a lasting legacy for his family. Jase digs into James 2 and Genesis 22 to show why real faith cannot remain only a belief—it listens, trusts, and acts even when God's plan seems impossible. In this episode: Psalm 90; James 1; James 2:14–26; Genesis 3:15; Genesis 12; Genesis 22; Joshua 2; Matthew 1; John 1; John 3:16; John 3:19–21; John 8:58; Romans 4:20–21; Romans 9; Hebrews 6; Hebrews 11 “Unashamed” Episode 1378 is sponsored by: https://chministries.org/unashamed — Get a better solution at half the cost of traditional healthcare! https://www.bruntworkwear.com/UNASHAMED — Get $10 Off at BRUNT with code UNASHAMED #Bruntpod #sponsored http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://open.spotify.com/show/3LY8eJ4ZBZHmsImGoDNK2l Chapters 00:00 Jellyfish UFOs & Immortal Marine Life 05:58 Man's Quest to Live Forever 11:34 Wisdom of Numbering Our Days 16:29 Jase Declares Jellyfish UFO Pure Clickbait 19:03 Faith Without Deeds Is Dead 24:24 Why James Chose Abraham & Rahab 32:05 Abraham & Isaac Trust God to Provide 38:00 Abraham's Test Points Forward to Jesus 43:40 Seeing God's Plan in Our Sacrifices 49:58 Listening to God Means Acting on His Word — Learn more about your ad choices. Visit megaphone.fm/adchoices

Pittsburgh Penguins Forward Nick Robertson joined OverDrive to discuss landing with the Penguins, signing a contract with the team, the excitement of playing in Pittsburgh, the familiarity with the team's staff, the transition of being with the roster, the experience in Toronto, the departure from the Maple Leafs and more.

On this episode of Tip of the Ice-Burgh, Nick Belsky discusses the Pittsburgh Penguins avoiding salary arbitration with forward Nicholas Robertson and where he fits into the team's plans for the upcoming season. He also reacts to the first few games of the Penguins' schedule announced on Wednesday afternoon, Anthony Mantha finally signing in free agency, and more—tune in!   Check out our latest episodes

The Robertson family may have stumbled onto a surprisingly simple secret to a long, healthy life, and Jase, Al, and Zach compare the routines that have kept generations of their family going strong. The guys also reflect on a military veteran who searched for truth in Islam before finding peace in Jesus, then turn to James 2 for a hard look at favoritism, wealth, and celebrity culture inside the church. They challenge every Christian to reflect on how they treat others, and dig into why even correct theology becomes empty noise when it is separated from the character of Jesus. In this episode: James 1:4; James 1:27; James 2:1–26; Deuteronomy 6; Exodus 20; Genesis 1:26–28; Genesis 9; Genesis 10–11; Joel 2:28; Acts 2:5–17; Acts 15; 1 Corinthians 1:26–31; John 5; Matthew 5–7 “Unashamed” Episode 1377 is sponsored by: https://homechef.com/unashamed — Get 50% off and free shipping on your first box plus free dessert for life! curehydration.com/unashamed — Get 20% off your first order with promo code UNASHAMED https://bravebooks.com/unashamed — Use code UNASHAMED for 20% off your order! https://myphdweightloss.com — Find out how Al lost 80+ pounds. Visit the website or call 864-644-1900 and mention "Al Robertson" to get 2 weeks free in the program! http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://podcasts.apple.com/us/podcast/at-home-with-phil-robertson/id1835224621 Chapters 00:00 Zach's Yawning Sparks a Debate over Naps 05:09 Al's Fourth of July Shrimp Boil Nearly Falls Apart 08:20 The Robertson's Best Leftover Recipe 13:12 A Veteran's Journey from Islam to Jesus 17:04 James 2 Confronts Favoritism in the Church 22:27 Loving Jesus Must Change How We Treat People 28:41 The Church's Attraction to Wealth & Influence 33:44 Kingdom-Bound Wealth & Resources 38:37 Babel & God's Plan to Unite the Nations 42:40 Mercy Triumphs over Judgment 50:01 Faith Without Love Is Just Babbling — Learn more about your ad choices. Visit megaphone.fm/adchoices

On this episode of The Steve Dangle Podcast, 00:00 Golfing with Wendel Clark 24:00 Nick signs in Pittsburgh 35:00 Jason hasn't signed in Dallas 50:00 Top UFA deals quiz 57:00 Leafs move on from Hayley Wickenheiser 1:12:00 Evan Gold leaves the Bruins 1:15:00 Dylan Larkin's captaincy 1:21:00 Leo Carlsson vs Connor Bedard Visit this episode's sponsors: Camp Day is back July 15th at Tim Hortons! Every hot and iced coffee sold on Camp Day supports Tim Hortons Foundation Camps, helping youth build confidence, connection and life skills through camp. You don't have to wait until July 15th to help. Buy a bracelet, pick up a badge, or round up your order in the Tims app and you're already making a difference. Learn more: http://timscamps.com/ 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

Jase, Al, and Zach confront the political division tearing at America and challenge listeners to examine the way they view people on the other side. Jase takes the Robertson family's most destructive young wrecking ball under his wing, a pairing that seems destined for chaos. The guys explore why faith leaves no room for treating people as lesser and how the gospel dismantles the labels that keep us divided. Jase also brings up the mysterious James Ossuary, an ancient burial box that sparked years of controversy over its possible connection to Jesus' brother. In this episode: James 1:26–27; James 2; James 3:14–16; James 4:8; James 5:5, 8; Acts 15:1–19; Galatians 1:18–19; Galatians 2:7–11; Ezekiel 11:19; Ezekiel 36:26; Jeremiah 31:33; 2 Corinthians 3:3; Hebrews 8:10; Hebrews 10:16; Psalm 139; Amos 9; 2 Samuel 7; Matthew 28:18–20 “Unashamed” Episode 1376 is sponsored by: Taking care of your health just got easier – start here with Zocdoc: https://zocdoc.com/UNASHAMED #sponsored https://fastgrowingtrees.com — Get 20% your first purchase when using the code UNASHAMED at checkout. https://vanman.shop/unashamed — Get 15% off your first order with code UNASHAMED http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://open.spotify.com/show/3LY8eJ4ZBZHmsImGoDNK2l Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Chapters 00:00 Bear's Latest Destructive “Accident” 05:05 Al's Sermon on Freedom & Faith 09:12 Democracy Depends on Humility 13:30 God Shows Favor Without Showing Favoritism 21:18 The Biblical Meaning of a Circumcised Heart 27:55 Why God's Law Must Be Written on the Heart 33:06 The Hidden Heart Theme in the Book of James 38:47 The Early Church's Debate over Salvation 43:28 God Makes No Distinction Between His People 47:14 The Strange Artifact Linked to Jesus' Brother 52:02 The James Ossuary and the Limits of Biblical Proof — Learn more about your ad choices. Visit megaphone.fm/adchoices

Uncle Si and John Luke relive the dangerous Robertson compound scare that was handled by an unusually brave Duck Dynasty cameraman, then debate whether Si's legendary slingshot skills could survive an actual math test. John Luke breaks down his growing backyard animal kingdom, from chickens and bees to the mysterious animals wandering around the family property. John-David sees the silver lining in Si's brutal bee attack, and Jacob fact-checks the family's long history of questionable exotic animal ideas. Duck Call Room episode #569 is sponsored by: https://myphdweightloss.com — Find out how Godwin is losing weight! Visit the website or call 864-644-1900 and mention "Godwin" to get 2 weeks free in the program! http://ponchooutdoors.com/DUCK — Get $10 off your first order and free shipping! https://tecovas.com/duck — Get 10% off when you sign up for email and texts. - Learn more about your ad choices. Visit megaphone.fm/adchoices

Every weekday, award-winning columnist Dejan Kovacevic delivers three ‘Double Shot' shows as a supplement to the morning ‘Daily Shot' of Steelers, Penguins and Pirates podcasts!  Video versions streaming live on YouTube starting at 3 p.m.! Eastern Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Yesterday a reporter at the All Star festivities called Paul Skenes a ‘future Yankee.' As annoying as it is – is it true? Does it anger you to hear people doing this? If Skenes costs 500+ million bucks, is it worth it for the Pirates to make that deal? What if a salary cap is instituted? The Penguins have agreed to terms with Nicholas Robertson after trading for his rights 2 weeks ago. The deal with Robertson is 2 years for $3.25M/year. His brother, Jason Robertson, is still with the Stars, but continues to be part of major trade rumors. What is the price looking like to acquire the 45-goal scorer? Afternoon radio host on 670 The Score in Chicago Matt Spiegel joined the show. Matt was able to tell us about Jacob Gonzalez, one of the newest Pirates. Gonzalez was acquired by the Pirates on Friday night in a deal with the White Sox. Matt said Gonzalez started to catch his stride in the minors, but was bumpy when he got called up to the bigs. The White Sox asked him to play 1B, which he played none of in the minors. Matt thinks the Sox may regret parting ways with Gonzalez if they have an injury or two in the second half. Matt thought Gonzalez actually made it difficult for the White Sox to take him out of the lineup even after a rocky start. Matt explained why the trade was made from the White Sox perspective, but he thinks Ben Cherington may find something here.

Jase drops the news that Phil and Miss Kay's legacy of serving the homeless inspires local doctors to honor their work by transforming the site of their former ministry into a new community clinic. The guys push back on a culture that turns every sin, struggle, and bad decision into a diagnosis while avoiding confession, accountability, and the healing that comes through Jesus. They trace America's freedom back to biblical truth, arguing that the Founding Fathers' failures did not make the principles they wrote any less true or worthy of fulfillment. In this episode: Acts 4; John 14–16; James 5:16; Galatians 5:1, 13; James 1:4, 17, 25; James 2:8, 12, 22–23; 2 Peter 2; Philippians 3:18–21; Romans 1; Genesis 1:26–27 “Unashamed” Episode 1375 is sponsored by: https://meetfabric.com/unashamed — Join the thousands of parents who trust Fabric to help protect their family. http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://podcasts.apple.com/us/podcast/at-home-with-phil-robertson/id1835224621 Chapters 00:00 What Jase Learned in School 05:10 The Holy Spirit Is the Ultimate Counselor 11:05 Zach Cancels College Pizza Night  14:45 Phil & Miss Kay's Legacy Comes Full Circle 18:45 Phil's Advice for Staying Out of Prison 24:23 Freedom Requires Responsibility 31:57 The Declaration of Independence Points to God 36:53 The Foundation of American Freedom 42:05 The Non-Christian Anchor of Morality is Still God 47:02 Phil Finds Scripture Across Washington, D.C. — Learn more about your ad choices. Visit megaphone.fm/adchoices

Howard Robertson had every reason to go down the wrong path. His parents died. His siblings were in the streets. But instead of following them he chose corrections — and over a 22 year career from the late 1970s to the early 2000s he rose from correctional officer to captain to deputy warden to warden of Rikers Island — the largest and most violent jail in America. In this episode of Locked In with Ian Bick, Howard pulls back the curtain on everything — from his brutal upbringing to what made him choose corrections to what Rikers Island looked like from the inside during its most violent era to the notorious inmates he encountered to how programs reduced violence to how politicians destroyed what it could have been to the problems with closing it and what the future of Rikers Island really looks like. _____________________________________________ #rikersisland #jail #truecrimestories _____________________________________________ Thank you to FACTOR & GLD for sponsoring this episode: Factor: Head to http://factormeals.com/lockedin50off and use code lockedin50off to get 50 percent off and free daily greens per box, with new subscription only, while supplies last until 09/27/2026. (See website for more details). _____________________________________________ GLD: New customers get 40% Off with code LOCKEDIN at https://www.gld.com/ _____________________________________________ Connect with Howard Robertson: https://www.amazon.com/Student-Game-Become-Unstoppable-Smarts/dp/1977283896 _____________________________________________ Hosted, Executive Produced & Edited By Ian Bick: https://www.instagram.com/ian_bick/?hl=en https://ianbick.com/ _____________________________________________ Timestamps: 00:00 Howard Robertson's Unlikely Journey 01:12 Overcoming Tragedy and Choices 02:29 Early Mindset: Learning from Role Models 03:53 Shooting for the Moon: Mentorship & Goals 05:02 Rising Above Average Through Hard Work 07:01 Is Drive Innate or Learned? 07:42 Family, Bad Paths, and Purpose 08:03 Helping Inmates and Preventing Recidivism 09:36 From Speaking to Writing: Reaching Youth 10:16 Authenticity in Storytelling: Why the Book Matters 11:01 Personal Stories: Bullying, Friendship, and Impact 13:02 How the Past Shapes Leadership Style 14:47 Navigating Street Ties Inside Rikers 18:00 Inmate Politics and Safe Resolutions 21:22 Respect, Boundaries & Saying No 23:40 Life Lessons and Staying Clean 24:43 Sponsor Segment: Factor Meals 27:40 Entering Corrections: Career Choice 29:34 Knowing the Community: Double-Edged Sword 30:14 Respect, Fairness, and Avoiding Violence 32:00 Overcrowding, Programs, and Jail Services 34:49 Correctional Culture: Then and Now 36:32 Political Changes & Rikers' Decline 41:13 Burough Jails, Funding, and Flawed Solutions 44:43 Sponsor Segment: GLD Chains 45:56 Corrections Leadership & Barriers to Progression 47:13 Mass Incarceration, Bad Policy, and Population Issues 51:01 Physical Conditions & Racial Makeup 54:35 Bail, Releases, and Systemic Injustice 56:39 Promotions, Process & Rules of the System 01:00:31 Programs: Entertainment and Violence Reduction 01:03:35 The Winner's Dorm: Transforming Inmates 01:04:41 Solitary Confinement: Problems & Alternatives 01:08:06 Expanding Special Housing and Culture Change 01:10:44 Medical, Mental Health, and Malingering 01:13:36 Mental Health, Career Impact and Life After 01:14:50 Defining Real Success for Youth 01:15:55 Numbers that Shock: Mass Incarceration 01:17:00 Notorious and Celebrity Inmates 01:18:36 Retirement, New Mission, and Legacy 01:18:56 Biggest Takeaways: Excuse-Free Success 01:19:56 Book Recommendation & Final Thoughts _____________________________________________ To advertise on the show, contact sales@advertisecast.com or visit https://advertising.libsyn.com/LockedInWithIanBicka Learn more about your ad choices. Visit podcastchoices.com/adchoices

Jay Lafferty hosts Scotland's award-winning satirical news quiz.This week Jay and the teams break up the week's news, including: Nigel Farage's resignation announcement, Nigel Farage's announcement that he's standing, concerns about FIFA's integrity at the World Cup, Andy Burnham's thoughts on Scottish independence, new research into fitness, Taylor Swift's big day and more. Lead Writer: Nathan CowleyAdditional material: Alan Hazlie, Jon Paisley, Dan Welton & Sarah Tattersall, Rachel Powell, Lee Jevon & Garth ApThomas, Matt Oakley, Charlie Owen, Lucienne Cummings, David Nuttall, Stephen Holford, Gregor Paton and Kat Hyde Producer: Chris Quilietti Senior Producer: David Flynn Researcher: Jodie White Script Editor: Keiron NicholsonAn Eco-Audio certified Production

Phil's daughter Phyllis opens up about the story behind her book, I Never Knew, and the hardships she faced during the 44 years before her reunion with the Robertson family. Phyllis reflects on the difficult and sometimes dark road that shaped her, the calling that led her into counseling children and families, and the surprising tenderness Phil showed her during the six years they spent together before his passing. Jase and Al connect her story to their own family wounds, the way counseling helped their marriages and children, and the biblical picture of moving from fear into sonship through Christ.  In this episode: Romans 8:13-17; Acts 17; Philippians 3; James 1; 1 Corinthians 13; Psalm 139; John 14-17; Genesis 3 “Unashamed” Episode 1373 is sponsored by: https://myphdweightloss.com — Find out how Al lost 80+ pounds. Visit the website or call 864-644-1900 and mention "Al Robertson" to get 2 weeks free in the program! https://www.quo.com/unashamed — Get 20% OFF your first six months! http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://open.spotify.com/show/3LY8eJ4ZBZHmsImGoDNK2l Chapters 00:00 Jase Discovers His New Favorite Dessert 04:50 Phil's First Tender Moment with Phyllis 12:13  Phyllis Opens Up about Her Life before Phil 17:16 Phil's Advice That Jase Had to Unlearn 25:20 Jase Gets Honest about Counseling 31:08 Mia's Healing & Overcoming 37:18 The Gospel's Answer to Brokenness 44:10 Phil's DNA Test & His Tender Final Years with Phyllis — Learn more about your ad choices. Visit megaphone.fm/adchoices

Uncle Si declares Al Robertson the number one Robertson son as they relive the family conversations and moments that shaped Duck Dynasty behind the scenes. Al tells it all about the pact the family made before the show took off, Miss Kay's push for him to finally appear on the show, and when he caught Phil Robertson turning a wrestling legend's cameo into a private gospel conversation. Si, Al, and the boys look back on the Robertson family roots and the faith that still keeps the whole family grounded. Duck Call Room episode #568 is sponsored by: Try QUO for free PLUS get 20% off your first 6 months when you go to https://quo.com/duck https://rocketmoney.com/duck — Let Rocket Money help you reach your financial goals faster! https://helixsleep.com/duck — Get 20% off sitewide and make sure you enter our show name after checkout so they know we sent you! - Learn more about your ad choices. Visit megaphone.fm/adchoices

NHL writer Sean Gentille from The Athletic joined the show. Elliot Friedman said the other week that the Penguins have had serious talks with Jason Robertson, but nothing has happened yet. Sean thinks that it is possible that Robertson ends up getting traded, and that the most important thing to Jason Robertson is maximizing his contract. Sean also says that there are parts of Robertson's game that teams don't love, and are the reason why teams are hesitant to give Robertson 15 million dollars a season. Sean says the Penguins should also be hesitant on Elias Pettersson. KDKA TV's Bob Pompeani joined the show. NFL.com listed off three storylines for the Steelers going into the season, and number one was that a winning record isn't guaranteed with Mike McCarthy. Bob disagrees, and thinks the Steelers will finish above .500. PM Team Power Rankings: Greatest sporting events on the world.

The America 250 celebration gives the guys a patriotic jump-start as Zach brings back a firsthand report from Washington, D.C., including a moving visit to the Museum of the Bible, run-ins with secret service, and the world's largest-ever fireworks show. Jase, Al, and Zach connect America's story to the deeper foundation of Scripture, tracing how God's Word has endured through history and still points people toward the source of real freedom. Jase follows a biblical trail showing how Jesus fulfills the 10 words of creation, the 10 commandments, and the “I am” statements that reveal his divine identity.  In this episode: James 2:8; 1 Corinthians 15:3-4; James 2:22-23; Matthew 5:17; Luke 24:44; John 1:1, 14; Genesis 1:3, 6, 9, 11, 14, 20, 24, 26, 28-29; Exodus 3:2-6, 14; John 6:35; John 8:12, 24, 28, 58; John 10:7, 11; John 11:25; John 14:6; John 15:1; John 3:14, 19-21; John 12:32; James 4:10; Philippians 2:8-9; Hebrews 13:8; John 17:5; Matthew 28:18-20; Hebrews 10:28-29 “Unashamed” Episode 1372 is sponsored by: https://cozyearth.com/unashamed — Get up to 20% off when you use our link and code UNASHAMED!  https://chministries.org/unashamed — Get a better solution at half the cost of traditional healthcare! http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://podcasts.apple.com/us/podcast/at-home-with-phil-robertson/id1835224621 Chapters 00:00 Jase Gets Sucked into the World Cup 06:18 Jase Solves the Problem of American Soccer 11:20 Al's Grandson Takes the World Cup Loss Hard 14:27 Zach's Wild Fourth of July Trip to D.C. 21:13 Fulfilling the “Royal Law” of Scriptures 29:29 The 10 Words of Creation & the 10 Commandments 34:53 Jesus' 10 “I Am” Statements in John 40:10 The Identity of Jesus in the Father 47:05 Jesus as the Fulfillment of Moses and Abraham — Learn more about your ad choices. Visit megaphone.fm/adchoices

Since we've done about 100 episodes pointing out the general lack of preparedness of BCBAs leaving grad school and jumping right into public school work, it'd be pretty mean of us not to have some episodes where we tell you HOW to prepare. And this week we have special guests, Dr. Kristin Foley and Dr. Fina Robertson, doing just that. We cover some of the basics as to how to make friends with teachers and administrators rather than alienating them with your behavior analytic jargon before discussing specific reflection and action steps needed to ensure not just competence in your work, but also maintaining your ethical expectations while you get to work. Quick! You've still got two months of summer vacation to listen up, follow Dr. Foley and Dr. Robertson's guidance, and get your prep in gear! This episode is available for 1.0 LEARNING CEU. Articles discussed this episode: Squires, M., Cutrer-Pãrraga, E.A., Morris, J.R., Miller, E.E., & Hansen, B.D. Navigating collaboration: Factors influencing special education teachers' relationships with BCBAs in diverse school contexts. Behavior Analysis in Practice, 17, 1033-1049. doi: 10.1007/s40617-024-010009-w Copeland, S.R., Duffie, P., & Maez, R. (2025). Preparation of behavior analysts for school-based practice. Behavior Analysis in Practice. doi: 10.1007/s40617-024-01028-7 Light-Shriner, C., Pizzella, D., Schreiber, J.B., & Wahman, C.L. (2025). Collaborative practices of behavior analysts in school settings: Evidence from the field. Behavior Analysis in Practice, 18, 681-692. doi: 10.1007/s40617-023-00883-0 Robertson, F., Favre, C., Foley, K., Symons, R. & Weiss, M.J. (in review). Ethical competence for the school-based behavior analyst: Perceptions and preparedness If you're interested in ordering CEs for listening to this episode, click here to go to the store page. You'll need to enter your name, BCBA #, the two episode secret code words, and answers to the knowledge check questions to complete the purchase. Email us at abainsidetrack@gmail.com for further assistance.

Quinn Robertson has worked with 1,000+ founders in the past 7 years and is currently a Senior Manager of Finance at Walmart. In this episode we discuss why some startups win and why others don't. We also dive into some of history's greatest entrepreneurs. If you enjoyed this episode please share it with a friend. It helps me out a lot.https://podcasts.apple.com/us/podcast/built-for-more-with-jacob-oconnor/id1594231832Jacob's Instagram: https://www.instagram.com/jacoboconnorBuilt For More Instagram: https://www.instagram.com/bfmpodYouTube Channel: https://www.youtube.com/@jacob-oconnor

The offer sheet heard round the world comes through on the 4th of July. Leo Carlsson is now officially the highest paid player in the NHL. Either the Ducks match and now their young core is destroyed. Or they don't match and their young core is destroyed. Lose lose like you read about. Unless you are Leo Carlsson's bank account.  Chapters: 0:00 - Intro and World Cup Talk 14:02 - Leo Carlsson's Offer Sheet 59:56 - Robertson in Arbitration/Nemec Signing 1:10:35 - Jordan Henderson Injury 1:13:04 - Beer League Hotline PRESENTED by BetMGM. Download the BETMGM app and use code “NETTERS” and enjoy up to $1500 in bonus bets if you lose your first wager! Thanks to our Sponsors! BetMGM: Use bonus code NETTERS when signing up to receive up to $1500 in bonus bets if your first bet loses. Gambling problem? Call 1-800-GAMBLER (Available in the US) 877-8-HOPENY or text HOPENY (467369) (NY) 1-800-327-5050 (MA), 1-800-NEXT-STEP (AZ), 1-800-BETS-OFF (IA), 1-800-981-0023 (PR) 21+ only. Please Gamble Responsibly. See BetMGM.com for Terms. First Bet Offer for new customers only. Subject to eligibility requirements. Bonus bets are non-withdrawable. In partnership with Kansas Crossing Casino and Hotel. This promotional offer is not available in New York, Nevada, Ontario, or Puerto Rico. Find LUCY near you at lucy.co/stores, or save 20% on your first online order at lucy.co/NETTERS with promo code NETTERS. Learn more about your ad choices. Visit megaphone.fm/adchoices

I'm really excited about today's podcast. What happens away up there on Capitol Hill where laws are made, hearings are held, and legislators debate? Away from the headlines, behind closed doors, and in the many offices that house the members of Congress and the committees they sit on an army of congressional staffers labor away at the detailed work of legislation. This podcast gives you, the listener a peek inside that world. My guests today are a former student of mine and a former pick up basketball buddy, both graduates of the Political Science program at Biola University where I work. Solomon Chen currently works on the House Committee on Education and Workforce and Micah Robertson is the current Director of Partnerships at PreBorn! A prolife nonprofit organization, but served a staffer in the US Senate prior to moving into the nonprofit sector.Today on the show, Solomon, Micah and I talk about their experiences working on Capitol Hill, the differences between staff work on committees versus congressional offices, what a typical day looks like, and the joys and frustrations of working at the business end of American government.Subscribe to Tim Talks Politics⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ on Substack⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for the full show notes (30% off for podcast listeners)!

The Robertsons clash with modern culture's anti-family message as Jase and Zach open up about the children who changed their families forever and the biblical calling to care for widows, orphans, and the vulnerable. Jase shares the Walmart bathroom prayer moment that reminded him how “Unashamed” is reaching whole families. The guys connect James' definition of pure religion to Jesus' warning about protecting children, the spiritual danger of giving evil a foothold, and why God's design for family still stands against the isolation of the world. In this episode: James 1; 1 John 4; 1 John 2:15-17; 1 John 5; Jeremiah 22:1-5; Jeremiah 19:1-6; Genesis 1:28 “Unashamed” Episode 1371 is sponsored by: https://www.wildalaskan.com/UNASHAMED — Get $35 off your first box of wild-caught, sustainable seafood delivered right to your door. https://myphdweightloss.com — Find out how Al lost 80+ pounds. Visit the website or call 864-644-1900 and mention "Al Robertson" to get 2 weeks free in the program! Download the FREE Upside App and use promo code Unashamed to get an extra 25 cents back for every gallon on your first tank of gas http://unashamedforhillsdale.com/ — Sign up now for free, and join the Unashamed hosts every Friday for Unashamed Academy Powered by Hillsdale College Special thanks to Create-It Studios in Franklin, Tennessee, for hosting this special edition of ‘Unashamed' Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://open.spotify.com/show/3LY8eJ4ZBZHmsImGoDNK2l Chapter Notes  00:00 Jase's First Walmart Bathroom Trip 06:24 Phil Saved a Young Man's Life 12:17 Praying in Public Spaces 17:14 Sin Gives Power to Spiritual Forces of Evil 23:45 James Defines Pure Religion 30:06 Jeremiah's Warning About Innocent Blood 35:55 Jesus' Warning About Harming Children 41:45 Why Our Culture Is Anti-Family 47:40 The Real Pollution James Warns Us About — Learn more about your ad choices. Visit megaphone.fm/adchoices

00:00:00 - START 00:00:31 - Chiclets Updates 00:23:56 - Carlsson Offer Sheet 00:48:53 - Robertson arbitration 01:00:21 - Werenski 01:18:49 - New Jersey Devils 01:35:20 - Edmonton Oilers 01:38:43 - San Jose Sharks 01:45:09 - Around the League 01:58:17 - RA's World Support the Show: PINK WHITNEY: Go get a bottle of Pink Whitney.  Pinkies UP! ATHLETIC BREWING COMPANY: Go to https://Athleticbrewing.com/CHICLETS to find stores near you and get 15% off your first order. Terms and conditions and certain limitations apply.  RHOBACK: Go to https://Rhoback.com and use code SPITTIN for 20% off your first purchase through the end of the week. PINNED GOLF: Shop https://pinnedgolf.com and use code CHICLETS for an extra 15% off your purchase.You can find every episode of this show on Apple Podcasts, Spotify or Netflix. Prime Members can listen ad-free on Amazon Music. For more, visit barstool.link/schiclets

Rebecca relives her wild journey from Taiwan to Louisiana, where a one-year exchange student experience turned into a permanent place in the Robertson family. Uncle Si gets a surprise reminder that his first meeting with Rebecca nearly ended in a 911 call after he showed up for poker night alone at Willie's house. John-David and Martin are floored by her questionable McDonald's habit, and Rebecca shares how her global childhood, fashion career, downtown business, and husband all became part of the unexpected path God used to make Louisiana home. Plus, Rebecca tries to teach the boys her Taiwanese name with debatable success. Duck Call Room episode #567 is sponsored by: https://drinkag1.com/duck — Get a FREE AG1 Travel Case with 7 Travel Packs in your Welcome Kit with your first subscription order! https://buyraycon.com/duckopen — Get 20% OFF The Essential Open Earbuds today! Thanks Raycon for sponsoring! https://myphdweightloss.com — Find out how Godwin is losing weight! Visit the website or call 864-644-1900 and mention "Godwin" to get 2 weeks free in the program! - Learn more about your ad choices. Visit megaphone.fm/adchoices

Give to help Chris make Truce. Pat Robertson's bid for the 1988 Republican presidential nomination (often discussed in 1989 contexts because of its aftermath) marked a notable moment in American politics, as a prominent televangelist moved out of religious broadcasting and directly into the national political arena. After building a large following through his Christian Broadcasting Network and The 700 Club, Robertson formally entered the Republican primary race in late 1987, having first set an unusual condition for his candidacy: he would run only if three million Americans pledged support through petitions to pray, work and contribute to his campaign—an effort that succeeded and gave him a built-in grassroots base. His platform blended standard conservative Republican positions—such as lower taxes and strong defense—with a strong emphasis on social and moral issues informed by his evangelical Christian worldview. During the 1988 primary season, Robertson surprised many political observers by finishing second in the Iowa caucuses, ahead of Vice President George H.W. Bush and indicating the mobilizing power of evangelical voters in early nominating contests. However, he struggled to maintain momentum as voting moved to later states: his support weakened in more diverse primary electorates, and he did not win a competitive share of delegates nationwide. Ultimately, Robertson suspended his campaign in 1988, later endorsing Bush, who went on to win the nomination and presidency. In the aftermath of his presidential run, Robertson organized the Christian Coalition in 1989, which became a significant force in mobilizing conservative Christian voters and shaping Republican politics in the 1990s and beyond. His campaign was plagued by the public falls of other televangelists like Jim and Tammy Faye Bakker. Our special guest for this episode is John Wigger. Sources PTL: The Rise and Fall of Jim and Tammy Faye Bakker's Evangelical Empire by John Wigger Pat Robertson: A Life and Legacy by David Edwin Harrell Jr. God's Own Party by Daniel K Williams "Clean Up Radio Everywhere" (Season 3, Episode 22) WKRP in Cincinnati Prime Time Preachers by Jeffrey K. Hadden and Charles E. Swann. Fager, C. (1982, May 05). Falwell and co.--on the skids... or speeding up? In these Times Interview with Frances Fitzgerald on the Gospel Coalition The Evangelicals by Frances Fitzgerald Reaganland by Rick Perlstein “CBN'S Pat Robertson: White House Next?” Saturday Evening Post, March 1985. by Cory SerVaas M D. and Maynard Good Stoddard. ABC News story on the Bakkers Interview with Falwell on the Bakker scandal Discussion Questions A lot of evangelicals with large followings are super into entrepreneurship. Why is that? How does it change evangelicalism? Why would it be risky for Robertson to have extraction interests in poor countries? How did the public falls of televangelists impact Robertson? What is there to be learned from the Tim and Tammy Faye Bakker scandals? Learn more about your ad choices. Visit podcastchoices.com/adchoices

Washington Watch Reporter Mary Stackhouse reports on the NATO Summit, Iran, and the latest scandal surrounding Graham Platner. Dr. David Adesnik, Vice President of Research at the Foundation for Defense of Democracies, shares what to anticipate from

The UK is now in political turmoil, as Keir Starmer has announced his resignation. The next British election is still three years away, but it is hotly anticipated because Labour is going to faceoff against three parties of the Right: the Tories (also known as the Conservaties), Reform UK and Restore Britain. Reform, led by Nigel Farage and stocked with defections from the Tories, has a good chance to win in 2029. On today's episode, Razib talks to Joseph Robertson about the British politican scene. Robertson is Director at Touchpoint Strategy and CPAC Britain, wrote for Epoch Times and has been a long-time conservative political consultant in the UK. Currently, he is aligned with Reform UK. Razib and Robertson discuss the political and economic challenges facing the UK, particularly since the 2019 election and Brexit. Robertson highlights the shift in political allegiances, with the working class moving from Labour to the Tories, and the subsequent rise of Nigel Farage's Reform UK party. They address issues like economic stagnation, high energy costs, and the impact of net-zero policies. Robertson criticizes the inherited socialist Fabian agenda of Labour and the lack of integration among new immigrants. They also touch on the rise of radical Islam and the need for stronger national identity and sovereignty. The conversation concludes with the announcement of CPAC UK, aiming to unite conservative movements globally.  

NHL Insider Sean Shapiro says Jason Robertson wants to be a Dallas Star. He joins Gavin Spittle to discuss the moves the Stars made this past week. They discuss Robertson filing for arbitration, Mavrik Bourque signing with Nashville and Jamie Benn signing a one year deal.

Guest co-host Michael Chiesa fills in for Matt in an episode of Unfiltered that invites reigning strawweight champion into the show after discussions about UFC Baku and next weekend's UFC 329 card.First, Jim and Chiesa unpack the biggest storylines from UFC Baku, including Rafael Fiziev's much-needed knockout win in front of his home crowd. The conversation then shifts to UFC 329, where Chiesa shares his expectations for Conor McGregor's long-awaited return against Max Holloway and shares his thoughts on whether Max can hold is own in his very first fight at 170 pounds.Then, Mackenzie Dern joins ahead of her first UFC title defense against fellow jiu-jitsu ace Gillian Robertson at UFC 330. Dern reflects on the turnaround that led to her three-fight winning streak and championship victory, explains why the stylistic challenge against Robertson excites her, and reflects on what it meant to help out the next wave of UFC hopefuls on this season of The Ultimate Fighter.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Every weekday, award-winning columnist Dejan Kovacevic delivers three ‘Double Shot' shows as a supplement to the morning ‘Daily Shot' of Steelers, Penguins and Pirates podcasts!  Video versions streaming live on YouTube starting at 3 p.m.! Eastern Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

As July heat makes its way to New England, we're staying inside with the AC on and a bevy of exciting guests in the studio. That's right: It's GUEST MONTH! Nothing but episodes featuring amazing guests. First we kick things off by reviewing how to get ready for the new school season with Dr. Kristin Foley and Dr. Fina Robertson sharing their work on preparing behavior analysts to work effectively and ethically in schools. Next Dr. Jon Bailey shares his unique and masterful perspective on ethical behavior from the past to the future! Turning back to schools, we learn from Dr. Mawule Sevon how to look for and plan against inequitable discipline practices that are harming Black students, especialy Black girls. Then Dr. Denise Ross and Dr. Douglas Greer teach us how to teach others how to read no matter the age in a secret Book Club episode. And it's a good time too because we also find out what books we'll be reading in the 2026-2027 podcast year. Will Diana be happy with our listeners' choices? Either way, she'll be happy with all these awesome guests! Articles for July 2026 Preparing for Public School Practice w/ Dr. Kristin Foley + Dr. Fina Robertson Squires, M., Cutrer-Pãrraga, E.A., Morris, J.R., Miller, E.E., & Hansen, B.D. Navigating collaboration: Factors influencing special education teachers' relationships with BCBAs in diverse school contexts. Behavior Analysis in Practice, 17, 1033-1049. doi: 10.1007/s40617-024-010009-w Copeland, S.R., Duffie, P., & Maez, R. (2025). Preparation of behavior analysts for school-based practice. Behavior Analysis in Practice. doi: 10.1007/s40617-024-01028-7 Light-Shriner, C., Pizzella, D., Schreiber, J.B., & Wahman, C.L. (2025). Collaborative practices of behavior analysts in school settings: Evidence from the field. Behavior Analysis in Practice, 18, 681-692. doi: 10.1007/s40617-023-00883-0 Robertson, F., Favre, C., Foley, K., Symons, R. & Weiss, M.J. (in review). Ethical competence for the school-based behavior analyst: Perceptions and preparedness. Ethics for Today and Tomorrow w/ Dr. Jon Bailey Bailey, J.S. (1991). Marketing behavior analysis requires different talk. Journal of Applied Behavior Analysis, 24, 445-448. doi: 10.1901/jaba.1991.24-445 Sellers, T.P., Seniuk, H.A., Lichtenberger, S.N., & Carr, J.E. (2025). The history of the Behavior Analyst Certification Board's ethics codes. Behavior Analysis in Practice, 18, 650-660. doi: 10.1007/s40617-023-00803-2 Inequitable Discipline w/ Dr. Mawule Sevon Ladson-Billings, G. (1998). Just what is critical race theory and what's it doing in a nice field like education? International Journal of Qualitative Studies in Education, 11, 7-24. doi: 10.1080/095183998236863 Epstein, R., Blake, J.J., & Gonzàlez, T. (2017). Girlhood interrupted: The erasure of Black girls' childhood [White paper]. Center on Poverty and Inequality, Georgetown Law. https://genderjusticeandopportunity.georgetown.edu/wp-content/uploads/2020/06/girlhood-interrupted.pdf Sevon, M. (2022). Schooling while Black: Analyzing the racial school discipline crisis for behavior analyst. Behavior Analysis in Practice, 15, 1247-1253. doi: 10.1007/s40617-022-00695-8 So You Want to Teach Reading (When Text Speaks Book Club) w/ Dr. Denise Ross + Dr. Douglas Greer Ross, D.E., Greer, R.D. (Eds.) (2025). When text speaks: Learning to read and reading to learn. Sloan Publishing.