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Michael Bernstam explains how Ukrainian drone strikes have destroyed 30% of Russia's refining capacity, causing the "crack spread"—the profit margin for refining oil—to triple worldwide. While Russia exports crude, it now suffers from severe domestic shortages of gasoline and jet fuel. Consequently, Russia is forced to buy back its own refined oil from India at premium prices. Putin has been "hoist on his own petard," creating a global energy weapon that has ultimately turned against the Russian economy. (9)1860 INDIA
In this episode, we break down what capacity really is, why it's one of the greatest predictors of success, and how to intentionally expand it. You'll learn why opportunities don't change your life—your ability to carry them does. If you want a bigger business, stronger relationships, greater peace, or more impact, you must first become the person who can sustain it.Watch the documentary: Change the family treeBuy my book Above the illusion. Above the Illusion: The blueprint for mental clarity, self-respect, and irreplaceable value" is a deep exploration into the hidden forces shaping our lives – the conditioning, beliefs, and stories we've unknowingly accepted as truth. This book exposes the psychological distractions that cloud our vision, keeping us blind, fearful, and stuck in cycles of limitation.Anthony Minaya challenges you to question the narratives that hold you back, illuminating the illusions that prevent you from seeing yourself clearly. From the self-imposed boundaries to the unconscious patterns dictating your choices, "Above the Illusion" guides you to break free from the mental fog and step into undeniable personal growth.This isn't just a book about change – it's about learning how to see. When you learn to recognize what is real and what is fabricated by fear and doubt, you gain the clarity, awareness, and self-respect necessary to reshape your life."Above the Illusion" will leave you more prepared, more conscious, and more powerful than ever before – ready to live with a sharpness that cuts through deception and a confidence rooted in truth.Buy now. https://a.co/d/8w516R7
Dr. Tommy Wood, BM, BCh, PhD, is a professor of neuroscience at the University of Washington and an expert on brain health, neuroplasticity, and cognitive performance. Dr. Wood explains how to use specific forms of exercise, dietary strategies, and compounds to enhance the rate and stability of mental and/or physical skill development. We also discuss science-based tools to preserve cognitive function, reduce dementia risk, and offset loss of memory after a concussion or other brain injury. This episode provides practical, science-based tools for learning new information and skills and for improving your overall ability to learn. Read the episode show notes at hubermanlab.com. Thank you to our sponsors AG1: https://drinkag1.com/huberman David: https://davidprotein.com/huberman Function: https://functionhealth.com/huberman Rorra: https://rorra.com/huberman Timestamps (00:00:00) Tommy Wood (00:04:05) Neuroplasticity; Neurogenesis; Synaptic Pruning (00:11:11) Aging & Neuroplasticity; Familiar vs Novel Tasks (00:14:33) Protocols Book; Sponsor: David (00:16:49) Aging, Training & Processing Speed (00:21:56) Enhancing Neuroplasticity with Age, Tool: Motor & Cognitive Challenge (00:26:56) Learning New Skills, Dance, Sports, Arts; Psychological Benefits of Challenge (00:36:50) Flow, Clutch States; Virtuosity (00:46:59) Power of Practice (00:50:55) Sponsor: AG1 (00:52:14) Tools for Focused Work & Learning; Distractions (01:00:17) Nutrition for Brain Health, Dementia; Critical Nutrients (01:06:56) Nutrient Timing, Supplementation; Omega-3s, Tool: Blood Tests (01:16:41) Sponsor: Function (01:18:19) Enhancing Brain Health, Nutrition & Supplements (01:23:10) GLP-1s, Peptides, Supplements & Evaluating Efficacy (01:32:56) Stimulants: Feeling vs Performance (01:37:18) Exercise & Enhancing Cognitive Function, Tool: Optimize Exercise Volume (01:43:18) Long-Term Cognitive Health & Exercise, HIIT (01:47:17) Sponsor: Rorra (01:48:31) Cortisol Benefits, Acute vs Chronic Stress (01:54:24) Resistance & Aerobic Exercise, Brain Gray & White Matter, Cognitive Health (02:03:37) Cognitive Decline, Dementia, Alzheimer's Disease, Modifiable Risk Factors (02:09:47) Shingles Vaccine & Dementia Risk; Tool: Avoid Illness for Cognitive Health (02:18:28) Concussion, Traumatic Brain Injury (TBI), Creatine (02:24:04) Treating TBI, Supplements, Physical Therapy (02:32:16) Strongman Competition (02:38:51) Zero-Cost Support, YouTube, Spotify & Apple Follow, Reviews & Feedback, Sponsors, Protocols Book, Social Media, Neural Network Newsletter Disclaimer & Disclosures Learn more about your ad choices. Visit megaphone.fm/adchoices
Want to Start or Grow a Successful Business? Schedule a FREE 13-Point Assessment with Clay Clark Today At: www.ThrivetimeShow.com Join Clay Clark's Thrivetime Show Business Workshop!!! Learn Branding, Marketing, SEO, Sales, Workflow Design, Accounting & More. **Request Tickets & See Testimonials At: www.ThrivetimeShow.com **Request Tickets Via Text At (918) 851-0102 See the Thousands of Success Stories and Millionaires That Clay Clark Has Helped to Produce HERE: https://www.thrivetimeshow.com/testimonials/ Download A Millionaire's Guide to Become Sustainably Rich: A Step-by-Step Guide to Become a Successful Money-Generating and Time-Freedom Creating Business HERE: www.ThrivetimeShow.com/Millionaire See Thousands of Case Studies Today HERE: www.thrivetimeshow.com/does-it-work/
On today's episode, Dr. Mark Costes answers listener questions in this Ask Me Anything special, covering ownership strategy, practice growth, scaling decisions, and the team of advisors every dental owner should build. Mark shares what he would do differently if he were starting over as a new grad, including avoiding practices that are too small to scale, being cautious with overly rural locations, and focusing on demographics, capacity, and long-term exit options. He also discusses when it makes sense to add another doctor, what metrics to watch beyond revenue, and why owners should stabilize their flagship practice before pursuing additional locations. The episode also dives into building a personal board of directors, including a CPA, bookkeeper, attorney, tax strategist, financial advisor, banker, and performance coach, before wrapping with advice on making faster, less fearful business decisions without abandoning thoughtful analysis. Be sure to check out the full episode from the Dentalpreneur Podcast EPISODE RESOURCES https://www.truedentalsuccess.com Dental Success Network Subscribe to The Dentalpreneur Podcast
Have you ever heard a coach or well-meaning adult say something like, "every extra 10 pounds puts 70 to 100 pounds of extra force through a gymnast's joints"?It sounds scientific. It sounds logical. And it can make a parent start to wonder if their gymnast should be smaller to protect her joints.But here is the problem: that statement only tells half the story.In this episode, Christina breaks down the physics and the physiology behind gymnast injury risk, and why trying to make a growing gymnast lighter is not the same thing as making her safer.The physics part is true. Landing forces in elite gymnastics can reach six to thirteen times an athlete's body weight, and a lighter athlete does experience less external force on identical landings. But injuries are not determined by physics alone. They come down to whether the body is actually prepared to absorb that force.Christina walks through what does the absorbing: muscles, tendons, bones, ligaments, and the nervous system. Think of it like a truck's suspension system. It is not the weight of the truck that smooths out the bumps, it is the suspension. For a gymnast, her muscles, tendons, and bones are that suspension.And building that suspension requires fuel. When a gymnast underfuels, she ends up with low energy availability, meaning her body does not have enough calories to grow, repair, recover, and adapt from training. The result is earlier fatigue, slower reaction time, worse recovery, and poor training adaptation, all of which increase injury risk rather than lowering it.Christina explains the real framework sports medicine uses: load versus capacity. Load includes things like number of landings, skill difficulty, training hours, and body weight. Capacity includes muscle strength, bone health, tendon health, landing mechanics, sleep, recovery, and fueling. You can lower the load by making an athlete smaller, or you can build her capacity, and the best injury prevention strategies focus on capacity.This matters even more for growing, developing gymnasts going through puberty. Weight gain, body fat gain, and growth spurts during this stage are normal biology, not something to diet against. Restricting a gymnast through puberty interferes with normal growth and bone development, and tends to backfire.Christina also unpacks what the research on RED-S (Relative Energy Deficiency in Sport) actually says, and why the International Olympic Committee identifies underfueling, not body weight, as the biggest nutritional threat to an athlete's health and performance.In this episode, we cover:❗ Why the "extra pounds equal extra force on joints" statement only tells half the story❗ How landing forces actually work in elite gymnastics❗ Why physics tells us how much force hits the body, but not whether the body can handle it❗ What actually absorbs landing forces: muscles, tendons, bones, ligaments, and the nervous system❗ Why underfueling leads to low energy availability, and what that does to performance❗ Why RED-S identifies underfueling, not body weight, as the biggest threat to athlete health❗ The load versus capacity framework sports medicine uses to think about injury risk❗ Why strong, well-fueled muscles absorb force and fatigued muscles transfer it to bones and growth plates❗ Why weight gain and growth spurts during puberty are normal biology, not a problem to fix❗ Why restricting a growing gymnast's food can interfere with bone development and backfire long-term❗ Why resilient, well-fueled athletes recover better, train harder, and stay healthier and in the sport longer❗ How to shift the question from "how do I make her lighter" to "how do I help her body get stronger"Christina's takeaway: the goal is not to create the lightest gymnast in the gym. It is to create a gymnast whose body can tolerate thousands of landings, recover from them, and keep getting stronger.If you have been wondering about this, if a coach has made comments about your gymnast's weight, or if you are watching your gymnast's body change through puberty and want support navigating it, reach out. Information on how to connect is below.Links & ResourcesThe Balanced Gymnast® Program (Level 5–10)Connect with Christina on Instagram @the.gymnast.nutritionist christinaandersonrdn.com
In this episode of Personal Injury Marketing Minute, host Lindsey Busfield is joined by Sarah Walton, a business strategist and coach, to explore the concept of high capacity women leaders and their impact on law firms. Sarah explains the physiological and psychological aspects that enable women to multitask effectively and discusses the importance of recognizing and harnessing this capacity without falling into the trap of high-functioning codependence. They delve into the significance of delegation in business, emphasizing how it can prevent burnout and enhance productivity. The conversation also covers practical strategies for law firm owners to implement healthy habits and mindset shifts that lead to sustainable business growth and personal fulfillment. Listeners will gain insights into improving their leadership skills, fostering a supportive work environment, and achieving a better work-life balance. Key Timestamps: 00:01 –Introduction 0:17 –Defining High Capacity Women Leaders 1:26 –The Science Behind Multitasking 2:18 – High Functioning Codependence Explained 3:34 – The Double-Edged Sword of High Capacity 5:56 – Reframing the A Game for Sustainability 7:00 – Importance of Delegation in Law Firms 9:02 – Delegating for Business Efficiency 10:10 – Creating Jobs and Wealth Flow 12:19 – Eliminating Business Lag 14:18 – Leadership Through Delegation 16:00 – Business Needs vs. Personal Preferences 17:12 – Hiring the Right People 19:47 – Implementing the 80% Rule 22:05 – Mindset Shifts for Business Success 24:03 – Starting the Day with a Slow Morning 26:12 – Connecting with People for Business Growth See all episodes or subscribe to the Personal Injury Marketing Minute here: https://optimizemyfirm.com/podcasts/. What Defines High-capacity Women Leaders In The Business World? High-capacity women leaders are individuals who can multitask effectively due to physiological traits, such as more connective tissue between the brain’s hemispheres, allowing them to handle multiple tasks simultaneously. This ability often leads them to function at high levels consistently. However, this capability can sometimes lead to high-functioning codependence, where they overextend themselves, neglecting self-care and delegation. Recognizing and managing this balance is crucial for sustainable success. How Can Women Leaders Avoid Burnout While Maintaining High Performance? To avoid burnout, women leaders should recognize that while they are capable of multitasking, it is not necessary to function at high levels constantly. It’s essential to delegate tasks and set boundaries to prevent becoming overwhelmed. By acknowledging the need for support and avoiding the trap of trying to do everything themselves, leaders can manage their responsibilities more effectively and maintain a healthier work-life balance. Why Is Delegation Important For Business Leaders, Particularly In Law Firms? Delegation is critical because it allows leaders to focus on the aspects of their business they are passionate about and excel in. By delegating tasks that are not their strengths, leaders can reduce inefficiencies and prevent burnout. This approach not only fosters a more dynamic and efficient workplace but also enables leaders to perform at their best, contributing to the overall success of the business. How Can Law Firm Leaders Effectively Delegate Tasks? Law firm leaders can delegate effectively by understanding that they are not their business; the business is an entity on its own. Leaders should focus on what the business needs rather than personal preferences for task completion. By hiring people who excel in specific areas and allowing them to take ownership of their roles, leaders can ensure tasks are completed efficiently, freeing them to focus on critical areas of the firm. What Should Leaders Consider When Hiring To Ensure Effective Delegation? When hiring, leaders should adopt the mantra “hire hard, manage easy.” It’s important to invest time in finding the right fit for the business and then provide comprehensive training and clear SOPs (Standard Operating Procedures) to guide new hires. This ensures that tasks are completed to the desired standard without the leader having to micromanage, allowing the business to run smoothly and efficiently. How Can Law Firm Owners Incorporate Mindset Shifts And Habits For Better Business Outcomes? Law firm owners can benefit from adopting mindset shifts such as the Pareto Principle, focusing on the most impactful tasks, and maintaining an 80% capacity to prevent burnout. They should also implement daily habits like starting their day with a slow morning routine, reflecting on personal and business priorities. These practices can enhance productivity, improve mental clarity, and lead to greater satisfaction and success in their professional lives. What Practical Advice Can Law Firm Owners Implement To Improve Their Leadership And Business Operations? Law firm owners should remember that they matter and that their actions have significant impacts. By prioritizing self-care, setting clear goals, and maintaining connections with clients and colleagues, leaders can ensure they are operating at their best. Recognizing their value and the importance of their contributions can lead to better decision-making and a more fulfilling professional experience. {"@context":"https://schema.org","@type":"FAQPage","mainEntity":[{"@type":"Question","name":"What Defines High-capacity Women Leaders In The Business World?","acceptedAnswer":{"@type":"Answer","text":"High-capacity women leaders are individuals who can multitask effectively due to physiological traits, such as more connective tissue between the brain's hemispheres, allowing them to handle multiple tasks simultaneously. This ability often leads them to function at high levels consistently. However, this capability can sometimes lead to high-functioning codependence, where they overextend themselves, neglecting self-care and delegation. 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In This Hour:-- The momentum for destroying bans on classes of guns continues/-- Why own several AR-15s?-- One federal court just ruled that bans on so-called "High Capacity" magazines are unconstitutional. Will the Supreme Court rule that way?Gun Talk 07.19.26 After ShowBecome a supporter of this podcast: https://www.spreaker.com/podcast/gun-talk--6185159/support.
In this interview I sit down with MJ Gordon, high-performance strategist and founder of the Level Up System. This conversation is all about how fast-paced professionals can increase their capacity and deliver on their bigger ambitions in life and business.Keep in touch with MJ!WebsiteInstagram
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
A Deeper Investigation Into Whether Romantic “Value” Measures Character, Compatibility, Purchasing Power, Social Rank, Emotional Capacity, Or Our Willingness To Pay The Hidden Price Of Access
The RUNDOWN S6 E111: Breaking: Third Circuit Says Ban on 'Assault Weapons' and 'Large Capacity' Magazines Is UnconstitutionalPlease Support Our Sponsors:HITMAN INDUSTRIES - Visit them at https://www.hitmanindustries.net/THE CALIFORNIA REPUBLICAN ASSEMBLY - Visit them at https://cragop.org/USCOMBATGEAR.COM - Visit them at https://www.uscombatgear.com/HAWG HOLSTERS - Visit them at https://www.hawgholsters.com/
Michael Bernstam explores Houthi threats to the Bab-el-Mandeb strait, which could drive oil prices over $100 per barrel by choking global shipping. Simultaneously, Ukrainian drone strikes have crippled Russian refining capacity and shipping in the Black Sea, leading to energy rationing, electricity shortages, and potential food crises in Crimea. (2)
Send us Fan Mail"Every stage of your business growth requires a different version of you as the business owner."Antwon is all about removing the complexities from being a business owner or entrepreneur and focusing on what it takes to execute. Scaling your business will not be possible if you are not changing the capacity in which you operate. They are not asking you to relinquish control completely, but rather truly step into the role of CEO and take advantage of the resources at your disposal. As you work with Antwon and the team, you'll come to the realization that they don't call him "The Skillful Advisor" for no reason. Tune in to episode 237 as Antwon reveals his ideal client, recalls how two decades in the Army contributed to the experience he has today and much more!For more information about The Skillful Advisor:Website: antwonperson.comLinkedIn: Antwon PersonSupport the show
Why you should listenJim Marascio runs Equals 11 with roughly 30 direct team members, yet delivers Salesforce work with on-demand access to more than 600 certified engineers. He breaks down the exact staffing partnerships in LATAM and Europe that let a lean business play far larger than its headcount.Learn how to move up the value chain from tactical delivery to consultative "what if" conversations: the shift that raises deal value, creates more interesting work for your engineers, and turns you into the trusted advisor a client cannot swap out.Get Jim's front-end planning approach (milestones, definition of done, clear ownership, agreed success metrics) that keeps projects out of the 40% of implementations that stall on activity without results.You want to take on bigger Salesforce work, but every larger project means hiring people you cannot afford to keep on the bench, so you stay stuck delivering most of it yourself. In this episode, I talk with Jim Marascio from Equals 11, who spent 25 years as a CIO and CTO of SaaS companies before building a delivery business that runs on a lean core team and plays far larger than its size. We get into the moment he stopped being the tactical fix-it vendor waiting for clients to define the problem, and started becoming the strategic partner clients build their roadmap around. Jim also puts a number on it: roughly 40% of implementations break, and the difference between the ones that deliver and the ones that stall comes down to what you do in the first week. If you are the owner doing too much of the delivery and you want to grow capacity without betting the business on payroll, this conversation is your blueprint.About Jim MarascioJim Marascio is the founder and CEO of Equals 11, a certified Salesforce consulting partner that helps mid-market companies get real value from Salesforce long after go-live. With more than 25 years as a CEO, CIO, and CTO, he has built his career managing distributed teams, and today Equals 11 pairs a lean core team with a network of 600+ certified Salesforce engineers across the US, Latin America, and Europe. Guided by the belief in its name, 1 + 1 = 11, Jim has grown the firm from tactical delivery into strategic, consultative work for direct clients and system integrators alike.Resources and LinksEquals 11 Jim Marascio on LinkedInSalesforce AgentforceClaudeNeed help with your WHO and WHAT decisions? Apply for a FREE Multiplier CallBook a Decision Session herePrevious episode: 694 - The 60% ShiftCheck out more episodes of the Paul Higgins PodcastSubscribe to our YouTube channel: @PaulHigginsMentoringJoin our newsletterSuggested resources
Recorded live at Cannes, this episode explores the shift from surface-level ad efficiency to true business effectiveness in a hyper-fragmented media landscape. VaynerX's Jon Morgenstern delivers a masterclass on navigating the creator economy, leveraging YouTube's cross-screen dominance, and using common-sense attribution to cut wasteful ad spend without harming the bottom line. Key Highlights
AP correspondent Karen Chammas reports on a Taiwanese chip making company's huge investment in manufacturing in the U.S.
What if the biggest obstacle to greater abundance isn't attracting more—but feeling safe enough to receive it? In this episode of the Money Lighthouse Podcast for Spiritual Entrepreneurs, Michel Ai Reavis concludes her three-part neuroscience and money series by exploring the fascinating connection between the nervous system and our ability to receive success, money, opportunities, visibility, and support. Listeners will discover why expansion can sometimes feel unexpectedly uncomfortable, even when it is something they've been praying for and working toward.Drawing on neuroscience and gentle nervous system awareness, Michel explains why the brain naturally prefers what is familiar over what is possible, and how that tendency can influence financial decisions, business growth, pricing, visibility, and the willingness to accept abundance. Rather than viewing hesitation or self-doubt as personal flaws, this episode invites spiritual entrepreneurs to see these experiences through a compassionate, empowering lens.Listeners will leave with practical, supportive ways to gradually expand their capacity to receive, celebrate success without fear, and create greater safety around prosperity, recognition, and joyful growth. If you've ever wondered why success can sometimes feel just as vulnerable as struggle, this encouraging conversation offers both insight and hope for your next season of expansion.Action StepsPractice receiving with intention. The next time someone offers a compliment, support, encouragement, or appreciation, simply say, "Thank you," and allow yourself to fully receive it without minimizing or deflecting it.Celebrate your wins—big and small. Pause to acknowledge each success before rushing to the next goal. Help your nervous system learn that growth, achievement, and abundance are safe.Notice where receiving feels uncomfortable. Pay attention to moments when you hesitate to accept opportunities, charge appropriately, ask for help, or welcome visibility. Approach these moments with curiosity rather than judgment.Ask a new empowering question. Instead of asking, "What if it doesn't work?" gently explore, "What if it does?" Notice what thoughts, emotions, and possibilities begin to emerge.Journaling PromptsWhere in my business or financial life do I already feel safe receiving, and where do I still notice resistance?If success, visibility, and abundance felt completely safe, what opportunities would I be willing to say yes to today?What is one small way I can intentionally practice receiving more support, joy, or prosperity this week?If this episode encouraged you, inspired a new perspective, or helped you better understand your relationship with receiving, consider sharing it with another spiritual entrepreneur who may need this reminder. Together, we can create healthier relationships with money, success, and abundance—one gentle step at a time.Thank you for listening to the Money Lighthouse Podcast for Spiritual Entrepreneurs. Be sure to subscribe so you never miss a future episode, and if this conversation resonated with you, leaving a review is a wonderful way to help more purpose-driven entrepreneurs discover the show. Your willingness to receive may become the very thing that allows your light to reach those who need it most.Contact Michel: michel@moneylighthouse.com
Send us Fan MailBex Spiller is the founder of The Anti-Burnout Club and creator of the Right to Recover campaign — joins Ela to talk burnout, workplace culture, and why recovery should be a right, not a luxury.We covered Bex's Burnout StoryBex built a marketing agency from her bedroom at 21, then hit a wall physically and mentally while studying for an MBA in addition to long working hours. A GP eventually named what she'd been feeling: burnout — a word she'd never heard before. That crisis, plus losing her father to stress-related heart disease, led her to start a small blog in 2020 that grew into The Anti-Burnout Club, now used by tens of thousands.We discussed where "Push Yourself" Beliefs Come FromBex traces her own drive back to childhood — poverty, losing her mum young, and feeling she had to prove herself. We discussed how hustle culture, school attendance awards, and even old Protestant beliefs about idleness being sinful have taught us that rest equals laziness — when most "laziness" is really overwhelm or unaddressed struggle.We explained why Individual Wellness Fixes Aren't EnoughYoga and meditation apps, whilst certainly great resources, put the burden of recovery on the individual and ignore root causes (e.g. understaffing and poor management in organisations, overcommitment and complex life circumstance in private lives). Bex now focuses on organisations — training managers to have honest conversations about stress, rather than offering wellness perks as a substitute for real change.Bex explained the Right to Recover CampaignEmployees take 9–11 official sick days a year on average, but "presenteeism" (working while unwell) costs roughly 44 lost productive days per person annually! Bex argues that giving people genuine time to recover is both more humane and better for business — and discusses how mistrust and guilt make it harder for people to ask for rest.We talked about the physical toll of burnoutChronic stress has real physiological effects — weakened immunity, stress-related heart disease, allostatic load. Bex reflects on a funeral where a woman's career barely came up compared to how she lived and loved. The takeaway: systemic change is needed, but individuals can start by knowing their own capacity, having honest conversations, and treating recovery as normal, not a failure.About Bex SpillerBex Spiller is an award-winning burnout speaker, author and changemaker. She's the founder of The Anti-Burnout Club and heads up the Right to Recover campaign, which aims to reduce the number of people working when unwell. Connect with Bex: The Anti Burnout Club (free app available) https://bexspeaks.com/ Support the showPlease reach out if you would like some support with your relationship to food OR movement. Ela currently has limited spaces for Intuitive Eating coaching and if you'd like to reconnect with movement, contact Christine. If you'd like exclusive access to our supporter-only channel click here.We appreciate you
Today's guest introduces us to the concept of capacity: the gap between the effort someone puts in and the impact they get out. You'll learn why capacity isn't a fixed container, like a gas tank or battery, but a nervous-system bandwidth that is completely trainable. You'll discover how a coach's own dysregulation bleeds into the coaching relationship through nervous system co-regulation, and why two clients can present with identical stated goals. At the same time, one is ready for strategy and the other needs nervous system regulation first, and how coaches can learn to read “the thing beneath the thing.” Join us for practical strategies, a “feel-think-do” framework, and the path to your free capacity report card self-assessment. Dr. Lizette Warner is a keynote speaker and leadership capacity expert who helps organizations solve the effort-to-impact disconnect so they can build cultures where people make a bigger impact with less effort, while increasing engagement and retention. With a PhD. in Biomedical Engineering, 20+ years of executive leadership experience in science and health technology, and certification as a Master Certified Coach through the ICF, Lizette sits at a rare intersection of scientific precision, executive credibility, and embodied transformation. Her Hashimoto's diagnosis, an autoimmune condition she now understands as her body's response to years of unregulated performance, was the turning point that reoriented everything she knew about achievement and performance. Today, she speaks at corporate conferences, leadership retreats, and executive events on topics including leadership under pressure, high-performance culture, decision-making, and workplace resilience. Show Highlights:Understanding effort, impact, and capacityFinding the value in data and measurementCapacity defined: the gap between your effort and impact (the wider the gap, the better)The coach's capacity shows up in the coaching space (How much more is possible?)As a coach, where is your “ceiling”? (How can you lower the “noise”?)Lizette's Feel-Think-Do framework to “lower the noise”Helping our clients become more aware of their ceiling.Signs to listen for from your clients so you can take the right approachLizette's free tool, the Capacity Report CardLizette's biggest takeaway: “Capacity is your nervous system's bandwidth; it's not fixed, but it's trainable.”Resources:Connect with Dr. Lizette Warner: Website, LinkedIn, Power, Poise, and Presence book, Free Capacity Report Card, and Episode 339 with Dr. Lizette Warner.Connect with Meg:Explore our mentor program! Now enrolling for Fall 2026! Click here for more information!Learn more about the STaR Coach Community. We would love for you to join us!Explore past episodes and other resources at www.STaRcoachshow.com. Mentioned in this episode:Mentor ProgramIf you're working toward your ACC or PCC credential, or if it's time to recertify your ACC mentor, coaching isn't just a requirement on a checklist. It's one of the most transformative investments you can make in yourself and your coaching. I've taught or mentored over 2000 coaches, and I hear the same thing again and again. I came because I had to, and I am so glad that I did. Coaches tell me they walk away with renewed energy, deeper confidence and a community of peers who genuinely support each other. Here's what you need to know right now. Mentor coaching must span a minimum of three months, so the time to start is not when your credential is just about to expire. And if you complete your hours in 2026, you get ahead of the upcoming ICF changes, which means peace of mind along with skill development. My fall cohort is already filling up. Every group is capped at ten. It's small, personal, and powerful. If you've been waiting for the right time, this is it. So head over to Star Coach Show. That's https://starcoachshow.com/mentor/ to grab your spot or to learn more. I'd love to work with you. Now, let's get into today's show.
⚡️Click Here To Text Monique!What happens when you stop pushing through and give yourself permission to pause, reflect, and reset?Reflecting on her recent journey, Monique shares how easy it is to take for granted the practices that support her mental well-being amid the daily demands of motherhood, work, and personal commitments. After recognizing her own tendency to hold tightly to control, she discusses how this summer has become a season of slowing down and creating space to reassess what she needs.Throughout the episode, Monique highlights the struggle many women face in balancing ambition with self-care. She honestly shares her own experiences with burnout and the importance of stepping back to reevaluate priorities. With practical insights, she encourages us to find our own versions of rest and challenge the expectations that keep us constantly pushing.Because true success does not come from constant productivity alone. It also requires the courage to pause, reflect, and care for ourselves.GEMS DROPPED“Sometimes things just feel okay or good because they are. Like, the things on the surface or on paper are looking good. So that means you should be good. You don't feel bad. So therefore, that means you're good. And it's like, no. Something more is here. Something that you can't even totally predict or comprehend is available to you, but you can't conceive of more than what you can conceive of while you're still in motion in the way that you are.”“We busy ourselves with stirring because it makes us feel important, it makes us feel active, it makes us feel like we're doing something. And that's because our ego needs to feel it, not because there's any use in it at all.”“Just because your identity and the value that you have sort of set an expectation around, just because thus far it has been that of almost unlimited availability and the person who is the fixer, the problem solver, the handler, doesn't mean that it has to remain that way.”“You can rest by design. You can. You can be intentional and shift this proactively, as opposed to reacting to exhaustion and waiting for exhaustion to take you down.”STAY IN TOUCHCome and follow me on Instagram @moniquershields and I would love your feedback so send an email to ambition@moniquershields.com.
Amber Fuller is a substantive Deputy Principal, currently working as a HALT Talent Pipeline Advisor with the NSW Department of Education. She is a Highly Accomplished Teacher and serves as a committee member of the NSW HALT Association. Amber is committed to growing expert teacher capacity across the NSW public education system by supporting aspiring and accredited HALTs through innovative, practical approaches that embed the Australian Professional Standards for Teachers into everyday practice. She is passionate about teacher quality, professional learning, and developing teacher leaders who create lasting impact for students, colleagues, and schools.
If you're a woman over 40 who's exhausted by 3pm, craving sugar you can't explain, and wondering why you can't stay consistent no matter how much you know about nutrition, this episode is for you.In this episode, Kylie Pax unpacks the real relationship between adrenal fatigue, cortisol dysregulation, and self-sabotage. This isn't another episode telling you it's all in your head, and it isn't another one letting hormones take the blame for every skipped plan and every binge. Kylie introduces the Capacity vs. Character framework — a practical way to tell the difference between a genuine low-energy day and an old story hiding behind a diagnosis, plus the 3-Question Capacity Check you can run any time you feel yourself about to spiral.If you've ever said "I think it's my hormones" right before reaching for something you know isn't part of your plan, this episode gives you the tool to find out what's actually true.What You'll LearnWhy adrenal fatigue and cortisol dysregulation are real for women over 40 and perimenopausal women, and why that's still not the whole storyThe difference between capacity (what you have in the tank) and character (whether you keep your word anyway)The 3-Question Capacity Check: a practical framework to run before you quit on your planWhy "resizing" your standard beats abandoning it on a low-energy dayHow to treat sleep, protein, and stress management as identity-building acts of discipline, not excusesA real client example of applying this framework to break a nightly perimenopause binge cycleBOMBSHELL BLUEPRINT WEIGHT LOSS FOR EMOTIONAL EATERS
Most of us have been told, at some point or another, to just be happy. Just let it go. Just choose joy. And if you've tried that and found it completely unhelpful, you are in very good company. Dr. Peggy DeLong is back on the podcast for her third visit, and what she shares in this episode about how to increase your capacity for happiness is not what most people are teaching. It's not about ignoring what's hard. It's not about thinking positively until the feeling kicks in. And it has nothing to do with luck or your current circumstances. Peggy discovered the power of gratitude while sitting by her fiancé's side as he was dying from an aggressive cancer. She was 26. She didn't push the grief away. She felt it — and that turned out to be the beginning of everything she now teaches. If you've ever been told to just cheer up and wanted to throw something, this one is for you. WHAT YOU'LL LEARN Why pushing emotional pain aside actually makes it harder to access real happiness — and what to do instead How your capacity for joy is in direct proportion to your capacity to feel pain What collective effervescence is and why it matters more than we think How human connection with complete strangers predicts happiness just as much as our closest relationships What the three Ps — present, pleasure, and purpose — have to do with breaking the high-achieving cycle Peggy's four Ps for building positive mental health: prioritize, plan, practice, prosper DR. PEGGY'S FREE GIFTS FOR GAME ON GIRLFRIEND® LISTENERS Free: The Grateful Day — a Five Day Challenge with simple practices to build gratitude into daily life. Grab it here: https://drpeggydelong.com/thegratefulday/ 20% off Your Happy Second Half group coaching program. Use code mas at checkout: https://drpeggydelong.thinkific.com/courses/happy-second-half CONNECT WITH DR. PEGGY DELONG Website: https://drpeggydelong.com/ Your Happy Second Half: https://yourhappysecondhalf.com/ Love in a Bracelet: https://loveinabracelet.com/ Facebook: https://www.facebook.com/drpeggydelong/ Instagram: https://www.instagram.com/the.gratitude.psychologist/ LinkedIn: https://www.linkedin.com/in/drpeggydelongthegratitudepsychologist/ ABOUT DR. PEGGY DELONG Dr. Peggy DeLong, known as The Gratitude Psychologist™, is an internationally recognized expert in gratitude, positive psychology, mental health, and personal development. She helps individuals and organizations cultivate greater peace, joy, and fulfillment. With a Doctorate in Psychology and over 30 years of experience — including her work as a forensic psychologist conducting more than 4,000 evaluations — she brings a rare depth of insight, credibility, and practical wisdom to her work. She has partnered with leading institutions such as Princeton, Penn State, Rutgers, and major healthcare and corporate organizations to deliver transformational programs and experiences. As a speaker, author, therapist, and coach, Peggy is the creator of The Grateful Day™ and The Prioritize P.E.A.C.E. Method™, empowering people to move from overwhelm to clarity and emotional well-being. She is also the founder of multiple community-based initiatives and the Your Happy Second Half™ program, where she supports high-achievers in building meaningful connections, rediscovering joy, and living with renewed purpose. READY TO BUILD YOUR CONFIDENCE? There's a reason we talk about mindset and mental health on this podcast — because what's happening on the inside shows up directly in your business results. If this episode got you thinking and you're ready to look at what might be holding your business back, I'd love to spend 30 minutes with you. As my free gift to Girlfriends, I offer a 30-minute discovery call. We'll talk about where you are right now, what you want to build, and what might be getting in the way. Book here: https://app.acuityscheduling.com/schedule.php?owner=13047670&appointmentType=2244195 FREE GIFT FROM SARAH Get Sarah's Freedom Calculator and discover how much your business needs to make to finally be free. Download at https://sarahwalton.com/freedom LEARN FROM SARAH Explore Sarah's online courses and free resources to start building your business with confidence. Online Courses: https://sarahwalton.com/online-courses Free Resources: https://sarahwalton.com/free-resources CONNECT WITH SARAH Website: https://sarahwalton.com/podcast YouTube: https://www.youtube.com/@TheSarahWalton Instagram: https://instagram.com/thesarahwalton ABOUT SARAH WALTON Sarah Walton is a wealth consciousness coach, strategic advisor, podcast host, and mentor who helps women entrepreneurs build businesses they love. Her mission is simple: to put more money in the hands of more women. She's the creator of the Abundance Academy, The Art of Receiving, and the Game On Girlfriend® podcast. Sarah teaches authentic, heart-centered business strategies because when women have more financial power, they don't just keep it — they use it to take care of their families, support their communities, and build something bigger than themselves. RELATED GAME ON GIRLFRIEND® EPISODES YOU'LL LOVE Episode 45: Feeling Good with Dr. Peggy DeLong — https://sarahwalton.com/dr-peggy Episode 201: What It Means to Be an Adversity Warrior with Robin Osborn — https://sarahwalton.com/adversity-warrior/ Episode 293: Detours Are Inevitable, Suffering Is Not — https://sarahwalton.com/teenagers-taught-me-joy-doesnt-require-perfect-circumstances LOVE THE SHOW? LEAVE US A REVIEW! Thank you so much for listening. I'm honored that you're here, and I'd be grateful if you could leave a quick review on Apple Podcasts by clicking here, scrolling to the bottom, and clicking "Write a review." Your reviews help other women entrepreneurs find the show and get the support they need to build businesses they love. Thank you for being part of the Game On Girlfriend® community! (If you're not sure how to leave a review, you can watch this quick tutorial.)
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Diving into the story of a handful of women who broke the social norms in aviation during the 1920s and 1930s-----Sources: Fly Girls - Keith O'Brien-----:30 - Make Yourself Proud10:30 - Ruth Nichols: Relinquish yourself from the world16:30 - Capacity for criticism18:20 - "Make your atom count."19:36 - Frances Grayson transatlantic attempt: Risk vs consequence25:30 - Amelia Earhart: her first attempt, the importance of self-satisfaction30:20 - The national air races + the battle for opportunity35:10 - Be a thorn36:20 - The cost/burden of challenging 41:40 - Prepare for a long fight42:40 - Ruth Nichols - overlooking the small details45:02 - The grudge flight47:20 - More breakthroughs, more battles. 55:45 - Louise Thaden: speed with safety58:38 - Plant some trees
This week, we catch up with Sam Droege with the US Geological Survey and Clare Maffei with US Fish and Wildlife Service to discuss the origins and evolution of the Bee Lab and its role as a support hub for bee biodiversity work. Sam describes shifting from designing national monitoring programs for birds and other taxa to pollinators, finding bee monitoring statistically difficult due to high year-to-year variance and identification bottlenecks, and pivoting to developing sampling techniques, the Very Handy Bee Manual, Discover Life online ID guides, photography resources, and a large specimen database with substantial backlog. Claire outlines her path through a US Fish and Wildlife Service pollinator fellowship into a refuge-support role, producing updated bee inventory/monitoring frameworks and protocols, data management, and publishing over 500,000 records to GBIF. Together they emphasize collaboration with students, refuges, parks, and researchers, training via weekly livestreamed bee ID videos, and ongoing method development (e.g., emergence trapping, brine in traps, hanging shrub traps) while noting funding uncertainty and focusing on practical conservation through plant–bee relationships and better baseline data. Bee Lab website: https://www.usgs.gov/centers/eesc/science/usgs-bee-lab-eastern-ecological-science-center
Get the book, Cultivate and Activate: Building Teacher Capacity for Instructional Leadership Guest Host: Barbara Blackburn Barbara Blackburn, PhD is the author of more than 40 books and a full-time consultant who works with schools around the world to help raise the level of rigor and motivation for professional educators and students alike. Dr. Blackburn has been repeatedly named to the Top 30 Education Gurus and Top 10 Professional Development Programs by Global Gurus. See all of Dr. Blackburn's guest appearances on Principal Center Radio About The Guests: Keith Fickel & Justin Baeder Keith Fickel is a retired middle school and high school principal in the southwest Houston, Texas, area. His focus during his decade as principal was to ensure that high levels of student learning, achievement, and personal development occurred in every classroom, every day. He accomplished these aims through the intentional empowerment of teachers and staff to effectively lead not only their classrooms but the school as a whole. Keith prioritized building and maintaining a strong bond with the school community through trust during his principalship. He began his career in education in 1991, serving first as a classroom teacher and a band director for seventeen years, then as an assistant principal, associate principal, and campus principal during the second half of his career. His entire educational career was at the secondary level in both private and public school settings. Keith has facilitated or cofacilitated professional learning sessions at the district, regional, and state levels on a variety of topics. He is a member of the Texas Association of Secondary School Principals and ASCD. In 2008, he was a campus Teacher of the Year, as well as a finalist for the Fort Bend ISD Secondary Teacher of the Year. In 2022, he was named the Fort Bend ISD Secondary Principal of the Year, and he had the honor of serving as the founding principal of the district's newest high school in 2023, prior to his retirement. Keith earned both a bachelor's degree and a master's degree in music education from Texas Tech University, and he completed his principal certification through the University of Houston. He resides in Sugar Land, Texas, with his wife, Anne, who was also a music teacher. Together, they have an adult daughter who is also in education. Justin Baeder, PhD, is director of the Principal Center, where he helps school and district administrators build capacity for instructional leadership. Driven by the belief that leaders belong in classrooms, he created the Instructional Leadership Association to help school leaders confidently get into classrooms every day, have feedback conversations that change teachers' practice, and discover their best opportunities for school improvement. The Instructional Leadership Association now has thousands of members in more than forty countries. Prior to starting the Principal Center, Justin served as a teacher, head teacher, and principal in Seattle Public Schools, finishing his ten-year career in Seattle as principal of Olympic View Elementary. He has contributed to School Administrator, Principal, Principal News, Principal Navigator, and Education Week. Justin presents regularly at state and national conferences, including ASCD, Learning Forward, and the National Association of Elementary School Principals, and has spoken at numerous in-person professional learning events in the United States, Canada, and El Salvador, as well as at countless virtual events. Justin holds a PhD in educational leadership and policy from the University of Washington, where he is a graduate of the Danforth Educational Leadership Program. He holds a master of education degree in curriculum and instruction from Seattle University and a bachelor's degree in science education from Harding University. He resides in Heber Springs, Arkansas, with his wife, Amy, and two daughters, Vivienne and Genevieve. To learn more about Justin's work, or to contact Justin, visit PrincipalCenter.com or follow @eduleadership on X. Episode Sponsor This episode of Principal Center Radio is sponsored by IXL, the most widely used online learning and teaching platform for K-12. Discover the power of data-driven instruction in your school with IXL—it gives you everything you need to maximize learning, from a comprehensive curriculum to meaningful school-wide data. Visit IXL.com/center to lead your school towards data-driven excellence today.
The Human Equation with Joe Pangaro – Ultimately, the United States must maintain controlled, lawful immigration to remain stable and prosperous. We can welcome newcomers—millions do so legally every year—but we cannot simply accommodate everyone who wants to come here. No nation can. Borders exist for a reason: to regulate the flow of people so that society remains...
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“Meet your clients where they're at” sounds like good coaching advice… but is it always?In this episode, Jeremiah and Coach Natalie discuss the difference between supporting a client and enabling the same patterns that are keeping them stuck.We talk through when a coach should take things slow, when it's time to push harder, and why real progress often requires getting uncomfortable.Because the goal of coaching isn't to keep you where you are. It's to help you change.Timestamps00:00 Meeting Clients Where They Are03:04 The Balancing Act of Coaching05:58 Understanding Client Needs and Goals08:59 The Importance of Meal Plans11:51 Execution Over Macros15:11 Teaching Skills for Success17:51 Capacity for Change in Clients20:54 Strategies for Beginners24:07 Long-Term Client Transformations29:51 Client Readiness for Change32:20 Building Confidence in the Gym35:34 Challenging Comfort Zones39:44 The Importance of Feedback46:44 Coaching Beyond Comfort ZonesLinksApply for Coaching: https://form.typeform.com/to/ubUfJiEu?utm_source=podcastLiving Lean Podcast: https://www.buzzsprout.com/712032Follow Jeremiah on Instagram: https://www.instagram.com/jeremiahbair/Follow Andrea on Instagram: https://www.instagram.com/andirogersfit/Follow Natalie on Instagram: https://www.instagram.com/natalieatswell/Keywordscoaching, client progress, meal plans, nutrition, behavior change, fitness, coaching strategies, client goals, individualized coaching, capacity for change client readiness, gym confidence, feedback, coaching, comfort zone, nutrition, exercise selection, personal training, mindset, client progressTo Apply For Coaching With Our Team: CLICK HERE
Enrollment for The Creation Lab is now open! The Creation Lab is a 40-day challenge to help you start, finish, and move your ideas into the world through structure, accountability, co-working, and community! Join us HERE What if confusion isn't a sign that something is wrong but a sign that something new is trying to emerge? Today Sarah is sharing an excerpt from a live coaching call from the Moon Studio's Secret Studies: Intuition course where she explores what confusion actually is. Through reflections on emotional patterns, intuition, capacity, boundaries, and transformation, Sarah offers a framework for moving through seasons where life feels unclear. On this episode of Moonbeaming you'll hear: The difference between avoidance-based confusion and transformational confusion Why uncertainty can sometimes signal growth instead of being a problem to solve How emotional triggers can reveal old wounds and opportunities for healing The role of capacity, compassion, and self-awareness during seasons of change Why making space can be more important than making immediate decisions How to anchor into the version of yourself that's trying to emerge What it means to trust the intuition of right now instead of old patterns How to move through change without abandoning yourself This episode is for anyone feeling uncertain about what comes next in life. --- Join Our Community: Join the Moon Studio Patreon: https://www.patreon.com/themoonstudio Buy the 2026 Many Moons Lunar Planner: https://moon-studio.co/products/many-moons-2026?srsltid=AfmBOopThx1yrmKl0tMjecc_EFeeN5DAiIafqPqvQ4Uke1WEi5droeam Subscribe to our newsletter: https://moon-studio.co/pages/newsletter Find Sarah on Instagram: https://www.instagram.com/gottesss/
In Episode 6 of Erin's Expansive Series we'll explore a vital element for anyone who is on a journey of expansion: Capacity. Capacity is your ability to hold more in life. More money, more joy, more uncertainty, more success. More of anything that needs to be held to expand your life. Today we'll talk about how to grow capacity in a way that is sustainable and regulated. Answer these questions on your quest to increase capacity in your life: Where are you abandoning yourself in order to keep people comfortable? Where are you saying ‘yes' when every part of you wants to say ‘no'? Where are you carrying something that actually belongs to someone else? Where have I stopped using my voice because it's easier to stay quiet? What support have I convinced myself I shouldn't need? What needs of my own have I decided are negotiable? The podcast title is going to change again! Do you have a guess of what the new title will be? Send your guess in a DM to @erintreloar! If you're ready for expansion and want to do it within an incredible community of women, join us inside of The Expansive Mastermind. Subscribe to the podcast to make sure you never miss an episode. Connect with Erin:Instagram Website Support Our Sponsors: BIOOPTIMIZERS - Get 15% off any order by visiting https://bioptimizers.com/erinJONES ROAD BEAUTY - Get a free Cool Gloss on your first purchase when you use the code ERIN at checkout https://www.jonesroadbeauty.com/TUMBLE RUGS - Get 10% plus free shipping by visiting https://www.tumbleliving.com/erinHELLOFRESH - Go to hellofresh.ca and use the code RAWBEAUTYTALKS for 50% off your next order. KNIX - Go to knix.com and use code RAWBEAUTYTALKS for 20% off your next order.MITOPURE GUMMIES - Go to Timeline.com/ERIN and use the code ERIN for 20% off. LOLA BLANKETS - Go to LolaBlankets.com and use the code RAWBEAUTYTALKS for 35% off. SUPERBELLY POWDERS - Go to www.itsblume.com and use code RAWBEAUTYTALKS for 15% off.AQUTRU WATER FILTERS - Go to www.aquatru.com and use code RAWBEAUTYTALKS for 20% off. Please use link on left side of checkout page, not the coupon code box on the right. COWBOY COLOSTRUM - Use code RAWBEAUTYTALKS at CowboyColostrum.com for 25%offLeave Well Within a rating and a review on Apple Podcasts! See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
A Parenting Resource for Children’s Behavior and Mental Health
If you're stuck wondering why consequences aren't working for your dysregulated child, you're not alone. Learn what's really driving behavior and how to create change. With her Regulation First Parenting™ approach, Dr. Roseann Capanna-Hodge helps families turn dysregulation into growth. You've tried consequences. You've stayed consistent. And yet… nothing sticks. You're not alone. In this episode, we unpack why consequences aren't working for your dysregulated child—and what actually creates lasting change when behavior keeps repeating.Why do consequences not work for my child's behavior?If consequences were going to work, they already would have.The missing piece? Regulation.When your child's brain is dysregulated, it's not available for learning—no matter how consistent or “correct” your discipline is.Behavior only improves when the brain is regulatedConsequences may stop behavior temporarily—but don't break patternsIt's not bad parenting—it's a dysregulated brainThink about it: You give a consequence, things calm down… and then the same meltdown shows up again tomorrow.Example: Your child loses screen time for backtalk. They stop—for now. But the next day? Same pushback, same struggle. That's not defiance—it's dysregulation.Why does my child keep repeating the same bad behavior?Because you're addressing behavior, not the nervous system driving it.When kids are in fight, flight, or freeze, their brain is in survival mode. That means:No learning is happeningLogic doesn't landCorrection can escalate the situationIt feels like Groundhog Day for a reason.Behavior = communicationMeltdowns = nervous system overloadRepetition = unresolved dysregulationYou're not doing it wrong—you're just doing it in the wrong order.How do I discipline a child who is emotionally dysregulated?Let's calm the brain first. Everything follows.A simple framework—CALMS—changes everything:C – Co-regulate first: Lower your voice, pause, stay steadyA – Avoid personalizing: It's not disrespect—it's dysregulationL – Look for root causes: Fatigue? Sensory overload? Stress?M – Model coping: Show your child how to regulateS – Support effort: Catch progress, not perfectionExample: Instead of immediately correcting yelling, you pause, soften your tone, and help your child settle. Then you teach.That's the shift: Regulation first, then teaching.Want to stay calm when your child pushes every button? Become a Dysregulation Insider VIP and get the FREE Regulation Rescue Kit—your step-by-step guide to stop oppositional behaviors without yelling or giving in.Go to www.drroseann.com/newsletter and grab your kit today.What actually helps my child change their behavior long-term?Not fear. Not punishment. Capacity.When kids feel supported and regulated, they build the ability to:Problem-solve without melting downHandle stress without shutting downLearn from mistakes instead of repeating themYou'll start to notice:Slower escalationFaster recoveryLess defensivenessThat's real progress—not just compliance.
Rates are spiking and the scary part is why. We kick off with a June truckload market update built on real broker payment data, then we zoom in on what the numbers are actually saying: van, reefer, and flatbed buy rates are surging year over year, but freight demand is not the headline. Capacity is. Enforcement pressure, compliance friction, and a permanently higher cost floor are squeezing the supply side, and that changes how you price, how you source trucks, and how you talk to customers.Liz Wayne, CEO of Able Transport Solutions, joins me for a grounded look at flatbed and heavy haul logistics. We talk about why open-deck freight is harder to execute, how rare equipment like multi-axle RGNs can turn a single mistake into a massive TONU, and why proactive communication is the real “margin protection” strategy. We also get honest about the truck in hand myth, what shippers should actually expect from a broker, and the mindset of never giving loads back.We go beyond ops into leadership and strategy: staying focused as a founder, building systems that prevent half-finished initiatives, and learning to delegate without losing standards. We also dig into the Supreme Court negligent hiring landscape and what it means for carrier vetting, shipper contracts, indemnity clauses, and risk. Finally, we hit AI in logistics, back-office automation, and why data center construction may be a quiet demand engine for flatbed freight.Subscribe for more real freight operator conversations, share this with a teammate, and leave a review with the one guest or industry challenge you want us to break down next.Follow The Freight Pod and host Andrew Silver on LinkedIn.Thanks to our sponsors:Cloneops.ai: Not just AI. Industry-born AI.cloneops.aiBitfreighter: Scale Freight. Not Integration Costs. Win More. Accept More.bitfreighter.comTriumph: Accelerate quote-to-cash with AI-powered invoicing, bank-grade carrier payments, and transaction-based market intelligence.triumph.io/morecapacity
Welcome to Avory Around the Desk Podcast... Sean Emory, Founder and CIO of Avory & Co., asks whether prediction markets like Kalshi are really about betting, or whether they could expand society's capacity to transfer risk. Using Florida's hurricane insurance crunch, the Generac hedge, and AI-enabled micro-insurance, he argues insurance is capacity, and technology may finally be able to expand it. Chapters00:00 Welcome and setup01:19 Why prediction markets matter02:49 Markets as information engines05:55 From betting to bigger thesis07:17 Insurance prices uncertainty09:28 Capacity and risk transfer11:41 Florida hurricanes case study13:06 Hedging with opposite exposures15:04 Micro risks and AI automation18:31 Tech stack enables new markets21:15 Liquidity, market makers, regulation22:56 Wrap up and key takeawayDisclaimerThis conversation is for educational and informational purposes only. Nothing discussed is personalized investment, legal, tax, or insurance advice. Views reflect our thinking as of the recording date and may evolve as new information becomes available. Do your own research and consult a qualified professional before making financial decisions.More at avoryfunds.com
Mark Unruh is an associate professor of population health sciences at Weill Cornell Medical College. Stephen Morrissey, the interviewer, is the Executive Managing Editor of the Journal. M.A. Unruh, V. Mor, and H.-Y. Jung. Colliding Forces — The Aging of the Baby Boom Generation and Contracting Nursing-Home Supply. N Engl J Med 2026;395:105-107. A.R. Olenski and D.C. Grabowski. Caring for an Aging America — The Looming Crisis of the Long-Term–Care Workforce. N Engl J Med 2026;395:107-110.
Send us Fan MailIn this personal solo episode of Call Me CEO, Camille shares the unexpected lessons she learned during a year filled with major family transitions, health challenges, and a complete re-evaluation of what success really means.After a health crisis landed her in the emergency room last fall, Camille was forced to slow down, ask for help, and confront the reality that pushing harder wasn't the answer. Through navigating motherhood, business ownership, physical recovery, and emotional processing, she discovered that growth doesn't always look like expansion. Sometimes it looks like simplifying, healing, and learning to listen.In this episode, Camille shares:• Why growth sometimes feels like being stripped down instead of building up• The health scare that changed how she approaches work and life• Managing personal capacity and learning to say no• The challenges of navigating multiple family transitions at once• How breathwork became a powerful tool for emotional processing• What low iron, vitamin deficiencies, and hormone health taught her about wellness• The importance of getting blood work and understanding your body's unique needs• How she uses her Oura Ring to track sleep, stress, and recovery• Why clarity creates confidence in both life and business• The surprising power of slowing down and receiving supportWhether you're navigating a difficult season, feeling overwhelmed, or simply trying to balance business and family life, this episode serves as a reminder that your health, energy, and well-being matter.Connect with Camille:Website: camillewalker.coPodcast: Call Me CEOInstagram: @callmeceopodcast
In this personal mid-year reflection episode, Jess shares the 3 biggest lessons she's learned in 2026 about capacity, leadership, decision-making, business growth, nervous system regulation, and sustainable success. This episode is a behind-the-scenes look at what it actually takes to grow a business, expand your life, and lead at a higher level without waiting to feel fully ready first. Jess opens up about: Navigating IVF while simultaneously scaling her business The mindset shift that helped her stop choosing between business success and personal fulfillment Why capacity is a choice and expands after decision, not before it How indecision was slowing down her business growth more than strategy ever was The concept of "failing faster" and making decisions with less hesitation Why CEOs and coaches bottleneck their growth by waiting too long to move The connection between nervous system regulation, leadership, and sustainable success Her ongoing struggle with rest, slowing down, and creating more space for recovery Jess also shares practical shifts she's making in real time, including restructuring her schedule, protecting more personal time, getting off social media more intentionally, and learning how to emotionally experience the freedom she has worked so hard to create. If you are an entrepreneur, coach, leader, or high achiever who feels stretched between ambition, growth, healing, relationships, and personal goals, this episode will help you. This conversation is honest, strategic, reflective, and deeply grounded in the realities of building a bigger life and business without abandoning yourself in the process. 1-1 Trauma-Informed Coaching: www.chatwithjess.com Apply to The Art & Skill of Coaching: www.chatwithjess.com FREE Guide- 50 Trauma Informed Coaching Questions: https://jessicademarchis.myflodesk.com/50questions Stay in Touch: www.jessicademarchis.com IG @jess_demarchis_coaching
Watch Coach Ben outline a full program for an athlete who struggled with getting out of breath during Double Unders in her CrossFit workouts.» Watch on YouTube: https://youtu.be/JRxReIe4_Og» Free Educational Content: https://zoarfitness.com/articles» Hire a Coach: https://www.zoarfitness.com/coach/» Shop Programs: https://www.zoarfitness.com/product-category/downloads/» Follow ZOAR Fitness on Instagram: https://www.instagram.com/zoarfitness/Support the show
Brett Suma, President and COO of Bot Auto, joined Grayson Brulte on The Road to Autonomy podcast to discuss Bot Auto's playbook for autonomously driving one billion autonomous miles in four years.On April 29th by completing its first humanless run from Houston to Dallas. To achieve long-term growth and commercial success, Bot Auto is rejecting the standard driver-as-a-service intermediary model used by its competitors. Instead, the company is building direct relationships with shippers and designing a utility grid of capacity focused on solving network sequencing, lane selection, and utilization.As the company focuses on capital-efficient deployment, Bot Auto plans to sidestep raising large funding rounds to purchase depreciating operations assets. Instead, the company will rely on traditional financing methods, established banking relationships, and an experienced sales force to scale its tractor and trailer counts. With a comprehensive five-year financial roadmap in place, Bot Auto is positioning itself to scale organically based on market demand, setting a disciplined target of one billion autonomous miles within the next four years.Episode Chapters0:00 Why Bot Auto4:56 April 29th Humanless Houston to Dallas Run9:52 Economics of Humanless Miles14:36 Building a Trucking Business17:17 Capacity as a Utility Grid, Not Truck Counts24:19 Bot Auto's Business Model29:34 CapEx and Financing Trucks32:15 Hidden Risk of Operating a Mixed Fleet41:49 Staying Disciplined as Bot Auto Grows44:24 One Billion Autonomous Miles in Four Years47:36 AUTNMY AI--------About The Road to AutonomyThe Road to Autonomy is the leading applied intelligence platform covering the convergence of automation, autonomy, and the Autonomy Economy.™.Through our podcasts, newsletter, Indices and proprietary applied intelligence, we set the narrative for institutional investors, industry executives, and policymakers navigating the convergence of automation, autonomy, and economic growth.Join institutional investors and industry leaders who read This Week in The Autonomy Economy every Sunday. Each edition delivers exclusive insight and commentary on the autonomy economy, helping you stay ahead of what's next.Sign up for This Week in The Autonomy Economy newsletterFollow The Road to Autonomy IndicesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Have you ever asked God to help you grow in a specific area, only to doubt that He could come through for you? I know how easy it is for fear to creep in when you're asking for more, but if you're ready to see abundance and overflow at work in your life, you'll have to first believe that it's possible. In this episode of the podcast, I share my strategy for partnering with God in the process of expanding my capacity. Prepare to position yourself for all that God has for you. Highlights from Today's Episode Believing God for more Being in the right rooms Embracing boundaries Related Resources Ready to receive all that God has for you? Listen to this podcast episode and learn how to make room for overflow. Need even more encouragement? This podcast episode with Cassandra Speer is your reminder that abundance is here. Grab my Daily Tracker to begin setting limits and maximizing your time. CLICK HERE FOR FULL SHOW NOTES The post #578 – How to Expand Your Capacity for What God Has Next first appeared on Chrystal Evans Hurst.
Psalm 92:14 says of the righteous, “They still bear fruit in old age; they are ever full of sap and green.” That's a beautiful picture of faithfulness across every season of life. And it gives us an important reminder: when it comes to retirement, Scripture invites us to think beyond escape. For many people, retirement is pictured as the finish line. Work hard, save diligently, invest wisely, and one day you'll finally arrive at a season of leisure—no alarm clocks, no deadlines, no demands. And after decades of work, rest is a good gift. There's nothing wrong with enjoying a slower pace, spending more time with family, traveling, or having more flexibility in your schedule. But Scripture gives us a deeper vision for our later years. Retirement may change the rhythm of our lives, but it does not end our calling as stewards. When Retirement Feels Disorienting Many people reach retirement and find themselves asking, “Now what?” Without the familiar structure of work, the transition can feel surprisingly difficult. For years, your calendar, responsibilities, relationships, and even your sense of purpose may have been shaped by your vocation. When that changes, it can feel like something has been lost. But in God's kingdom, no season is wasted. Retirement may bring changes in schedule, income, health, energy, and responsibility. But it also brings new opportunities to serve, invest in others, and bear fruit in ways that may not have been possible during busier working years. That's why the question is not simply “What am I retiring from?” The better question is, “What am I now free to do for the glory of God?” Moving From Labor to Legacy We see a helpful picture of this in Numbers 8. The Levites were instructed to begin their service in the tabernacle at age 25 and then transition at age 50. But they didn't stop serving altogether. They stepped back from certain forms of labor, but they continued to assist and minister to their brothers. In other words, they didn't retire from purpose. They moved from labor into legacy. That's a helpful way to think about our later years. As we age, certain types of work may no longer be possible. Energy changes. Capacity changes. Responsibilities change. But our purpose in God's kingdom does not expire. The same hands that once built, typed, managed, served, or led can now mentor, teach, encourage, pray, and support. The same heart that once poured itself into a career can now pour itself into people. Maybe that means volunteering with a ministry that reflects your passions. Maybe it means mentoring young professionals or young parents. Maybe it means serving more faithfully in your church, caring for aging parents, helping with grandchildren, or simply being more available to encourage others. Whatever the expression, the heart of stewardship remains the same: offering your time, wisdom, experience, and resources for the glory of God. Faithful Presence Matters Think of Simeon and Anna in Luke 2. Both were advanced in years, and yet both were living with expectancy and devotion. Simeon was righteous and devout, waiting for the consolation of Israel. Anna worshiped with fasting and prayer, night and day. Their lives remind us that faithful presence is a powerful gift. God does not retire His servants. He repurposes them. That does not mean retirement has to be frantic or overfilled. This is not about proving your value through constant activity. In God's economy, usefulness is not measured by productivity, but by faithfulness. That's a word many of us need to hear. Our culture often measures significance by title, output, income, and visible achievement. But God sees differently. He sees the quiet prayer, the faithful encouragement, the wisdom shared across the table, the hospitality, the generosity, and the steady presence in the life of a child, a neighbor, a church member, or a younger believer. Those things may not always make headlines, but they matter deeply in the kingdom of God. Stewarding the Freedom Retirement Brings If you're approaching retirement, one of the wisest questions you can ask is not merely “What am I done with?” but “What am I now free to do?” And if you're already retired, perhaps today is an opportunity to revisit that question. What experience has God entrusted to you? What wisdom has He formed in you? What time do you have now that you didn't have before? What relationships could be strengthened? What people could be encouraged? What ministry could be supported? Those are not leftovers. They are stewardship opportunities. Retirement may look different from your working years, but it is no less important. In fact, it may become one of the most spiritually rich chapters of your life if you choose to steward it well. So don't simply retire from something. Retire to something. Retire to deeper fellowship with Christ. Retire to greater availability for others. Retire to prayer, encouragement, generosity, service, and wisdom. Retire to a life that continues to bear fruit. Our Ultimate Treasure Our devotional, Our Ultimate Treasure: A 21-Day Journey to Faithful Stewardship, is designed to help you slow down, open God's Word, and consider what it means to treasure Christ above all else in every season of life. You can place your order today at FaithFi.com/Shop. And if you'd like to go through it with your church or small group, we offer bulk discounts. On Today's Program, Rob Answers Listener Questions: I'm retiring from my government job on July 31 and have money in the TSP. Should I leave it there, roll it into a traditional IRA, or consider a Roth IRA? I'd also like to take some cash out for home repairs. What's the wisest way to handle this? A few months ago, the company managing my retirement fund had a data breach, so I signed up for two years of free monitoring through Kroll. Now my bank has notified me of another breach and is offering 12 months of free monitoring through CyEx. Is CyEx reputable, and is it okay to have two different monitoring services at the same time? I lost my job yesterday after nearly 10 years. I'm 70 and already receiving Social Security, while my wife is 64 and not yet eligible for Medicare. I have a 401(k) and stock share accounts from my former employer, along with a rollover IRA I opened years ago. Given our income and health insurance situation, should I roll those accounts into my existing IRA? I own some individual stocks that are essentially worthless. I placed a sell order at about half a cent, but no one is buying. What should I do with these shares, and how can I properly document the loss for tax purposes? Resources Mentioned: Faithful Steward: FaithFi's Quarterly Magazine (Become a FaithFi Partner) Christian Healthcare Ministries (CHM) Healthcare.gov AnnualCreditReport.com | Credit Karma Our Ultimate Treasure: A 21-Day Journey to Faithful Stewardship by Rob West Wisdom Over Wealth: 12 Lessons from Ecclesiastes on Money Look At The Sparrows: A 21-Day Devotional on Financial Fear and Anxiety Rich Toward God: A Study on the Parable of the Rich Fool Find a Certified Kingdom Advisor® (CKA) FaithFi App Remember, you can call in to ask your questions every weekday at (800) 525-7000. Faith & Finance is also available on Moody Radio Network and American Family Radio. You can also visit FaithFi.com to connect with our online community and partner with us as we help more people live as faithful stewards of God's resources. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
"We need to evolve from procurement professionals into business leaders with procurement expertise." - Israel Santiesteban, Former Chief Procurement Officer and Head of Supply Chain The next evolution of procurement is about so much more than cost savings. With new digital tools and relentless business change, leaders are being asked to deliver value in new ways and, as a result, develop talent for roles that didn't exist a few years ago. In this episode, Philip Ideson speaks with Israel Santiesteban, a former CPO and supply chain leader with experience across Danone, Kraft Heinz, Schreiber Foods, and more, who's spent decades delivering end-to-end transformation in fast-moving sectors. They discuss what it really takes to unlock the power of data and AI, and why the next generation of procurement jobs will look very different. Israel also opens up about the risks and opportunities of working with startups, the reality behind scenario planning, and why high-performing teams need to shift from transactional work to strategic value-creation. In this episode, Israel also discusses: -How to cut through the hype and use AI for quick wins in neglected indirect spend -Discovering how CPOs can partner with startups for tailored solutions -Ways to move from reactive firefighting to true predictive scenario planning -The importance of building new procurement roles that blend digital fluency with business acumen -Rethinking procurement metrics that show value, not just savings Links: Israel Santiesteban on LinkedIn: https://www.linkedin.com/in/israel-santiesteban-43627b1b/ Subscribe to the AOP Newsletter: https://resources.artofprocurement.com/art-of-procurement-podcast-subscribe Subscribe to Art of Procurement on YouTube: https://www.youtube.com/@ArtofProcurement
Anatol Lieven discusses Vladimir Putin's public admission that Ukrainian drone strikes are causing significant difficulties and a loss of refining capacity. While Putin remains in charge, he faces pressure from hawks and doves regarding escalation. Despite successful drone campaigns, the battlefield in the Donbass remains stagnant. (7)1918 ROSTOV ON DON
Have you ever felt like you were walking through quicksand every single day in your business? Like you were taking three steps forward and two steps back no matter how hard you worked? That was Tim Calise's life for years, and it might be yours right now too. In this episode of The Happy Hustle Podcast, I brought in Tim Calise for our AI Masterclass Workshop during our Happy Hustle Club meeting, and I sat down to soak up everything he's learned about scaling with artificial intelligence. Tim's path has been anything but a straight line. He started a late night snack delivery business in college, recruiting his fraternity brothers to help him hustle. From there he launched a hedge fund in his early twenties and had to give it all back right before the 2008 crash. He got into fitness and technology after that, joining Alex and Layla Hormozi at Gym Launch, where his team took the company from zero to 35 million dollars in revenue in under a year and a half, then added two more businesses worth over 50 million a year on top of that. Eventually he moved to Nashville, met his current business partner, the guy who actually created the technology behind Apple Pay, and now runs a house of brands company that spans compliance, auditability, and moving money around the world. Tim is a husband of 18 years, a father of three, and he's built a team of about 160 people around the globe that operates 24 hours a day. His company will do around 5 billion dollars in turnover this year, and they've been in business for less than 18 months. I wanted Tim on this stage because he's not talking theory. He's talking about what he is literally doing right now to run a company at this scale without burning himself out or losing time with his family. That's the whole point of the Happy Hustle. Build something big without sacrificing the people and the life that matter most. Here's what stuck with me most from his talk. AI is not just a better tool, it's a fifth form of leverage. Tim broke down the four types of leverage that have driven wealth for the past 200 years: labor, capital, code, and content. Each one takes time, money, or both to build. AI is different. It's permissionless, you don't need to ask anyone, and once you deploy it, it keeps working for you. Capacity outpacing sales is a good problem to have. Most businesses bleed money because they build out people and systems before the revenue shows up. Tim's team flipped that. They have more opportunity than people right now, and AI is what lets them architect for the future they already know is coming. His team built an agent that hunts for clients around the clock. It crawls the internet looking for nuanced signals, like specific plugins on a website, that flag a great fit client. It scores leads automatically and populates their CRM without a human touching it. One of those messages landed a call with a company doing a billion and a half dollars a year in revenue, and Tim's team didn't even know the message went out until the reply came in. The real win isn't the revenue, it's his time back. Tim was honest about the years he spent fighting an uphill battle in business, never having the right tools. Now he says his marriage is in the best spot it's ever been, and he can spend time with his kids on his own schedule instead of whatever time was left over. Humans still run the show. Even with agents doing the heavy lifting, Tim's principle is simple. The agent does the work, humans stay informed and empowered, and every exception gets handled at the people level. AI replaces busy work, not judgment. If you're building something and you feel like you're stuck in that same quicksand Tim described, this conversation is going to hit different. Go listen to the full episode at https://caryjack.com/podcastin/. It just might be the reset you didn't know you needed. Connect with Timhttps://www.facebook.com/timcalisehttps://www.instagram.com/tim.calise/https://www.youtube.com/@timcalise/featuredhttps://www.linkedin.com/in/tcalise/https://www.tiktok.com/@timcalise?is_from_webapp=1&sender_device=pc Find Tim on this website: https://timcalise.com/about-me Connect with Cary!https://www.instagram.com/caryjack/https://www.facebook.com/SirCaryJackhttps://www.linkedin.com/in/cary-jack-kendzior/https://twitter.com/thehappyhustlehttps://www.youtube.com/channel/UCFDNsD59tLxv2JfEuSsNMOQ/featured Get a copy of his new book, https://www.thehappyhustle.com/book Sign up for The Journey: 10 Days To Become a Happy Hustler Online Course @ https://thehappyhustle.com/thejourney/ Apply to the Montana Mastermind Epic Camping Adventure @ https://thehappyhustle.com/mastermind/ “It's time to Happy Hustle, a blissfully balanced life you love, full of passion, purpose, and positive impact!” Episode Sponsors: If you're feeling stressed, not sleeping great, or your energy's been kinda meh lately—let me put you on to something that's been a total game-changer for me: Magnesium Breakthrough by BiOptimizers. This ain't your average magnesium—it's got all 7 essential forms that your body needs to chill out, sleep deeper, and feel more balanced. I take it every night and legit notice the difference the next day. No more waking up groggy or tossing and turning all night If you're ready to sleep like a baby, calm your nervous system, and optimize your recovery, go grab yours now at https://www.bioptimizers.com/happy and use code HAPPY10 for 10% OFF. =================================================================== My Green Mattress If you've been waking up with back pain, feeling stiff, or just not getting that deep, quality sleep. This might be what you're missing: My Green Mattress. It's made with clean, non-toxic, and eco-friendly materials, so you're not just sleeping better, you're sleeping healthier too. The comfort and support are on another level, and you can really feel the difference night after night. 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Comedian Aaron Chen may be known internationally for his role on the hit Australian TV series Fisk, but he's been a working stand-up since the age of 15. In fact, he might be the only Working It Out guest who learned to drive commuting to and from comedy clubs with their dad. Now he's got a hit Netflix special, Funny Garden. This week, Aaron sits down with Mike to discuss his journey from the suburbs of Sydney to opening for Ali Wong to headlining his own shows across the world. Plus, Aaron and Mike open up about the instances early in their careers when they regrettably lashed out at audiences, and how they became more adept at navigating difficult shows. Please consider donating to Food Bank For NYC. Mike's tour dates: https://www.birbigs.com/tour-dates Text BIRBIGS to 917-444-7150 for updates Find Mike: Website: https://birbigs.com/ Instagram: https://instagram.com/birbigs/ Facebook: https://facebook.com/birbigfans TikTok: https://tiktok.com/@mikebirbiglia Find Aaron: Instagram: https://www.instagram.com/chennylifestyle/ Website: https://www.aaronchencomedy.com Hosted and Produced by Mike Birbiglia Producers: Peter Salomone, Joseph Birbiglia, Mabel Lewis, Gary Simons Sound Mixed by Shubh Saran Supervising Engineer: Kate Bilinski Video Consultant: Graham Willoughby Special Thanks: Marissa Hurwitz, Josh Upfal, David Raphael, Nina Cwik, J. Hope Stein, Oona Music: Jack Antonoff and Bleachers Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
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