Podcasts about Roth

Schedule a Free Financial Assessment with an experienced professional:https://purefinancial.com/lp/free-assessment/?utm_source=captivate&utm_medium=podcast&utm_campaign=free-assessment&utm_content=ymyw-pod-ep592-description-free-assessmentMichael, K & J, and Tracy all need retirement spitballs and Roth conversion plans, but they didn't share one of the most important numbers in retirement planning: how much they actually want to spend. Today on Your Money, Your Wealth® podcast number 592, Joe Anderson, CFP® and Big Al Clopine, CPA reverse-engineer their spitballs to back into what might be the same numbers missing from your own plan. Plus, Sean wants to retire in two years at age 56 with $4.4M without handing half of it to the tax man, and Dallas and Leeloo are wondering if there's such a thing as too much Roth - they're 48 and on track for $1M in theirs. Plus we'll talk about some charitable giving strategies: what's the difference between a DAF and a CRUT?Free Financial Resources in This Episode: https://bit.ly/ymyw-592 (full show notes & episode transcript)9th Annual YMYW Podcast Survey (password ymyw):https://www.surveymonkey.com/r/ymywpodcast2026Is There a Formula for Retirement? - YMYW TV:https://purefinancial.com/ymyw/episodes/is-there-a-formula-for-retirement/?utm_source=captivate&utm_medium=podcast&utm_campaign=ymyw-tv&utm_content=ymyw-pod-ep592-description-tv-s10e09Financial Blueprint (free, self-guided):https://purefinancial.com/financialblueprint/?utm_source=captivate&utm_medium=podcast&utm_campaign=financial-blueprint&utm_content=ymyw-pod-ep592-description-blueprintREQUEST your Retirement Spitball Analysis:https://bit.ly/YMYWaskCDOWNLOAD more free guides:https://bit.ly/YMYWguidesCREAD financial blogs:https://bit.ly/YMYWblogCWATCH educational videos:https://bit.ly/YMYWvidsCSUBSCRIBE to the YMYW Newsletter:https://bit.ly/YMYWnewsletterCConnect With Us:Subscribe on YouTube and join the conversation in the comments:https://bit.ly/YMYW-YTSubscribe or follow YMYW in your favorite podcast app:https://lnk.to/ymywLeave your honest reviews and ratings in Apple Podcasts:https://podcasts.apple.com/us/podcast/your-money-your-wealth/id312900254Chapters: 00:00 - The 9th Annual YMYW Podcast Survey is now open!00:44 - Intro: This Week on the YMYW Podcast01:39 - Working Until 70 With $6.5M Saved. Do I Need Roth Conversions? (Michael, Pittsburgh, PA)09:25 - How Aggressively Should We Drain Our $2.6M IRA Before RMDs Hit? (K & J, the Cascades)16:46 - Can I Retire Single at 63 With $1.5M? (Tracy, 63, CA)20:15 - I'm 54, Single, With $4.4M. How Do I Retire at 56 Without Getting Crushed on Taxes? (Sean, Orlando, FL)29:22 - How Much Roth is Too Much? We're 48, Heading for $1M in Roth. Did We Overshoot the Goal? (Dallas & Leeloo, 48, Brooklyn, NY)36:15 - You Said CRTs Must Leave 10% to Charity. Let Me Correct the Record. (DG)38:21 - DAF vs. CRUT: Which Charitable Tool is Better for $1M Company Stock That's Up 237%? (Fish Sean, 54, Winter Springs, FL)44:22 - Outro: Next Week on the YMYW Podcast

Trump Accounts are now live, giving parents and grandparents another option for saving and investing on behalf of their children. In this episode of the Tax Smart REI Podcast, Thomas Castelli, Jacob Orr, and Nate Sosa discuss how Trump Accounts work, who qualifies, how the government's $1,000 contribution is claimed, and where these accounts fit alongside strategies like 529 plans, Roth IRAs, and hiring your children in your business. In this episode, you'll learn: - Who qualifies for the $1,000 government contribution - Annual contribution limits - How contributions and withdrawals are taxed - How Trump Accounts compare to 529 plans - When a Roth conversion may make sense Request a consultation from Hall CPA at go.therealestatecpa.com/3KSEev6 Register for FREE access to the 2026 Hall CPA Tax Strategy Summit: www.taxandlegalsummit.com/2026signup Join the Hall CPA Team: www.therealestatecpa.com/careers/ Connect with Eckard Enterprises: eckardenterprises.com/taxsmartrei/?u…copy_hyperlink Submit your question for Tom & Nathan: go.therealestatecpa.com/question The Tax Smart Real Estate Investors podcast is for general information purposes only and is not intended to provide, and should not be relied on for, tax, legal, or accounting advice. Information on the podcast may not constitute the most up-to-date legal or other information. No reader, user, or listener of this podcast should act or refrain from acting on the basis of information on this podcast without first seeking legal and tax advice from counsel in the relevant jurisdiction. Only your individual attorney and tax advisor can provide assurances that the information contained herein – and your interpretation of it – is applicable or appropriate to your particular situation. Use of, and access to, this podcast or any of the links or resources contained or mentioned within the podcast show and show notes do not create a relationship between the reader, user, or listener and podcast hosts, contributors, or guests. Any mention of third-party vendors, products, or services does not constitute an endorsement or recommendation. You should conduct your own due diligence before engaging with any vendor.

Most people think tax strategy is the starting point. It's not. It's the final layer that sits on top of a life you actually want to live.In this episode, Ari Taublieb, CFP®, responds to a listener with over $3 million across pre-tax, Roth, and brokerage accounts, plus a pension and future Social Security. On paper, everything looks optimized. In reality, he's stuck on a question that keeps a lot of high savers from moving forward.Should he use his brokerage account for income, for tax strategies, or to fund Roth conversions?The answer is not as simple as picking the most tax-efficient move. In fact, focusing on taxes first can lead to the wrong outcome entirely. Ari walks through why having too much income later in life can create a “tax bomb,” how required minimum distributions change the equation, and why Roth conversions can make sense when future tax rates are likely higher.But the real takeaway has nothing to do with spreadsheets.Before deciding on conversions, withdrawal strategies, or tax brackets, the first question is much simpler. How much do you actually want to spend? Without that clarity, even the best tax plan can lead to regret. With it, the right strategy becomes much easier to see.Because the goal is not to minimize taxes at all costs. The goal is to use your money in a way that actually improves your life while you still have the time and energy to enjoy it.--Advisory services are offered through Root Financial Partners, LLC, an SEC-registered investment adviser. This content is intended for informational and educational purposes only and should not be considered personalized investment, tax, or legal advice. Viewing this content does not create an advisory relationship. We do not provide tax preparation or legal services. Always consult an investment, tax or legal professional regarding your specific situation.The strategies, case studies, and examples discussed may not be suitable for everyone. They are hypothetical and for illustrative and educational purposes only. They do not reflect actual client results and are not guarantees of future performance. All investments involve risk, including the potential loss of principal.Comments reflect the views of individual users and do not necessarily represent the views of Root Financial. They are not verified, may not be accurate, and should not be considered testimonials or endorsementsParticipation in the Retirement Planning Academy or Early Retirement Academy does not create an advisory relationship with Root Financial. These programs are educational in nature and are not a substitute for personalized financial advice. Advisory services are offered only under a written agreement with Root Financial.Create Your Custom Early Retirement Strategy HereGet access to the same software I use for my clients and join the Early Retirement Academy hereAri Taublieb, CFP ®, MBA  is the Chief Growth Officer of Root Financial Partners and a Fiduciary Financial Planner specializing in helping clients retire early with confidence.

A heartwarming story about a 92-year-old Chick-fil-A employee sparks a bigger conversation with Zach Abraham about purpose, retirement, Social Security, and the financial planning mistakes that can cost retirees thousands. Plus, Zach explains when Roth conversions make sense—and when they absolutely don't. Subscribe and stay tuned for new episodes every weekday! Follow us here for […]

In this Episode of the Secure Your Retirement Podcast, Radon and Murs discuss Trump Accounts with Taylor Wolverton, our Director of Financial Planning and Tax Strategy, breaking down exactly how do Trump Accounts work, who qualifies, and why this new option for Trump Investments is quickly becoming part of the conversation around saving for children and investing for grandchildren. Retirement planning has always started with the accounts you already know, but these works differently, and if you're building a family financial planning strategy or looking for financial gifts for grandchildren, it's worth understanding before you decide whether it belongs in your plan.Listen in to learn about the eligibility rules, the contribution limits, and the one-time $1,000 government deposit that applies to certain children. Radon and Murs also walk through a Roth conversion strategy hiding inside these accounts, one that turns a simple child investment plan into a genuine tool for building generational wealth. Whether you're deep into your own retirement tax planning or just starting to think about a retirement checklist for your family, this episode connects a brand-new account to the same retirement tax strategies you may already be using in your own retirement financial plan.In this episode, find out:What a Trump Account is, who's eligible, and how the application process actually worksThe contribution rules, including the $5,000 annual limit and the one-time $1,000 seed deposit for eligible childrenHow employer contributions work and why they don't add to your taxable incomeThe Roth conversion strategy that can turn contributions into a tax-free retirement account for your childWhen money can be withdrawn, and the penalties to know about before that ageTweetable Quotes:"There's zero money to us in setting up a Trump account. We just wanted to talk it through, because there are real benefits people can take advantage of." - Radon Stancil"There's not many ways you can get a thousand dollars tax-free. If someone was born between 2025 and 2028, it seems like a no-brainer." - Murs TariqResources: If you are in or nearing retirement and you want to gain clarity on what questions you should be asking, learn what the biggest retirement myths are, and identify what you can do to achieve peace of mind for your retirement, get started today by requesting our complimentary video course, Four Steps to Secure Your Retirement! To access the course, simply visit POMWealth.net/podcast.

Bonds are supposed to be the brakes in a portfolio—but should those brakes be BND, a shorter-term fund, CDs, or a Treasury ladder? Don explains why duration, yield stability, and personal comfort make the answer more nuanced than one ticker.The Friday questions keep coming: pairing AVGE with VT, moving $5 million from real estate into a retirement portfolio, understanding an emerging-markets fund that became legally non-diversified, and building 529s for grandchildren.The final stretch is all planning: Roth conversions and IRMAA, choosing a HELOC over a 401(k) loan, and resisting the urge to let the tax tail wag the retirement dog.00:00 A full inbox of financial questions02:30 BND versus short bonds, CDs, and Treasury ladders06:45 AVGE plus VT—or unnecessary overlap?10:23 Moving $5 million from real estate into markets14:51 When an index fund becomes legally non-diversified18:18 Building 529s and Roth head starts for grandchildren22:16 Roth conversions, RMDs, and IRMAA25:23 HELOC or 401(k) loan for renovations?28:01 The tax tail and a long Roth-conversion planQuestions? Comments? Click!

On the evening of December 24, 1926, a farmer in Farwell, Texas, called the sheriff to report that his neighbor, George Hassell, had been acting very strangely in recent days and he had been telling conflicting stories about the whereabouts of his family, who had been missing for several days. When the sheriff arrived at the Hassell farm, he began questioning George about where his family had gone, but mid conversation, Hassell removed a pocket knife from his pocket and stabbed himself three times in the chest.  Hassell was taken to the hospital, where he was not expected to survive, but against the odds, George pulled through. With no option for escape and having given law enforcement good reason to suspect him in the disappearance of his family, George began confessing to multiple murders. At first, it was assumed he had flown into a rage and murdered his family a week earlier, but the more Hassell talked, the clearer it became that George Hassell violent and murderous behavior went well beyond the walls of his home in Farwell. References Associated Press. 1927. "Hassell death edict to stand." Fort Worth Record-Telegram, February 15: 1. —. 1928. "Hassell is fifth white man to chair." Fort Worth Record-Telegram, February 10: 1. —. 1926. "Sheriff expects full statement from Hassell." San Antonio Express-News, December 26: 1. —. 1928. "Slayer of 13 thanks judge for sentence." San Antonio Express-News, January 11: 1. Church, Marlowe. 2019. "Hassell offered detailed confession." Eastern New Mexico News, September 3. Morning Press . 1927. "Texas killer's name heard in Whittier case." Morning Press (Santa Barbara, CA), January 1: 1. Roth, Michael. 2022. Man with the Killer Smile: The Life and Crimes of a Serial Mass Murderer. Denton, TX: University of North Texas Press. San Antonio Express-News. 1927. "Hassell's California victims identified." San Antonio Express-News, February 12: 5. Cowritten by Alaina Urquhart, Ash Kelley & Dave White (Since 10/2022)Produced & Edited by Mikie Sirois (Since 2023)Research by Dave White (Since 10/2022), Alaina Urquhart & Ash KelleyListener Correspondence & Collaboration by Debra LallyListener Tale Video Edited by Aidan McElman (Since 6/2025) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

"I always thought she would walk through the door."In late December 1976, a camper was spending time down in the Florida Keys. He was camping in an area known as the rock pit alongside US Route 1 on Grassy Key, a limestone quarry site used by campers and party-goers alike. While there, though, he was approached by a man he later described as a "hippie-type," who offered to show him a decomposing human body for a quarter. The camper declined and called the Monroe County Sheriff's Office.On December 30th, Detective Richard Roth was dispatched to investigate. Following the camper's directions, he makes his way into the heavily wooded area near the rock pit. There, he found bones...If you have any information about this story that you'd like to share, please reach to the Monroe County Sheriff's Office Major Crimes Unit at:Phone: +13052892410 or (305) 289-2410Check out the podcast store at unresolved.dashery.comIf you would like to support this podcast, consider heading to https://www.patreon.com/unresolvedpod to become a Patron or ProducerBecome a supporter of this podcast: https://www.spreaker.com/podcast/unresolved-a-true-crime-mystery-podcast--3266604/support.

Listener Q&A where Andy talks about: Should Roth conversion analysis look at marginal or effective tax rates ( 4:21 )His thoughts on why qualified Roth account distributions might eventually be included in certain measures of Modified Adjusted Gross Income ("MAGI") ( 8:28 )What other MAGIs are potentially impacted and should be watched out for with doing Roth conversions ( 12:38 )The difference between "directionality" and "precision" in retirement planning ( 20:40 )Is it reasonably for an advisor to charge you extra for outsourcing some of their investment management to a separately managed or sub-managed account ( 25:38 )His thoughts of reinvesting a deferred compensation plan to all cash when the plan will soon begin paying out its deferred payments ( 29:34 )His thoughts on using multiple dividend and fixed income funds to create a "high income sleeve" for near-term distribution needs ( 35:25 )Whether it's accurate that you can indirectly file a tax return extension simply by making an online tax payment and select "extension" as the reason for the payment ( 39:05 )Can a minor with less than $400 of self-employment income not file a tax return yet still be eligible to contribute to a Roth IRA ( 44:56 )How he helps clients balance Fear of Missing Out ("FOMO") and Fear of Running Out ("FORU") ( 52:04 )How much of his planning work with clients is computational vs psychological ( 54:42 )His thoughts on the gamification of investing, and the prediction markets ( 58:11 )Why there are so many different funds like buffered ETFs and option trading ETFs, at higher expense ratios, when many can just invest in a few basic low-cost ETFs ( 1:00:36 )To send Andy questions to be addressed on future Q&A episodes, email andy@andypanko.comAndy's LinkedIn profile: https://www.linkedin.com/in/andypanko/Links in this episode:Tenon Financial monthly newsletter/blog - Retirement Planning InsightsYouTube channel - Retirement Planning Education (formerly Retirement Planning Demystified)Retirement Planning Education website - www.RetirementPlanningEducation.com

What does it really take to build a happy retirement? Join Wes Moss and Christa DiBiase on this episode of the Retire Sooner Podcast as they blend retirement planning research with listener questions to explore the financial and lifestyle choices that may help shape life after work. • Learn how the five-step Retire Sooner Method brings together the financial and personal sides of retirement planning. • See how retirement "green zones" may help you think about savings, income, liquidity, and mortgage decisions. • Explore why core pursuits, strong friendships, and even better sleep have been linked to greater retirement satisfaction. • Hear practical conversations about written financial plans and other habits that may help reduce money-related stress. • Get answers to listener questions about AI financial tools, Roth conversions, bond funds versus money markets, spousal IRAs, retirement income, paying off a mortgage, reverse mortgages, and annuities. Listen and subscribe to the Retire Sooner Podcast for more educational conversations about retirement planning, retirement investing, and personal finance. Learn more about your ad choices. Visit megaphone.fm/adchoices

How do you know when it's worth optimizing your retirement plan and when it's better to keep things simple? This week, Roger answers a listener question by exploring Aristotle's concept of the "golden mean," arguing that the best retirement decisions are rarely found at either extreme. He explains why financial optimization should be measured by the life it enables rather than the dollars it saves and introduces the OODA Loop (Observe, Orient, Decide, Act) as a practical framework for evaluating trade-offs. Roger also answers listener questions about stepped-up cost basis after the death of a spouse, whether dividends can be used to fund an income floor, and when bonds versus CDs make sense in today's interest rate environment.OUTLINE OF THIS EPISODE OF THE RETIREMENT ANSWER MAN(00:00) Roger introduces today's discussion on balancing financial optimization with simplicity, previews upcoming episodes, and shares updates on the August replay schedule and September Social Security series.RETIREMENT TOOLKIT(02:31) Finding your "golden mean" between optimizing your retirement plan and keeping it simpleWhy retirement planning often overemphasizes financial optimizationThe difference between optimizing for money and optimizing for lifeHow Aristotle's concept of the golden mean applies to retirement decisionsUsing the OODA Loop (Observe, Orient, Decide, Act) to make better decisionsRecognizing personal biases before making financial decisionsEvaluating trade-offs and second-order consequences before pursuing tax strategies, Roth conversions, and other optimization opportunitiesLISTENER QUESTIONS(36:35) Roger answers a listener's question about home cost basis. (41:02) Can dividend income be used to fill the gap in my retirement income floor?(44:55) Are bonds still a good conservative investment, or should I use CDs instead?SMART SPRINT(49:55) Practice using the OODA framework on a small, everyday decision this week to determine whether optimizing is truly worth the extra time and effort.CLOSING THOUGHTS(51:24) Roger reflects on how building a resilient retirement plan isn't just about protecting against uncertainty—it also gives you the confidence to lean into life and enjoy retirement more fullyREFERENCESSubmit a Question for RogerSign up for The NoodleNote: The opinions expressed are for informational purposes only and should not replace personalized advice from licensed professionals.

A quarter in the piggy bank has grown into a maze of UTMAs, 529s, custodial Roth IRAs, and the new child investment accounts. Tom and Don sort the options by what the money is actually for—and who keeps control.The 529 emerges as the flexible favorite, especially with its education uses and limited Roth rollover. Then the conversation turns to concentrated factor ETFs, the familiar Bitcoin argument, and whether private markets are really swallowing public investing.The through-line is refreshingly simple: match the account to the goal, favor broad diversification, and resist stories that make investing sound more complicated than it needs to be.00:00 Pshaw, Wordle, and the kid-money maze03:00 UTMAs and UGMAs: control has an expiration date05:34 Why 529 plans remain the flexible favorite09:01 Custodial Roth IRAs and an enormous head start11:15 New child accounts versus the 52916:02 MOAT and COWZ: clever ticker, concentrated portfolio20:48 Bitcoin, volatility, and the meaning of value26:51 Public markets versus the private-market storyQuestions? Comments? Click!

Trump accounts — technically the 530A — went live July 4th, and Justin Harvey opened three for his own kids just to see how they work. These accounts are child-owned, they behave like a traditional IRA, and they come with rules most physicians haven't heard yet.  Tag along with Jimmy Turner and Justin Harvey as they discuss where they actually belong in your savings hierarchy, and who should pass entirely.Resources: Get 10% off working with Gelt, the tax strategy team that Jimmy Turner personally uses: https://moneymeetsmedicine.com/CPA Every doctor needs own-occupation disability insurance.  Get it from a source you can trust: https://moneymeetsmedicine.com/disability    Want a free copy of The Physician Philosopher's Guide to Personal Finance?  Snag your copy here: https://moneymeetsmedicine.com/freebook What you'll learn: Why the 530A is closer to a traditional IRA than a 529 — and the basis-tracking problem nobody is warning parents about Where Trump accounts rank against 401(k)s, backdoor Roths, and 529s in a physician savings hierarchy Who actually gets the free $1,000, and why older kids are treated differently The Roth conversion play at age 18 — and the risk of handing an 18-year-old a quarter-million-dollar account Why a kid's Roth IRA may teach better money lessons than any government-funded account Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

#734: Depending on which source you ask, the U.S. is short somewhere between 1.2 million and 10 million homes — and the reason for that wild range says as much about who's counting as it does about the shortage itself.

Schedule a Free Financial Assessment with an experienced professional:https://purefinancial.com/lp/free-assessment/?utm_source=captivate&utm_medium=podcast&utm_campaign=free-assessment&utm_content=ymyw-pod-ep591-description-free-assessmentB and S in Maryland are in their mid-40s with $425,000 and a couple of rental properties. Can they retire early at 62? Vee in Oregon came to the US as a refugee with nothing and built a three and three-quarter million dollar portfolio from the ground up. Is his Roth conversion plan solid? And finally, Chandler and Monica in Texas are sitting on $1.4 million and hope they can walk away from work in 3 years. Will Roth conversions keep the tax man from taking a giant bite on their way out? That's all today on Your Money, Your Wealth® podcast 591 with Joe Anderson, CFP® and Big Al Clopine, CPA.Free Financial Resources in This Episode: https://bit.ly/ymyw-591 (full show notes & episode transcript)Withdrawal Strategy Guide - free downloadhttps://purefinancial.com/white-papers/withdrawal-strategy-guide/?utm_source=captivate&utm_medium=podcast&utm_campaign=whitepaper-withdrawal-strategy-guide&utm_content=ymyw-pod-ep591-description-whitepaperThe Number One Spending Mistake Ruining Retirements - YMYW TVhttps://purefinancial.com/ymyw/episodes/number-one-spending-mistake-ruining-retirements/?utm_source=captivate&utm_medium=podcast&utm_campaign=ymyw-tv&utm_content=ymyw-pod-ep591-description-tv-s12e01Financial Blueprint (free, self-guided):https://bit.ly/YMYWblueprintCREQUEST your Retirement Spitball Analysis:https://bit.ly/YMYWaskCDOWNLOAD more free guides:https://bit.ly/YMYWguidesCREAD financial blogs:https://bit.ly/YMYWblogCWATCH educational videos:https://bit.ly/YMYWvidsCSUBSCRIBE to the YMYW Newsletter:https://bit.ly/YMYWnewsletterCConnect With Us:Subscribe on YouTube and join the conversation in the comments:https://bit.ly/YMYW-YTSubscribe or follow YMYW in your favorite podcast app:https://lnk.to/ymywLeave your honest reviews and ratings in Apple Podcasts:https://podcasts.apple.com/us/podcast/your-money-your-wealth/id312900254Chapters: 00:00 - Intro: This Week on the YMYW Podcast00:57 - Half a Million and Rental Properties in Our Mid-40s. Can We Retire Early? (B & S, Westminster, MD)12:48 - Refugee to $3.75M: Is My Roth Conversion Plan Actually Solid? (Vee, OR)25:55 - Can Friends with $1.4M and a Roth Conversion Puzzle Retire in 3 Years? (Chandler & Monica, TX)33:05 - Outro: Next Week on YMYW Podcast

Chasing performance feels like the easiest way to make money—but buying what has already gone up often means arriving late and leaving with less.In this episode of Talking Real Money, Tom and Don examine the “behavior gap”: the difference between an investment's return and what investors actually earn after buying high, selling low, and chasing the latest market story. They explain why disciplined diversification and a sensible asset allocation usually beat a portfolio built around hot ideas.They also answer listener questions about retirement withdrawal order, Roth conversions, reinsurance funds, high investment costs, and whether financial recommendations are influenced by commissions.00:20 Why buying what's hot usually means arriving late01:42 Chasing performance without ever catching it03:03 How Bitcoin rose while Bitcoin ETF investors lost money04:58 The costly confusion between “has gone up” and “is going up”05:53 Morningstar's “Mind the Gap” research06:44 AI, chips, and the latest performance-chasing cycle07:37 Asset allocation versus a collection of hot ideas09:21 Why trying to beat the market often backfires10:16 Listener Question: Retirement accounts and withdrawal order12:29 Taxable, pre-tax, or Roth—which money should come first?15:35 Listener Question: Do reinsurance funds belong in a portfolio?16:58 Catastrophe risk, complexity, and nearly 2% in expenses21:33 Listener Question: Are fund recommendations influenced by compensation?23:27 Why “trust us” isn't a convincing financial argumentQuestions? Comments? Click!

Most service members leave serious money on the table every year because nobody sat them down and explained how the military's pay structure actually works from a tax perspective. I'm breaking down 12 tax advantages built specifically for active duty, Guard, Reserve, and veterans. From BAH exemptions and combat zone TSP contributions to the Section 121 capital gains exclusion that saved one of my buddies close to six figures on a home sale.   Timestamps (00:00) - Intro (00:27) - PCS Moving Expense Deductions (01:09) - BAH, BAS, and Tax-Exempt Allowances (03:06) - Roth vs. Traditional TSP (03:54) - Deployment Tax Benefits and Combat Zone TSP (04:48) - Tax Credits vs. Deductions Explained (06:51) - Real Estate Tax Benefits and Section 121 Exclusion (08:57) - State of Residence Strategy (09:48) - Filing Extensions and Penalty Relief (10:06) - Reserve and Guard Drill Deductions (10:25) - Veteran Tax Advantages: Disability Pay, GI Bill, State Benefits   About the Show On the Military Millionaire Podcast, I share real conversations with service members, veterans, and their families. Each week, we explore how to build wealth through personal finance, entrepreneurship, and real estate investing. Resources & Links Download a free copy of my book: https://www.frommilitarytomillionaire.com/free-book Sign up for free webinar trainings: https://www.frommilitarytomillionaire.com/register Get an intro to recommended VA agents/lenders: https://www.frommilitarytomillionaire.com/va-realtor Apply for The War Room Mastermind: https://www.frommilitarytomillionaire.com/mastermind-application Join our investor list: https://www.frommilitarytomillionaire.com/investors Guide to raising capital: https://www.frommilitarytomillionaire.com/capital-raising-guide   Connect with David Pere Facebook Group: https://www.facebook.com/groups/militarymillionaire YouTube Channel: https://www.youtube.com/@Frommilitarytomillionaire?sub_confirmation=1 Instagram: https://www.instagram.com/frommilitarytomillionaire/ LinkedIn: https://www.linkedin.com/in/david-pere/ X (Twitter): https://x.com/militaryrei TikTok: https://www.tiktok.com/@militarymillionaire   Produced by ⁠UNFLTR

7-20-26 Executive Advisor for TBT's 'The Enchantment', Kurt Roth joins the program ahead of the First Round of the TBT Tournament

An alarming number of people have access to a 401(k) and are either not using it, not getting the full employer match, or not making the simple moves that turn a good account into a great one. Joe and OG dedicate a full episode to the retirement account that most people take for granted -- covering contributions, matching, investment selection, Roth versus traditional, and the specific decisions that separate people who retire comfortably from people who almost got there. Plus wins from the Stacker community and trivia that will make you the most dangerous person at your next dinner party.What You'll Walk Away WithWhy the employer match is the single highest guaranteed return available to any investor -- and the specific contribution level that captures every dollar of itRoth 401(k) versus traditional 401(k): the one question that cuts through all the noise and tells you which one to use right nowWhy your investment menu feels overwhelming and how to make a great choice in under five minutes using one simple filterThe auto-escalation feature most people never turn on -- and why setting it up once can add tens of thousands of dollars to your balance without you doing anything elseWhat to do with your 401(k) when you leave a job: the four options, which one is almost always wrong, and which one most people choose anywayWhy contribution limits are higher than most people think -- and the catch-up contribution that becomes available at 50 that most people in their 40s don't know to plan forThe vesting schedule trap: why your employer match might not actually be yours yet -- and what that means for anyone thinking about leaving their jobWhy 403(b) and 457 plans follow most of the same rules -- and the one unique advantage the 457 has that almost nobody knows aboutOG on the single most common 401(k) mistake he sees in client portfolios -- and how long it typically takes to fixStacker wins from the community: the specific moves people made this month that are already paying offWhy This Matters NowEvery year you don't optimize your 401(k) is a year of compounding you don't get back. The moves in this episode are not complicated -- but most people either don't know about them or keep putting them off. This is the episode to send to anyone who has a 401(k) and has never really looked at it.From the BasementJoe and OG celebrate the 401(k) in mom's basement while OG recovers from completing the Triple Bypass -- a Colorado cycling event that covers three mountain passes and approximately all of the elevation gain in the western hemisphere. OG's wife asked if he'd do it again. He answered with a childbirth analogy. Doug arrives with trivia that will be re-shared all week. The community delivers wins that prove the system works.Resources MentionedStacking Benjamins Basics Guide -- stackingbenjamins.com/basicsguideStacking Benjamins Field Kit -- stackingbenjamins.com/fieldkitStacking Benjamins BAD Groups -- stackingbenjamins.com/badStacking Benjamins Newsletter (The 201) -- stackingbenjamins.com/201OG financial planning calendar -- stackingbenjamins.com/ogStacking Benjamins Community -- stackingbenjamins.com/basementSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The government just created a brand new account that hands your kid $1,000 in free money from birth. Here is everything you need to know before you miss the window.

Money is a lot like your health—everyone has an opinion, the internet is full of questionable advice, and bad guidance can cost you years. In this episode, Danielle sits down with financial advisor Marcus Corvino to break down the financial myths, red flags, and costly mistakes that keep people from building real wealth. Together they unpack what actually makes a trustworthy financial advisor, why some investment products are oversold, and how smart tax planning can potentially save you hundreds of thousands of dollars over your lifetime. Whether you're a business owner, healthcare professional, employee with a 401(k), or simply wondering if you're on the right financial path, this episode gives you practical, easy-to-understand strategies to help you make better decisions with your money. You'll learn the difference between term life and whole life insurance, why disability insurance is one of the most overlooked financial tools available, how Roth conversions work, common retirement planning mistakes, and why building wealth isn't nearly as complicated as social media makes it seem. If you've ever wondered whether you're asking the right questions—or if your financial advisor is asking you the right questions—this episode is for you Learn more about working with Danielle  Shop Danielle's masterclasses (learn more in 60-90 minutes than years of dr appointments) Follow Danielle on IG Follow Empowered Mind + Body on IG  Marcus Consult www.wscoachingandconsulting.com

In this episode of Money Matters, brought to you by Greenberg Financial Group, Dave, Todd, and Dylan run the show while the rest of the team is traveling, breaking down a rough week where the chip stocks led the market lower. We get into what Dave dubbed the "chip wreck," with the semiconductor group dipping into bear market territory for the month, and why we look at that kind of volatility as part of the territory when an entire industry is going through price discovery rather than a reason to abandon good companies. We talk through the names in the middle of it, from Micron and SanDisk to Taiwan Semi's blowout earnings and its plan to pour another $100 billion into Phoenix, and why we still believe the demand story for AI is only getting started. We also dig into some encouraging news on inflation, with both CPI and PPI posting their biggest monthly drops in years as lower oil worked its way through, even as tensions in the Strait of Hormuz pushed crude back up sharply on the week. And we spend real time on the shift at the top of the market, with Apple retaking the largest company crown from Nvidia, and what that rotation is telling us. The back half of the show is all about planning, and the levers that actually matter in retirement. We walk through Roth conversions and the sweet spot in your early sixties, why QCDs are the underappreciated cousin of tax planning, how RMDs work and when to take them, and why owning individual bonds, treasuries, and fee-based annuities can serve the more conservative saver who wants off the rollercoaster. It all ties back to our fiduciary, fee-based, financial-planning-first approach, and the difference between being a true advisor and just a money manager. We are also thrilled to introduce the newest member of the Greenberg Financial team, Hailey Glick, who is helping us build out an in-house tax practice launching in 2027. It is the next step in Dean's vision of a true family office, everything you need under one roof, and we get into how bringing tax planning alongside investments, estate work, and financial planning lets us look at your whole picture over decades rather than one filing season at a time. If you have been thinking about taking us up on the free financial plan, this is exactly the kind of clarity it can bring. If you would like to contact us to learn more about our firm, our seminars, and our process - call us at 520.544.4909 or go to our website at www.Greenbergfinancial.com or email us at Contact@Greenbergfinancial.com Disclaimer: This show discusses different investment products and strategies. Every product and strategy has some type of inherent risk and we strongly encourage our listeners to properly understand these risks. Past performance is no guarantee of future performance. The information presented on this program is believed to be factual and up-to-date, but we do not guarantee its accuracy and it should not be regarded as a complete analysis of the subjects discussed.  The material covered on this program does not involve the rendering of personalized investment advice, but is for general information purposes only.  A professional advisor should be consulted before implementing any of the options presented.   Greenberg Financial Group is registered as an investment advisor with the SEC and only transacts business in states where it is properly registered, or is excluded or exempted from registration requirements.

In this episode, Drake Roth (@dek_grappling) returns to talk about open vs closed skills, how individuals can be intentional with their training, measure progress/learning, operationalize improvement, and adjust task goals over longer periods of time. Drake also writes periodically on substack, Grappling with Skill. The blog post we referenced can be found here.Hope you enjoy! Download Sherpa, the free AI-powered journaling app for athletes. Join the convo with Josh on Discord here.Use the code "BJJHELP" for 50% off your first month on Jake's Outlier Database to study match footage, get links to resources, and more.Use code “BJJHELP” at submeta.io to try your first month for only $8!

Poznáte jeho texty – teraz ich budete môcť aj počuť. Každú nedeľu vo svojej podcastovej aplikácii nájdete trochu iný formát Dobrého rána – Roth číta Marca. Eseje a komentáre publicistu Sama Marca v podaní herca Roberta Rotha. Načítaný text: https://www.sme.sk/komentare/c/nejakym-ludom-vadia-nejake-vrtule-pise-samo-marec – Všetky podcasty denníka SME nájdete na⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ sme.sk/podcasty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ – Odoberajte aj audio verziu denného newslettra⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ SME.sk⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ s najdôležitejšími správami na⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ sme.sk/brifingSee omnystudio.com/listener for privacy information.

Could a simple tax strategy create unexpected consequences if it's done incorrectly? On this episode from this past weekend’s radio show, Mike Douglas discusses Roth conversions, backdoor Roth strategies, and the often-overlooked IRS rules that can catch retirees by surprise. He explains how tax planning fits into a broader retirement strategy, why today’s tax environment matters, and how long-term care planning can impact families and retirement savings. The conversation highlights the importance of coordinating tax, income, and legacy planning to help avoid costly mistakes and prepare for the future. Schedule your complimentary appointment today: MichigansRetirementCoach.com Follow us on social media: YouTube | Facebook | Instagram | LinkedInSee omnystudio.com/listener for privacy information.

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

What did Mindy and Carl Jensen learn from The Money Guys after they reviewed their portfolio? In this recap episode, Mindy and Carl share their biggest takeaways on retirement planning, cash reserves, Roth conversions, tax strategy, and portfolio diversification. They discuss what advice they're putting into action, what they're still debating, and how these lessons could help anyone pursuing financial independence and long-term wealth. To go beyond the podcast: Kick start your financial independence journey with our FREE financial resources - https://biggerpocketsmoney.com/ Subscribe on YouTube for even more content- www.youtube.com/biggerpocketsmoney  Connect with us on social media to join the other BiggerPockets Money listeners - https://www.facebook.com/groups/BPMoney We believe financial independence is attainable for anyone no matter when or where you're starting. Let's get your financial house in order! Learn more about your ad choices. Visit megaphone.fm/adchoices

Richard Rosso & Jonathan McCarty explore some of the biggest retirement and investing questions facing Americans today. We examine how SECURE Act 2.0 is accelerating the "Rothification" of retirement savings, why catch-up Roth contributions remain a powerful planning tool, and what investors need to know about employer Roth matching and the long-term tax implications. We also tackle one of the hottest debates in retirement planning: Are dividend stocks really safer, or are investors being seduced by yield? We examine the arguments popularized by Dave Ramsey and Suze Orman, discuss whether dividends actually provide better retirement income, and explain why total return—not yield alone—should drive long-term investment decisions. Along the way, we'll discuss how today's market environment, disruptive technologies, and changing tax policies could reshape retirement planning for years to come. Plus, we preview our upcoming "Narrative Busters" series, where we challenge some of Wall Street's most widely accepted investment beliefs. 0:00 INTRO 0:19 - Butt stuff & Taxes 3:39 - MAHA & Homeopathy (Health & Wealth are Connected) 5:45 - Secure Act 2.0 & Rothification of America 9:53 - Do Not Stop Catch-up Contributions to Roths 12:58 - Putting Employer Matches in Roth accounts 14:15 - Dealing with Tax Implications (Bending Over) 15:45 - Temperature Technology 19:11 - Take the Pain of Taxes Now vs Later (Will They Tax Our Roths?) 20:23 - The Roth Saga of Peter Thiel 22:48 - The Tax Cascade is Coming 25:05 - Suze Orman, Dave Ramsey Rationale on Dividend Paying Stocks 27:58 - Dividend = Safety? 32:47 - Seduced by Yield 37:00 - If You Want Income... 39:15 - Impact of Disruptive Companies 40:39 - Narrative Busters tease (Which Ghost Buster is Who? Hosted by RIA Advisors Director of Financial Planning, Richard Rosso, CFP w Senior Investment Advisor, Jonathan McCarty, CFP Produced by Brent Clanton, Executive Producer ------- Do you enjoy our content? Rate us on Google: https://bit.ly/4b9JtEo ------- Watch Today's Full Video on our YouTube Channel: ------- Watch today's "Before the Bell" premarket commentary, "Is Market Leadership Changing?" https://youtu.be/-NtwWZUvZBA ------- Watch our previous show, "Winning Less, Investing Better" https://youtube.com/live/K-mLdepNr6Y?feature=share ------- Get more info & commentary: https://realinvestmentadvice.com/insights/real-investment-daily/ ------- * REGISTER for our next Candid Coffee, "Narrative Busters: Market Stories Investors Should Approach With Caution," Saturday, July 18, 2026: https://streamyard.com/watch/RfJtCj2byfDr --- Visit our Site: https://www.realinvestmentadvice.com Contact Us: 1-855-RIA-PLAN --- Subscribe to SimpleVisor : https://www.simplevisor.com/register-new --- Connect with us on social: https://twitter.com/RealInvAdvice https://twitter.com/LanceRoberts https://www.facebook.com/RealInvestmentAdvice/ https://www.linkedin.com/in/realinvestmentadvice/ #RetirementPlanning #RothIRA #DividendInvesting #TaxPlanning #FinancialPlanning

Richard Rosso & Jonathan McCarty explore some of the biggest retirement and investing questions facing Americans today. We examine how SECURE Act 2.0 is accelerating the "Rothification" of retirement savings, why catch-up Roth contributions remain a powerful planning tool, and what investors need to know about employer Roth matching and the long-term tax implications. We also tackle one of the hottest debates in retirement planning: Are dividend stocks really safer, or are investors being seduced by yield? We examine the arguments popularized by Dave Ramsey and Suze Orman, discuss whether dividends actually provide better retirement income, and explain why total return—not yield alone—should drive long-term investment decisions. Along the way, we'll discuss how today's market environment, disruptive technologies, and changing tax policies could reshape retirement planning for years to come. Plus, we preview our upcoming "Narrative Busters" series, where we challenge some of Wall Street's most widely accepted investment beliefs. 0:00 INTRO 0:19 - Butt stuff & Taxes 3:39 - MAHA & Homeopathy (Health & Wealth are Connected) 5:45 - Secure Act 2.0 & Rothification of America 9:53 - Do Not Stop Catch-up Contributions to Roths 12:58 - Putting Employer Matches in Roth accounts 14:15 - Dealing with Tax Implications (Bending Over) 15:45 - Temperature Technology 19:11 - Take the Pain of Taxes Now vs Later (Will They Tax Our Roths?) 20:23 - The Roth Saga of Peter Thiel 22:48 - The Tax Cascade is Coming 25:05 - Suze Orman, Dave Ramsey Rationale on Dividend Paying Stocks 27:58 - Dividend = Safety? 32:47 - Seduced by Yield 37:00 - If You Want Income... 39:15 - Impact of Disruptive Companies 40:39 - Narrative Busters tease (Which Ghost Buster is Who? Hosted by RIA Advisors Director of Financial Planning, Richard Rosso, CFP w Senior Investment Advisor, Jonathan McCarty, CFP Produced by Brent Clanton, Executive Producer ------- Do you enjoy our content? Rate us on Google: https://bit.ly/4b9JtEo ------- Watch Today's Full Video on our YouTube Channel: ------- Watch today's "Before the Bell" premarket commentary, "Is Market Leadership Changing?" https://youtu.be/-NtwWZUvZBA ------- Watch our previous show, "Winning Less, Investing Better" https://youtube.com/live/K-mLdepNr6Y?feature=share ------- Get more info & commentary: https://realinvestmentadvice.com/insights/real-investment-daily/ ------- * REGISTER for our next Candid Coffee, "Narrative Busters: Market Stories Investors Should Approach With Caution," Saturday, July 18, 2026: https://streamyard.com/watch/RfJtCj2byfDr --- Visit our Site: https://www.realinvestmentadvice.com Contact Us: 1-855-RIA-PLAN --- Subscribe to SimpleVisor : https://www.simplevisor.com/register-new --- Connect with us on social: https://twitter.com/RealInvAdvice https://twitter.com/LanceRoberts https://www.facebook.com/RealInvestmentAdvice/ https://www.linkedin.com/in/realinvestmentadvice/ #RetirementPlanning #RothIRA #DividendInvesting #TaxPlanning #FinancialPlanning

In this episode, Jake and Cory react to a listener-submitted article about proposed 401(k) changes that could make private equity and other alternative investments more accessible. They explain why they believe retirement plans should stay simple and discuss the risks of adding complexity to long-term investing. The conversation then turns to retirement planning, including a debate on the biggest risks retirees face, the challenge of "golden handcuffs," and why decisions about retirement can often involve more than just money. They wrap up with a discussion on mega backdoor Roth contributions and when they may—or may not—make sense. --------------- Get your complimentary guide to retirement https://falconwealthadvisors.com/jake-falcon-book-signup.html?utm_source=podcast&utm_medium=content&utm_campaign=rr_ebook  Get Jake's weekly blog https://falconwealthadvisors.com/index.html?utm_source=youtube&utm_medium=video&utm_campaign=upticks#ID2GUSO1Sj8Upy1QWdqVxHOM  Question for Jake and Cory? Email Luke → luke@falconwealthadvisors.com Watch clips of this episode on YouTube https://youtube.com/@uptickspodcast?si=H2Nj_aq7Jdh9AIc4  Follow Jake and Cory https://www.instagram.com/jake_falcon_crpc/?hl=en https://www.instagram.com/corybittnerkc/  #retirementplanning #goldenhandcuffs #401k #rothira #financialfreedom

On this episode of Simply Money presented by Allworth Financial, Bob and Brian play a financial planning game that reveals the one overlooked question that can completely change your retirement strategy. From caring for aging parents and buying a dream vacation home to pension decisions and Roth conversions, they explain why great financial planning isn't just about the numbers—it's about asking the right questions before you make life-changing decisions.See omnystudio.com/listener for privacy information.

Justin Halpern (writer/producer, Abbott Elementary, Sh*t My Dad Says) has a new book, Get Lost, and he here's to talk about how he wrote it with Drew and Roth. But first, Roth and Justin must commiserate about the Mets, and Drew gets recognized on the beach. Then, they open up the funbag to answer real questions from Defector readers and Distraction listeners.Go get Justin's new book, Get Lost, out now!Do you want to hear your question answered on the pod? Well, give us a call at 909-726-3720. That is 909-PANERA-0!Stuff We Talked AboutDapping in the toiletWitch doctors & geodesic domesGetting your kid to read your bookA getting-hit coachGetting all your blood replacedOur sweet soft sonsSponsors- Raycon, where you can get 20% off- Zocdoc, where you can find and instantly book a doctor you love today- Blueland, where you can get 15% off your first orderCredits- Hosts: Drew Magary & David Roth- Producer: Brandon Grugle, Multitude- Editor: Mischa Stanton, Multitude- Production Services & Ads: Multitude- Subscribe to Defector!About The ShowThe Distraction is Defector's flagship podcast about sports (and movies, and art, and sandwiches, and certain coastal states) from longtime writers Drew Magary and David Roth. Every week, Drew and Roth tackle subjects, both serious and impossibly stupid, with a parade of guests from around the world of sports and media joining in the fun! Roth and Drew also field Funbag questions from Defector readers, answer listener voicemails, and get upset about the number of people who use speakerphone while in a public bathroom stall. This is a show where everything matters, because everyone could use a Distraction. Head to defector.com for more info.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Andy chats with a real person (not an advisor) doing their own retirement planning. In this episode, Andy talks with Tom. They talk about a wide array of retirement planning topics such as when he started getting serious about planning for retirement, why he went back to work as a consultant a year after retiring, why their plans of relocating to a different state have since changed, what his Roth conversion plan is, and more!  Links in this episode:Tenon Financial monthly e-newsletter - Retirement Planning InsightsYouTube channel - Retirement Planning Education (formerly Retirement Planning Demystified)Retirement Planning Education website - www.RetirementPlanningEducation.comTo send Andy questions to be addressed on future Q&A episodes, email andy@andypanko.comAndy's LinkedIn profile: https://www.linkedin.com/in/andypanko/

Olivier Roth is the Co-founder and Chief Growth Officer at The Swarm, a go-to-network platform that helps companies and investors map, combine, and activate relationship networks for sales, recruiting, and fundraising. He helps lead the company's growth strategy, building systems that turn relationship data into warm introductions and stronger business opportunities. Previously, Olivier founded Timelapse, a strategic creative agency that worked with high-growth startups and brands, including LinkedIn, Lyft, and Stanford Research Park. His work focuses on helping teams use authentic relationships to create more practical, scalable paths to growth. In this episode… Cold outbound can create opportunities, but the strongest path to a deal often starts with a trusted relationship already inside your extended network. When teams can map those relationships, identify the right connectors, and ask for introductions with care, how can they turn relationship networks into a repeatable growth channel? Olivier Roth, a relationship intelligence leader who has spent years helping teams uncover warm introduction paths, says the key is treating networks as structured business assets rather than loose collections of contacts. He highlights the importance of mapping relationships among employees, investors, advisors, customers, partners, and industry friends to identify the most credible path to a target account. Instead of relying on cold emails or broad LinkedIn connections, Olivier explains how teams can use relationship data to identify stronger, more actionable introduction paths. The result is a more human go-to-market motion where AI helps surface the path, but people still build trust, protect social capital, and personalize the ask. In this episode of the Inspired Insider Podcast, Dr. Jeremy Weisz sits down with Olivier Roth, Co-founder and Chief Growth Officer at The Swarm, to discuss how relationship networks can become a stronger source of pipeline. Olivier breaks down warm introductions, reverse-engineered intro paths, and connector-driven network graphs. He also shares how AI, Claude, Salesforce, and Klarna fit into relationship-led growth.

Day Break | Peace Or Escalation? Iran, Election Fraud & America's Future --- 00:00 - Monologue 19:10 – Eugene Kontorovich, Senior Legal Fellow at Advancing American Freedom. Kontorovich discusses legal and constitutional questions surrounding efforts by Democratic lawmakers to scrutinize Jewish charities that support Israeli communities, examining the intersection of nonprofit law, foreign policy, and religious freedom. 28:04 – Nick Hopwood, Certified Financial Planner and Founder of Peak Wealth Management. In this week's No Lazy Money, Hopwood discusses persistent inflation, interest rate expectations, retirement planning, and the financial challenges facing Americans. Topics include retirement confidence, the long-term potential of Trump Accounts and Roth investing, student loan debt's impact on retirement, and why building a comprehensive financial plan has never been more important. 38:17 - Monologue Featuring Ivey Gruber 47:19 – Brandon Arnold, Executive Vice President of the National Taxpayers Union. Arnold discusses the rapid expansion of data centers, examining their economic impact, tax implications, infrastructure demands, and why he believes these projects can provide long-term benefits for both taxpayers and local communities. 57:36 – Pastor Lorenzo "Zo" Sewell, Senior Pastor of 180 Church in Detroit. Sewell discusses allegations of voter fraud affecting his Detroit church, reflects on election integrity concerns, and previews what he expects President Trump to address during his nationally anticipated evening speech. 1:06:30 – Chris Hagerman, Bath School Museum Committee. Hagerman discusses ongoing efforts to preserve the history of the 1927 Bath School disaster through the proposed Bath School Museum, highlighting fundraising efforts, the importance of remembering the tragedy, and the museum's mission to educate future generations. 1:16:43 - Monologue 1:25:44 – Dennis Kneale, bestselling author, veteran business journalist, and author of Ore-Goners. Kneale examines changing public attitudes toward capitalism, discussing why confidence in the free market has declined, the cultural and economic factors driving that shift, and what it could mean for America's future. 1:36:02 – Gordon G. Chang, author of Plan Red and China Is Going to War. Chang discusses concerns surrounding foreign election interference, focusing on China's influence operations, cybersecurity threats, and the challenges of protecting U.S. elections from foreign adversaries. 1:44:59 – Ivey Gruber, President of the Michigan Talk Network. Gruber discusses the growing influence of private equity on everyday life, including rising costs for family entertainment, while also covering the impact of wildfire smoke drifting into the United States from Canada and other notable headlines from around the country. --- Check out our brand new podcast, 'Forgotten America'... Episode 22 is live NOW at Steve Gruber on YouTube! Link below: https://youtu.be/Dfr8Z_syB-M

Are you building a business or has your business started controlling you?In this episode of the Know Your Numbers Podcast, Chris McCormack reveals the financial systems that help entrepreneurs escape the stress of living paycheck to paycheck and build lasting financial freedom. Learn why emergency funds matter, where business owners should invest first, how retirement and Roth strategies fit into your plan, and why alternative investments can accelerate long-term wealth.If you're a business owner, entrepreneur, real estate investor, or self-employed professional, these practical money management strategies can help you reduce financial anxiety, strengthen cash flow, and create a business that serves your life, not the other way around.Like, Follow & Share if you're ready to build a business that gives you freedom.••••••••••••••••••••••••••••••••••••••••••••➤➤➤ To become a client, schedule a call with our team➤➤ https://www.betterbooksaccounting.co/booking-calendar/better-books-consultation••••••••••••••••••••••••••••••••••••••••••••Connect with Better Books on Social MediaFacebook: https://www.facebook.com/betterbooksaccounting.coInstagram: https://www.instagram.com/betterbooksaccounting.co→ → → SUBSCRIBE TO BETTER BOOKS' YOUTUBE CHANNEL NOW ← ← ← https://www.youtube.com/@betterbooksaccountingThe Know Your Numbers REI podcast is for general information purposes only and is not intended to provide, and should not be relied on for, tax, legal, or accounting advice. Information on the podcast may not constitute the most up-to-date legal or other information. No reader, user, or listener of this podcast should act or refrain from acting on the basis of information on this podcast without first seeking legal and tax advice from counsel in the relevant jurisdiction. Only your individual attorney and tax advisor can provide assurances that the information contained herein – and your interpretation of it – is applicable or appropriate to your particular situation. Use of, and access to, this podcast or any of the links or resources contained or mentioned within the podcast show and show notes do not create a relationship between the reader, user, or listener and podcast hosts, contributors, or guests.

Welcome back to the Dollar Wise Podcast. In this episode, Andrew Barnhardt, CFP, and Brett Herron, CFP, take a deep dive into Roth conversions — what they are, why so many pre-retirees and retirees are asking about them, and when they do (and don't) make sense. Andrew and Brett walk through the core benefits of converting pre-tax retirement dollars to Roth, including lowering future required minimum distributions, creating a tax-free pot of money for large expenses, hedging against potential future tax increases, and leaving a tax-free inheritance to heirs. They also cover the practical side of paying the resulting tax bill, scenarios where converting may not be the right move — including charitable giving goals — and real examples of when conversions have paid off for clients. Throughout, they emphasize that Roth conversions are a personal, best-guess optimization strategy that should be made in coordination with a tax professional and financial advisor, not a one-size-fits-all recommendation.Tune into this episode to also learn:● What a Roth conversion is and how it differs from a regular Roth contribution.● How Roth conversions can help reduce future required minimum distributions.● The most tax-efficient ways to pay for a Roth conversion when it comes due.● Why charitable giving goals can change whether a conversion makes sense.What we discussed● [00:00:31] Kicking off the episode: introducing today's topic, Roth conversions.● [00:00:50] What a Roth actually is — after-tax contributions, tax-free growth, and tax-free qualified withdrawals.● [00:03:27] What a Roth conversion is and how it differs from contributing directly to a Roth account.● [00:06:54] Advantage #1: how converting to Roth can lower future required minimum distributions (RMDs).● [00:09:13] Smoothing retirement income over time to avoid higher tax brackets and other income-based traps.● [00:09:54] Advantage #2: building a tax-free pot of money for large or unexpected expenses.● [00:11:46] Advantage #3: using conversions as a hedge against potential future tax rate increases.● [00:13:11] Advantage #4: tax-free inheritances and gifting Roth dollars to heirs.● [00:15:46] How to actually pay the tax bill on a conversion — cash, taxable accounts, and what to avoid.● [00:19:16] Three scenarios where a Roth conversion may not make sense.● [00:21:41] Qualified charitable distributions (QCDs) and leaving pre-tax IRAs to charity.● [00:23:36] A real client example: how consistent conversions during low-income years changed one business owner's retirement picture.● [00:24:13] Why peak earning years are usually the wrong time to convert.● [00:25:49] Closing thoughts: Roth conversions are a personal decision based on your own goals, not trends.3 Things To Remember1. Roth conversions are about optimization, not necessity — they're rarely what makes or breaks a retirement.2. Whether a conversion makes sense depends on your own tax bracket today versus your expected bracket later — not on trends or what your neighbor is doing.3. How you pay the tax on a conversion matters — paying from cash or a taxable account is generally more efficient than withholding from the conversion itself.Memorable moments:(00:06:54) "Roth conversions are a way of moving some of that income forward into your retirement to lower your RMDs, therefore lowering the tip that you give Uncle Sam."(00:11:46) "It's a hedge against future tax rate increases... if you convert money from pre-tax to Roth, you insulate yourself somewhat against some of those tax potentials in the future."(00:19:16) "If doing a Roth conversion is going to hurt you financially for your retirement, it would be more necessary to not do it."Useful LinksConnect with Brett Herron: bherron@hfmadvisors.comLinkedIn: https://www.linkedin.com/in/brett-herronConnect with Andrew Barnhardt: abarnhardt@hfmadvisors.comLinkedIn: https://www.linkedin.com/in/andrew-barnhardt-cfpLike what you've heard...Learn more about HFM HERE: https://hfmadvisors.com/Schedule time to speak with us HERE: https://calendly.com/hfminquirycall/360102 WEST HIGH STREET, SUITE 200GLASSBORO, NJ 08028HFM Investment Advisors, LLC is a registered investment adviser. All statements and opinions expressed are based upon information considered reliable although it should not be relied upon as such. Any statements or opinions are subject to change without notice. Information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. All investments involve risk and are not guaranteed. Information expressed does not take into account your specific situation or objectives and is not intended as a recommendation appropriate for any individual. Listeners are encouraged to seek advice from a qualified tax, legal, or investment advisor to determine whether any information presented may be suitable for their specific situation. Past performance is not indicative of future performance.

David McKnight addresses one of the most common questions he gets: "If tax rates are going to be dramatically higher in the future, shouldn't I be putting every dollar into a Roth 401(k)?". Moreover, people often wonder whether they should be converting as much of their IRA to Roth as quickly as possible. David is a firm believer that the current tax rates are as low as we're likely to see in our lifetime. The U.S. has over $39 trillion in debt and it's going to increase by two trillion per year over the next 10 years and over $200 trillion in unfunded obligations for Social Security, Medicare, and Medicaid. Many people make the critical mistake of thinking that every retirement plan contribution should be immediately redirected into Roth accounts. However, David stresses, if you're a high-income earner contributing heavily to a Roth 401(k) today may actually be one of the most expensive tax decisions you can make. David explains why he has long argued that 24% is the sweet spot. The so-called Retirement Income Valley is the window of opportunity that opens up immediately after retirement and before social security required minimum distributions kick in. David touches upon IUL and why he doesn't suggest that it should replace your 401(k) or serve as a stock market alternative… Remember: your 401(k) should remain the primary engine driving your retirement plan.  Once you've maximized that tax deduction, an IUL can serve a very important supporting role, though. An Ernst & Young study examined what happens when retirees allocate a portion of their retirement savings to a maximum-funded index universal life policy. Researchers found that if you could divert 30% of your retirement contributions to an IUL with the goal of saving 3-5 years of living expenses by day one of retirement, it helps shield you from stock market volatility. "The IUL isn't designed to replace the investment portion of your portfolio, it's there to protect it", clarifies David. The best retirement strategy isn't the one that sounds the most compelling, it's the one that maximizes the likelihood that your money lasts as long as you do. Mentioned in this episode: David's national bestselling book: The Guru Gap: How America's Financial Gurus Are Leading You Astray, and How to Get Back on Track DavidMcKnight.com DavidMcKnightBooks.com PowerOfZero.com (free video series) @mcknightandco on Twitter  @davidcmcknight on Instagram David McKnight on YouTube Ernst & Young   

The market is hitting new highs, but that doesn't mean your investment strategy is working. In this episode, Art Wiederman and Joe Kalinowski explain why building wealth as a dentist has far less to do with predicting the next winning stock and far more to do with having the right long term plan.From the strong performance of large cap, small cap, and international markets to the growing impact of AI on investing, Art and Joe break down what's happening in today's market and what it means for dentists. They discuss why chasing returns often leads to poor decisions, how diversification and disciplined portfolio management can help reduce risk, and why your investment strategy should evolve throughout your career. The conversation also explores retirement planning, tax efficient investing, Roth conversions, selling a dental practice, and practical financial decisions that can have a lasting impact on your wealth. Whether you're buying your first practice, growing your investments, or preparing to retire, this episode offers practical guidance to help you make smarter financial decisions.Follow us on our Socials!Instagram: @artofdentalfinanceFacebook: The Art of Dental Finance and ManagementLinkedIn: Art WiedermanTiktok: theartofdentalfinance&mgmtConnect with Joe!Email:Joe@earned.comWebsite:https://www.earned.com/Contacts:877 939 2500. 925 280 5706--------------Stop feeling overwhelmed by the numbers. ADCPA member firms specialize exclusively in serving dentists to help you achieve financial success. Gain a strategic partner who understands industry benchmarks and overhead management so you can focus on clinical excellence.Find your expert: Visit https://adcpa.org/ to find a trusted dental CPA near you. Your numbers should work as hard as you do.--------------Detect what traditional diagnostics miss. Innerview uses FDA-cleared technology to measure internal tooth mobility, helping you identify cracks and loose restorations earlier before they become emergencies. The result is better treatment planning, fewer surprises, and stronger patient trust, all without disrupting your workflow.Book a demo at Innerview.ai and mention Art Wiederman to receive $250 off.

Tonight on America at Night with McGraw Milhaven: Mike Fox, Legal Fellow with the Cato Institute's Project on Criminal Justice, joins the show to discuss ICE's decision to temporarily limit traffic stops following recent fatal shootings involving federal agents. Fox examines the legal and operational implications of the policy change and what it could mean for immigration enforcement moving forward. Gabe Roth, Executive Director of Fix the Court, discusses why the U.S. Supreme Court is requesting millions of dollars in additional funding for security. Roth explains the increasing security concerns facing the justices, the role of Congress in funding the Court, and the broader conversation about protecting the judiciary. Later, Bryan Burhans, director of Outer Banks Forever, joins the program to highlight his organization's work supporting Cape Hatteras National Seashore, Fort Raleigh National Historic Site, and the Wright Brothers National Memorial in North Carolina. Burhans discusses preserving these historic landmarks and why they remain must-visit destinations for travelers and history enthusiasts alike. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Schedule a Free Financial Assessment with an experienced professional:https://bit.ly/YMYWassessCToday on Your Money, Your Wealth® podcast 590, Joe Anderson, CFP® and Big Al Clopine, CPA spitball for people with a small fortune sitting in pre-tax accounts turning into a tax bomb. We'll find out how Roth conversions and careful tax liability management can optimize their retirement income strategy. Eric in California is 72 with nearly four million dollars in pre-tax accounts. How much should he transfer in Roth conversions? Is borrowing against his own house to pay the tax bill brilliant or bonkers? Rick and Kiani hoping they can quit sooner than they think. Mike just hit full retirement age. Should he claim Social Security benefits now or wait until age 70? And finally, Jeff wants to walk away at 59 with a roadmap for aggressive Roth conversions, assuming the tax cliff doesn't get him first. Free Financial Resources in This Episode: https://bit.ly/ymyw-590 (full show notes & episode transcript)Retirement Accounts Guide - free download:https://purefinancial.com/white-papers/retirement-accounts-guide/?utm_source=captivate&utm_medium=podcast&utm_campaign=whitepaper-retirement-accounts-guide&utm_content=ymyw-pod-ep590-description-whitepaperFinancial Blueprint (free, self-guided):https://purefinancial.com/financialblueprint/?utm_source=captivate&utm_medium=podcast&utm_campaign=financial-blueprint&utm_content=ymyw-pod-ep590-description-blueprintRetirement Checklist: Check Off These 7 Things Before You Retire - YMYW TV: https://purefinancial.com/ymyw/episodes/retirement-checklist-check-off-these-7-things-before-you-retire/?utm_source=captivate&utm_medium=podcast&utm_campaign=ymyw-tv&utm_content=ymyw-pod-ep590-description-tv-s12e05REQUEST your Retirement Spitball Analysis:https://bit.ly/YMYWaskCDOWNLOAD more free guides:https://bit.ly/YMYWguidesCREAD financial blogs:https://bit.ly/YMYWblogCWATCH educational videos:https://bit.ly/YMYWvidsCSUBSCRIBE to the YMYW Newsletter:https://bit.ly/YMYWnewsletterCConnect With Us:Subscribe on YouTube and join the conversation in the comments:https://bit.ly/YMYW-YTSubscribe or follow YMYW in your favorite podcast app:https://lnk.to/ymywLeave your honest reviews and ratings in Apple Podcasts:https://podcasts.apple.com/us/podcast/your-money-your-wealth/id312900254Chapters: 00:00 - Intro: This Week on the YMYW Podcast01:01 - $3.9M Pre-Tax at 72: How Do We Minimize Taxes Before RMDs Hit? (Eric, CA)11:13 - We're on One Salary. Can We Retire at 62 With $1.7M and a $56K SS Benefit? (Rick & Kiani, Southern CA)23:16 - Just Hit Full Retirement Age. Should I Delay Social Security or Start Now? (Mike, 66, NV)31:04 - Retiring With $4M and a Roth Conversion Roadmap at Age 59. Does Our Plan Hold Up? (Jeff & Amber, 55, Orlando, FL)44:54 - Outro: Next Week on the YMYW Podcast

Having a child later in life can change far more than your sleep schedule. It can completely rewrite your retirement plan.Don and Tom explore the financial realities of becoming a parent in your late 40s or 50s, from college savings and life insurance to delayed retirement and the temptation to sacrifice your own financial future for your children. Tom brings some very personal experience to the conversation—and a few stories about being mistaken for his daughter's grandfather.Then, a listener asks about a simple three-fund retirement portfolio, international diversification, small-cap value, Roth asset location, and when an aggressive investor should finally consider adding bonds.Plus, why the best retirement portfolio may be the one that keeps you from doing something stupid during the next bear market.00:12 Old guys, act your age—and other financial lessons01:14 Disagree with Don and Tom? Send in your argument01:57 The financial reality of becoming a parent later in life03:17 Tom became a father at 5004:11 The dangers of grocery shopping with your daughter05:21 Are older parents actually better parents?06:10 How a late child can completely change retirement plans07:28 Why retirement should come before college savings08:48 A $36,000-a-year whole life insurance quote09:08 How long does a parent really need term life insurance?10:42 Fertility costs and the financial price of parenthood11:28 Your retirement must remain the financial priority12:50 Having a child at 50 may mean working until 6813:42 What are you actually going to do in retirement?15:19 Tom reflects on raising his youngest daughter16:02 Don and Tom need more listener questions17:17 Listener portfolio review: FZROX, FZILX, and AVUV18:49 Is 50% U.S., 30% international, and 20% small value reasonable?20:01 Should high-growth assets go in a Roth IRA?20:43 When should an aggressive investor start adding bonds?21:25 Bonds may keep you from doing something stupid22:53 Remembering investor panic after 9/1123:21 How to get a free Talking Real Money portfolio analysis25:16 Why Talking Real Money is differentQuestions? Comments? Click!

Kate and Guy are back from Roth. We hear their feedback from the event and Kate tells us how her marathon went! We review the racing from the WTCS Hamburg and Hayden Wilde's personal challenges getting over sickness plus Cassandre Beaugrand's race at the Diamond League and her record-breaking achievements. The IRONMAN 70.3 in Swansea finished early for Mika Noodt after a bike crash. We chat about safety concerns on race courses. After Danielle Lewis's announcement of her REDS diagnosis we delve into the critical role of nutrition in athletic performance. The conversation highlights the need for coaches to be vigilant about their athletes' nutritional habits and the potential consequences of underfuelling. Additionally, we explore the different types of body composition and the significance of metabolic efficiency in endurance sports. TIMESTAMPS: 0:00:00 – Kate and Guy are back from Roth 0:04:48 – Kate's marathon 0:05:53 – Cassandre Beaugrand and Alex Yee at the Diamond League 0:08:55 – WTCS Hamburg 0:11:56 – Hayden Wilde 0:20:29 – WTCS Women's Race 0:21:11 – Lisa Tertsch's racing making her unpopular? 0:31:36 – IM703 Swansea safety concerns 0:33:23 – The worst run of Jack's career 0:38:10 – Mika Noodt's bike crash 0:40:24 – This weekend IRONMAN Lake Placid 0:43:19 – Danielle Lewis announces she has REDS 0:44:27 – The hosts experiences of underfuelling in athletes 0:51:16 – Jack goes to the chiropractor 0:52:49 – Nutrition and underfuelling 0:59:37 – Metabolic efficiency and testing LINKS: Jack Moody at https://www.instagram.com/jacktmoody/ Kate Bevilaqua at https://www.instagram.com/katebevilaqua/ Guy Crawford at https://www.instagram.com/guyrcrawford/ Challenge Roth at https://www.challenge-roth.com/en/ WTCS Hamburg - https://events.triathlon.org/2026-wtcs-hamburg IRONMAN 70.3 Swansea at https://www.ironman.com/races/im703-swansea Danielle Lewis https://www.instagram.com/danilewistri/ Mika Noodt https://www.instagram.com/mika.noodt/ Cassandre Beaugrand https://www.instagram.com/cassandrebeaugrand/

Should you invest all savings into Roth or invest in a different way? Quint and Logan talk through their thoughts. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Money Monday has arrived, and Don kicks off a new weekly series based on his book Financial Fysics. The first “law” may surprise you: according to Don, every dollar ever earned comes from just three sources—luck, theft, or work. He and Tom debate where investing belongs, why entrepreneurship remains one of the best paths to wealth, and how much luck really contributes to financial success.Then they answer a listener's retirement planning question about whether to finance a Florida townhouse or withdraw money from a Roth IRA. Along the way they discuss Roth conversion strategy, Florida HOA reserve funds, special assessments, and why building a retirement plan should always come before deciding where the money comes from.00:00 Welcome to Money Monday00:12 A new weekly Financial Fysics series begins01:35 Why anonymous two-star book reviews are so frustrating02:40 Free Financial Fysics book giveaway03:50 Rule #1: There are only three ways to make money04:45 Luck—including investing, lotteries, and inheritance06:35 Theft, fraud, and unethical financial products07:55 Why successful investing combines work and luck10:30 How most great fortunes are actually built12:10 Entrepreneurship, risk, and creating wealth13:35 Understanding just how large a trillion dollars really is15:50 The biggest takeaway from Rule #117:15 Preview of next week's rule: Supply and Demand18:15 Why listener questions slow down during the summer19:15 Listener Question: Should a retiree finance a Florida townhouse or withdraw money from a Roth IRA?21:10 Florida HOA reserves and avoiding expensive surprises24:30 Why retirement planning comes before choosing an account26:00 Why the Roth IRA is probably the last account to tapQuestions? Comments? Click!

If you'd like to help a child, grandchild, or other young person get started investing, you have a few options when it comes to the type of account to open. Starting this month, a new option is available: Trump Accounts. Fools Robert Brokamp and Joel O'Leary discuss the details, pros, and cons. Topics covered:-Eligibility and contribution limits for Trump Accounts-The tax advantages, including potentially converting them to Roth accounts-The drawbacks, limitations, and potential penalties if money is withdrawn before age 59 1/2-The best use cases for Trump Accounts, and other types of accounts that might be more appropriate for the youngsters in your lifeHost: Robert Brokamp, CFP®, EAGuest: Joel O'LearyEngineer: Bart Shannon Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

While Pat is on vacation, Scott and partner advisor Richard Del Monte break down two high-stakes financial scenarios that highlight the difference between "good on paper" and "good in practice." Through two detailed caller case studies, they explore: Case Study 1: The $450k New Doctor. After 15 years of medical training, a 32-year-old is finally hitting a massive salary. But with multiple retirement options like 403(b)s and non-governmental 457 plans, her father is worried about "tying her hands" too early. Scott and Richard explain why some retirement plans are actually "traps" for young high-earners and how to use the "mega backdoor" Roth to maximize flexibility. Case Study 2: The $1.1M Retirement Reality Check. A couple plans to retire next year with just over $1 million, but they're facing $125k in immediate "one-time" expenses for a wedding and new vehicles. The duo discusses the "4% Rule," the danger of "confusing a bull market with brilliance," and why a 19% return today doesn't guarantee a stress-free tomorrow. The Philosophy of Work: Richard Del Monte shares his personal "25-year plan" at age 70 and discusses why the most successful people often choose engagement over a traditional retirement.   Join Money Matters:  Get your most pressing financial questions answered by Allworth's co-founders Scott Hanson and Pat McClain. Call 833-99-WORTH. Or ask a question by clicking here.  You can also be on the air by emailing Scott and Pat at questions@moneymatters.com. Download and rate our podcast here.

Drew has finally vanquished Roth, so fellow Defectors Diana Moskovitz and Dave McKenna are on the show! First, World Cup – who's rooting for who? Are either of them for it coming ‘ome to England? How expensive are these tickets exactly?! Then, they open up the fun bag to answer real questions from Defector readers and Distraction listeners. Can this one easy rule change make soccer exciting for Americans? Do you want to hear your question answered on the pod? Well, give us a call at 909-726-3720. That is 909-PANERA-0!Stuff We Talked AboutHalf price burgers on Monday nightsEnormous badonkadonksDifferent EuropeKorean light sticksGaelic football's superior rulesSponsors- MeUndies, where you can get up to 50% off their Subscribe & Save dealCredits- Hosts: Drew Magary & David Roth- Producer: Brandon Grugle- Editor: Mischa Stanton- Production Services & Ads: Multitude Podcasts- Subscribe to Defector!About The ShowThe Distraction is Defector's flagship podcast about sports (and movies, and art, and sandwiches, and certain coastal states) from longtime writers Drew Magary and David Roth. Every week, Drew and Roth tackle subjects, both serious and impossibly stupid, with a parade of guests from around the world of sports and media joining in the fun! Roth and Drew also field Funbag questions from Defector readers, answer listener voicemails, and get upset about the number of people who use speakerphone while in a public bathroom stall. This is a show where everything matters, because everyone could use a Distraction. Head to defector.com for more info.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.