Podcasts about Daley

Alonzo Smith v. Richard Daley

Welcome to episode 498 of the Mobile Tech Podcast with guests Christian de Looper (BGR), Jason Howell (Android Faithful), C Scott Brown (Android Authority), Adam Doud (SlashGear), Nick Gray (Phandroid), Dean Daley (MobileSyrup), and Sascha Segan (Qualcomm) -- brought to you by Mint Mobile. In this episode, join us pondside as we recap everything that was announced at Qualcomm's Snapdragon Summit 2026 in Maui -- including the new Snapdragon 8 Elite Extreme Gen 6 and 8 Elite Gen 6 -- then dive into the latest flagships from Motorola, Xiaomi, Oppo, and Vivo, plus new smart glasses from Meta... Good times! (Special thanks to Qualcomm for covering travel.)Episode Links- Support the podcast on Patreon: https://www.patreon.com/tnkgrl- Donate / buy me a coffee (PayPal): https://tnkgrl.com/tnkgrl/- Support the podcast with Mint Mobile: https://mintmobile.com/mobiletech- Christian de Looper: https://www.threads.net/@christiandelooper- Jason Howell: https://www.threads.net/@thatjasonhowell- C Scott Brown: https://www.threads.com/@c.scottbrown- Adam Doud: https://www.threads.net/@deadtechnology- Nick Gray: https://www.threads.net/@nickmgray- Dean Daley: https://www.threads.com/@deandaley_- Sascha Segan: https://www.threads.com/@saschasegan- Qualcomm Snapdragon Elite Gen 6 benchmarks (1): https://www.bgr.com/2268742/qualcomm-snapdragon-8-elite-gen-6-benchmarks-performance/- Qualcomm Snapdragon Elite Gen 6 benchmarks (2): https://www.youtube.com/watch?v=5blJhnOPLoo- Qualcomm Snapdragon Sound Elite Gen 2: https://mobilesyrup.com/2026/09/23/qualcomm-sound-elite-gen-2/- Qualcomm wants its AI chips on every device: https://aiinside.show/episode/qualcomm-wants-its-ai-chips-on-every-device- New Microsoft Surface devices: https://www.zdnet.com/tech/surface-pro-laptop-snapdragon-x2-plus-hands-on/- Motorola Signature 27 (1): https://www.gsmarena.com/motorola_unveils_signature_27_with_200mp_telephoto_camera_snapdragon_8_elite_extreme_gen_6-news-74726.php- Motorola Signature 27 (2): https://mobilesyrup.com/2026/09/22/motorola-unveils-signature-27-first-with-snapdragon-8-elite-extreme/- Xiaomi 18 Pro/Pro Max: https://www.gsmarena.com/xiaomi_18_pro_and_18_pro_max_arrive_with_latest_snapdragon_chips_privacy_displays_and_more_useful_re-news-74733.php- Oppo X10 Pro Max: https://www.gsmarena.com/oppo_find_x10_pro_max_launches_with_three_200mp_rear_cameras_dimensity_9600_pro_soc-news-74714.php- Vivo X500 series: https://www.gsmarena.com/vivo_x500_x500_pro_and_x500_pro_max_announced-news-74698.php- New Meta smart glasses: https://www.engadget.com/2267230/everything-announced-at-meta-connect-2026/- Meta VR Glasses: https://phandroid.com/2026/09/24/metas-1299-vr-glasses-could-fix-what-made-you-give-up-on-vr/- Ray-Ban Meta Audio glasses: https://phandroid.com/2026/09/24/meta-is-ditching-the-camera-to-shake-its-pervert-glasses-label/- Nothing spins off CMF: https://www.gsmarena.com/nothing_makes_cmf_an_independent_indian_brand-news-74713.php- Clicks Communicator updates: https://discover.clicks.tech/big-updates-clicks-communicatorAffiliate Links (If you use these links to buy something, we might earn a commission)- Moto Razr Fold: https://link.amazon/B053lsgeJ- Google Pixel Watch 5: https://link.amazon/B0ghO0WVj- Samsung Galaxy Buds4 Pro: https://link.amazon/B0cAYV3pe- Microsoft Surface Laptop 13" (2026): https://link.amazon/B0ioNH8L0- Meta Ray-Ban Audio Clubmaster: https://link.amazon/B0cS3sS69

This is a free preview of a paid episode. To hear more, visit andrewsullivan.substack.comJake is a journalist and a dear old friend, starting in our early days as interns together at TNR. He's the former longtime editor of Slate and the co-founder of the podcast company Pushkin Industries. He's also the chairman of The Committee to Protect Journalists and a regular contributor to the New York Review of Books. His new book is called Profiles in Cowardice: A Study of Collaboration in the Trump Era.A polished transcript is here, including money quotes. Below are timestamps for the main sections of the pod:* 04:09: Jake's background that made him especially attuned to corruption and totalitarianism* 18:45: Contrasting the craven Lindsey Graham with the principled Liz Cheney* 25:45: How Megyn Kelly — and others demonized by the left — came to support Trump* 35:15: Liberal lawyers like Brad Karp who needlessly bent the knee* 45:52: Debating the culpability of colleges targeted by Trump* 53:36: Jeff Bezos' 180 and his lifelong obsession with space travel* 58:43: The abomination of January 6th and McConnell caving over the impeachment* 102:28: Debating the culpability of John Roberts for Trump's success* 117:26: Reminiscing on our early days at TNR and the genius of Mike KinsleyFor two clips of the episode — on why McConnell balked at banning Trump, and how Megyn Kelly became a bully — head to our YouTube page.Other topics: growing up in Chicago with public servants for parents; his dad taking on the Daley machine; Jake's talent for takedowns back at TNR; South Park mocking Trump; Stop the Steal and Jan 6; Biden's clusterfuck campaign; the Cheneys backing Harris; Trump's retribution; the weakness of Schumer; McCain's nonconformity; Massie's cojones; the university deals with Trump; his talent as a bully; higher ed's dearth of viewpoint diversity; anti-semitism in the Ivy League; Musk and the big subsidies for SpaceX; decimating USAID and PEPFAR; Bezos funding the Melania doc; SCOTUS checking tariffs; the presidential immunity ruling; the post-presidencies of Bush and Obama; and the one magazine piece I would never write.Browse the Dishcast archive for an episode you might enjoy. Coming up: Emily Eakin on the French postmodernists, Sean Illing on the relevance of Camus and Nietzsche, Michael Lewis on the bureaucrats who fought back against Trump, and Evan Barker on how the Democratic Party got hijacked by elite activists. Please send any guest recs, dissents, and other comments to dish@andrewsullivan.com.

NL Conservative MPs are wondering why French fishermen are gaining access to snow crab outside 200-mile limit + People in St. Mary's are devastated by news that the town's crab plant will not be rebuilt there + Southern Harbour mayor Joe Brewer says investment from Daley Seafoods is good for the area.

On this episode, Alex Bozich is joined by Zach Horwitz of Inside the Hall to discuss the news of Kellan Wyatt, Stephen Daley and Sam Alexis being granted a preliminary injunction for eligibility, IU football's 3-0 start and Friday's game against Northwestern. Alex and Zach also share some thoughts on the upcoming 2026-27 IU basketball season.Support Inside the Hall and Podcast on the Brink with a donation: https://www.insidethehall.com/recommends/donate-to-inside-the-hall/Subscribe to Peacock to watch Indiana men's and women's basketball: https://www.insidethehall.com/recommends/peacock (affiliate link)Subscribe to B1G+ to watch Indiana men's and women's basketball: https://www.insidethehall.com/recommends/big-ten-plus/ (affiliate link)Buy IU basketball tickets at Vivid Seats: https://www.insidethehall.com/recommends/vivid-seats (affiliate link)

Big news for Indiana athletics: Stephen Daley and Kellen Wyatt are eligible to play, after a Monroe County court granted temporary relief in the NCAA eligibility case. The ruling also affects Sam Alexis in men's basketball, Avry Tatum in volleyball, IU swimmers, and other athletes involved in the case.In this breaking CrimsonCast update, Galen Clavio explains what the court found, why the NCAA's treatment of the 2022 recruiting class became central to the dispute, and how the organization's move toward a five-years-to-play-five model created a major inconsistency. The ruling points specifically to how athletes from the 2022 class who had already played four seasons were excluded while redshirted athletes and later classes were treated differently.Galen also breaks down the court's criticism of the NCAA's rulemaking process, previous eligibility exceptions involving COVID seasons, junior-college transfers and former professional athletes, and why the judge found immediate relief necessary with several college sports seasons already underway.The temporary order is not necessarily the final word, but for Indiana the immediate impact is significant: Daley and Wyatt can return to the football defense, while Alexis and Tatum also regain eligibility for their respective IU programs.Subscribe to the Back Home Network for more CrimsonCast, Indiana football, IU basketball and breaking Indiana athletics coverage.

A great real estate agent's work starts before a home is listed. After 26 years in the business, Christine Daley explains why she advises sellers on where to spend their prep budget, stays responsive when clients are anxious, and asks the questions that reveal what each side needs in a negotiation.For business owners, her approach is a reminder that trust grows through steady service, especially when the stakes are high.Need a VA to give you extra leverage in your business right now? Pick a time that works: https://sl1nk.com/Kwqm3mP#RealEstateBusiness #RealEstateAgents #ClientService #RealEstateNegotiation #HomeSelling #BusinessGrowth #Delegation

Galen Clavio covers a packed week in Indiana Athletics, including No. 2 IU men's soccer, No. 18 Indiana volleyball, Brooksley Colvin's women's basketball commitment and the latest on the eligibility cases involving Stephen Daley and Kellen Wyatt.The football conversation turns toward Indiana vs. Northwestern on Friday night, when IU gets an exclusive national window on FOX. Galen discusses how dramatically the program's place in college football has changed — and why this game provides the first major national showcase of the 2026 season.Finally, Galen compares Indiana's 2025 and 2026 PFF grades through the opening three games. Despite the criticism surrounding Josh Hoover and the Western Kentucky performance, the numbers show a team playing at a level remarkably similar to where last year's national champions were at the same point. The run game still needs development, but the early data offers far more reason for patience than panic.

Indiana football is 2-0 and closes out its nonconference schedule against Western Kentucky on Saturday at Memorial Stadium. In this CrimsonCast preview, Galen Clavio breaks down the statistical mismatch, what Indiana still needs to improve before Big Ten play, Josh Hoover's early efficiency, the Hoosiers' increasingly dangerous rushing attack, and the uncertainty surrounding Stephen Daley and Kellen Wyatt.The episode opens with the ongoing eligibility situation involving Daley and Wyatt. Their temporary restraining order covered Indiana's first two games, but their status for Western Kentucky remained unresolved when this episode was recorded. Galen explains the court situation, which also involves IU basketball player Sam Alexis and volleyball player Avery Tatum, and why Indiana is still waiting for clarity.Then it is time for the matchup itself. Western Kentucky has endured a difficult start, including a 70-20 loss at Georgia, and the early statistical profiles show a major gap between the Hilltoppers and the defending national champions. Galen digs into Indiana's advanced numbers and identifies one area he would especially like to see improve: creating more consistent push in the running game against an FBS defensive front.The offensive numbers are already encouraging. Josh Hoover is completing more than 70 percent of his passes with eight touchdowns and no interceptions, putting his early efficiency in the same neighborhood as Kurtis Rourke and Fernando Mendoza. Turbo Richard and Lee Beebe Jr. have developed into a productive two-back attack in the absence of Khobie Martin, while Indiana is averaging more than five-and-a-half yards per rush as a team.At receiver, Charlie Becker has been absurdly efficient, producing five touchdowns on only seven receptions, while Nick Marsh is averaging more than 20 yards per catch. Galen also looks at Tyler Morris, Shazz Preston, and Davion Chandler, and why Indiana's combination of receiver depth, blocking demands, and different skill sets gives the offense so many options.The episode also checks Indiana's updated FPI win probabilities for the rest of the season, including Northwestern, Nebraska, Michigan, USC, Washington, Ohio State, and Purdue.Finally, Galen covers the Saturday gameday forecast — including a hot 4 p.m. kickoff, IU's updated water-bottle policy, Parents Weekend ticket demand, and tailgating conditions — before identifying the Western Kentucky players to watch, including quarterbacks Rodney Tisdale Jr. and Brock Glenn and running back A.J. Allen.Subscribe to the Back Home Network for more CrimsonCast, Indiana football, IU athletics, Big Ten football, and Hoosiers coverage throughout the 2026 season.

Mike Niziolek and Zach Osterman preview Indiana's final nonconference game, against Western Kentucky, updating injuries and eligibility statuses. Plus, a discussion of their forthcoming book! Chapters: 0:00 -- Intro 1:10 -- Digging into Western Kentucky 6:22 -- Comparison point to UGA? 8:26 -- What's the latest on Wyatt and Daley 15:03 -- Injury updates 23:02 -- Indiana's nonconference approach 32:52 -- Previewing "Unthinkable to Unstoppable" Read: https://www.indystar.com/story/sports/college/indiana/2026/09/13/indiana-football-charlie-becker-touchdown-catches-nfl-draft-stock/91732482007/ Get IndyStar's IU coverage sent directly to your inbox with our IU Insider newsletter: https://profile.indystar.com/newsletters/iu-insider/?ipid=NLsignupIU Preorder "Unthinkable to Unstoppable" today: https://bit.ly/4gezKxZ

On this episode of Sound Speed Action, we review Mayday, the new 80s style action comedy on Apple TV starring Ryan Reynolds and Kenneth Branagh, made in the vein of Midnight Run, 48 Hrs, and Red Heat. It's a lot of fun, it knows exactly what it is, and Branagh's Nikolai, a former KGB hermit who worships one bootleg VHS of Top Gun, turns out to be a genuine badass. I am not kidding. I did not see that coming.But I keep telling myself the two guys who made it are cursed. Jonathan Goldstein and John Francis Daley made Dungeons and Dragons: Honor Among Thieves, which everybody who saw it loved and Hollywood still called a disappointment. Then they made Mayday, finished it in the spring of 2024, and it sat on a shelf for two years before going straight to your phone. Cursed is not the right word, though. I found a better one, and I'll give it to you at the end of the episode, right after I tell you what they're making next.What We Cover:Nikolai Owns One Movie: A character set in 1987 who worships a film from 1986. Why the 80s homage in Mayday lives inside the character instead of being painted on top.Thin Is The Point: Red Heat did not have a serious position on the Cold War. Neither does this. Why the reviews knocking the politics are grading the wrong thing.The Villain Problem: One honest gripe about a good actor in a part nobody built.Two Years On A Shelf: Apple's habit of holding content that gets close to live geopolitics, and why a comedy stops being the same movie once the room around it changes.Same Week, Different Screens: A movie a studio decided was worthless opened in theaters. A movie built for theaters opened on your TV. Neither decision had anything to do with whether the movie was good.Not Cursed: Goldstein and Daley keep making movies that Hollywood keeps burying. I owe them a better word than cursed, and I found one. Stay to the end.Connect & Support:Show Website: https://www.ssapod.comFollow & Review: If you enjoyed this breakdown, please leave a review on your podcast app and follow the show for more cinema breakdowns.

Brian recaps a historic weekend for men's golf, a road sweep for volleyball, and much more during his weekly recap. Then, men's soccer head coach Chaka Daley discusses his team's tough loss at Notre Dame on Sunday, his early impressions of the team through four games, and Friday's Big Ten opener against Indiana. You can get tickets for the 7 p.m. game here in Ann Arbor at MGoBlue.com/Tickets. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

THE DEVIL WITHIN The New Monsters: Alligators in the Sewers — Episode Two: The Man Who Saw Them They kept seeing alligators. Sometime in the 1930s, New York sewer inspectors began returning from beneath the city with an increasingly ridiculous claim: there were alligators living beneath Manhattan. Their boss, Theodore “Teddy” May, had a more reasonable explanation. Whiskey. According to Robert Daley's 1959 book The World Beneath the City, May became convinced his workers had discovered somewhere underground to hide booze. He sent men to investigate. Nobody found the whiskey. But the alligator sightings continued. Eventually, Teddy May decided to descend into the sewers himself—and according to the story he later told, his flashlight swept across the water and revealed something he hadn't expected to see. Several alligators. In Episode Two of Alligators in the Sewers, The Devil Within heads back beneath 1930s New York to meet the men whose jobs took them into a hidden world most New Yorkers would never see. We explore what it was actually like to work inside Manhattan's enormous underground infrastructure, where sewer inspectors navigated brick tunnels by flashlight during the lowest-flow hours of the night. The dangers were very real: rapidly rising wastewater, powerful currents, blockages and deadly gases. And the things moving through those tunnels could be bizarre—barrels, Christmas trees, jewelry, false teeth, weapons and practically anything else New York managed to lose down a drain. Then we meet Teddy May. Part sewer worker, part foreman and apparently one hell of a storyteller, May would become the central figure in the sewer-alligator legend. His claims transformed the documented discovery of a single reptile beneath East Harlem into something much larger: an entire population living beneath Manhattan. And then, according to the legend, New York fought back. Daley's account describes an extraordinary extermination campaign in which sewer crews supposedly used poisoned food, powerful trunk-sewer currents and, in some versions, .22-caliber rifles to eliminate the animals. It's an irresistible image: Depression-era municipal workers disappearing through Manhattan manholes carrying flashlights and guns to hunt alligators beneath New York City. There's just one problem. The evidence for a citywide infestation—and the war supposedly waged against it—is considerably thinner than the story. No substantial contemporary municipal paper trail has emerged documenting an organized extermination campaign. What survives largely depends upon testimony recorded more than twenty years later. But folklore was already taking over. The ordinary reptiles of the earliest stories became pale, blind subterranean monsters, supposedly transformed by generations without sunlight and sustained by Manhattan's endless supply of rats. The biology doesn't work, but the mythology is perfect. An ordinary alligator beneath New York could simply be lost. A pale, blind alligator belonged there. This is the story of the men beneath the manholes, the raconteur who gave their stories life, and the moment an escaped exotic pet became something uniquely New York. This is The Man Who Saw Them. LISTEN • WATCH • FOLLOW Listen & Follow: Follow The Devil Within wherever you get your podcasts. Rate & Review: Leave a five-star rating and review to help new listeners discover the show. Watch & Subscribe: Watch The Devil Within on the Evio Creative YouTube channel. Subscribe and turn on notifications for full episodes and exclusive video content. Join the Conversation: Follow @thedevilwithinpod and tell us what you think Teddy May really saw beneath Manhattan. Stories, tips and strange encounters: info@eviocreative.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

Untold billions in dark money is funding MAGA efforts to hold on to the Senate. Ben riffs. Jessica Biggs makes her debut. Talking about her candidacy for school board president. How she was punished by Mayor Rahm's school flunkies for daring to speak out for clean schools. And the need to be independent of the mayor—even an all powerful one like Daley or Rahm—on TIFs. Also, a few words about charters, magnets and neighborhood schools. Jessica is currently on the Chicago school board.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Galen Clavio continues CrimsonCast's Indiana football positional preview series by moving to the defense, starting with what may be the strongest position group on the entire roster: the defensive line.The episode opens with the bigger statistical picture. Under Bryant Haines, Indiana has been one of the most disruptive defenses in the country over the last two seasons. Galen explains front-seven havoc rate, defensive PPA, tackles for loss per game, and why those numbers matter when trying to understand what IU's defensive front is designed to do. The short version: Indiana does not just want to hold up at the line of scrimmage. It wants to confuse quarterbacks, wreck blocking schemes, create negative plays, and make offenses operate under stress.The interior defensive line starts with Tyrique Tucker and Mario Landino, both of whom return after excellent seasons. Galen highlights Tucker's tackle reliability, leverage, movement skills, and preseason All-America recognition, while also pointing to Landino's low missed-tackle rate and strong pressure production. Together, they give Indiana a powerful starting point inside.The depth behind them is one of the more interesting parts of the preview. Joe Hjelle arrives from Tulsa as a proven, high-effort interior piece who can help right away, while Jhrievous Hall and Kyler Garcia represent the next stage of internal development under Pat Kuntz and Buddha Williams. Galen also discusses freshman names like Blake Smythe, Cameron McHaney, Gabe Hill, and Rodney White, noting that Indiana is getting closer to the point where defensive line depth can be cultivated in-house rather than rebuilt every year through the portal.The edge group brings even more upside, but also more uncertainty. Stephen Daley remains a major storyline because of his eligibility status, and Galen explains why Indiana wants him back so badly: 19 tackles for loss, 41 quarterback pressures, and the kind of disruptive speed that changed games last season. Kellen Wyatt is also part of that eligibility picture after giving IU important physicality and production before his injury.The returning and incoming edge talent gives Indiana plenty to work with regardless. Daniel Ndukwe flashed late last season and now looks like a major rotational weapon. Chiddi Obiazor brings Big 12 production, versatility, and the ability to slide inside on passing downs. Tobi Osunsanmi may be Indiana's best pure pass rusher if he is fully healthy after his injury at Kansas State, while Josh Burnham brings experience from Notre Dame and gives Haines another useful chess piece.The final takeaway is that Indiana's defensive front has a chance to be special. With Tucker and Landino inside, Obiazor and Osunsanmi coming off the edge, Ndukwe emerging, and the possibility of Daley and Wyatt returning, the Hoosiers have the kind of depth, versatility, and pressure potential that can define a championship-level defense. The real fun will be watching how Haines moves those pieces around — who lines up where, who rushes, who drops, and how often opposing quarterbacks realize too late that Indiana has disguised the pressure again.

Miles Anthony Daley is playing Richard Holland and Prince in I'm Every Woman: The Chaka Khan Musical at Troubadour Wembley Park.With a book by Nia T. Hill, I'm Every Woman tells the story of Chaka Khan's extraordinary life and career. The musical premiered at Hackney Empire before transferring to Troubadour Wembley Park, with Chaka Khan attending the show's press night.Miles' theatre credits include George Treadwell in The Drifters Girl (UK & Ireland Tour), The Romantic in The Choir of Man (Arts Theatre and Playhouse Square, Cleveland) and Thriller Live (West End & International). He understudied Raymond Hill in Tina: The Tina Turner Musical in the West End (Aldwych Theatre), and later played the role full-time in the show's Australian production (Melbourne). Elsewhere, Miles appeared on The Voice UK.In this episode, Miles discusses the development of I'm Every Woman and why being part of the production feels like such a significant moment in his career. He also talks about his path into theatre, some of the biggest challenges he has faced and the crazy journey the industry has taken him on so far. I'm Every Woman: The Chaka Khan Musical runs at Troubadour Wembley Park until 27th September.This podcast is hosted by Andrew Tomlins @AndrewTomlins32 Thanks for listening! Email: andrew@westendframe.co.uk Visit westendframe.co.uk for more info about our podcasts. Hosted on Acast. See acast.com/privacy for more information.

Wondering about homeschool freedom and flexibility? And how homeschooling might be a fit for your family? On this episode of The Brainy Moms Podcast, Dr. Amy and Sandy talk with Cheryl Daley, author, speaker, and host of the popular Homeschool How To podcast, to trace the exact chain of events that took her from a six-figure New York State government career to building a homeschool life rooted in freedom, relationships, and real-world learning.Cheryl shares why she treated homeschooling like a research project, interviewing more than 120 families to test assumptions about socialization, academics, and what kids “miss” when they don't follow a standard school track. We talk about deschooling, child-led learning, and the mindset shift from checking boxes to teaching kids how to learn. If you've ever worried about prom, sports, or whether you're doing “enough,” you'll hear practical ways families create options without copying school at home.We also dig into reading and literacy through the lens of the science of reading: why phonics fell out of favor, how balanced literacy failed too many kids, and what structured literacy gets right. Plus, we explore the trade-offs of digital textbooks, handwriting, and online learning tools, including how “smart” programs can still be gamed when a child is focused on time instead of mastery.If you're curious about homeschooling, curriculum overwhelm, or how to start simply with read-alouds, nature walks, and meaningful projects, this conversation will steady your next step. Even if you're a seasoned homeschooler, the conversation should resonate with you in validating ways. Subscribe, share this with a parent who's on the fence, and leave a review so more families can find it.ABOUT US:The Brainy Moms is a parenting podcast hosted by cognitive psychologist Dr. Amy Moore and Sandy Zamalis. Dr. Amy and Sandy have conversations with experts in parenting, child development, education, homeschooling, psychology, mental health, and neuroscience. Listeners leave with tips and advice for helping parents and kids thrive. If you love us, add us to your playlist and follow us on social media! CONNECT WITH US:Website: www.TheBrainyMoms.com Email: BrainyMoms@gmail.com Social Media: @TheBrainyMomsSubscribe to our free monthly newsletterVisit our sponsor's website: www.LearningRx.com

Indiana football's eligibility picture shifted again after the Tenth Circuit stayed the Wisne v. NCAA injunction, and CrimsonCast LIVE breaks down what it means for Stephen Daley, Kellen Wyatt, Sam Alexis, Avery Tatum, and the broader Class of 2022 eligibility fight.Galen Clavio explains why Daley and Wyatt are currently allowed to practice but not play, why Sam Alexis remains in a different legal category through a Tennessee state-court case, and why the NCAA's handling of the “five-for-five” eligibility rule has created so much confusion for athletes, schools, and fans. The episode also looks at possible next steps, including whether Daley and Wyatt could pursue separate legal action and how quickly anything would need to happen before the season.The second half turns to the changing economics of college sports, NIL and revenue-share roster building, the need for eventual collective bargaining, and a major milestone for Indiana football: Memorial Stadium selling out for the full season. Galen reflects on how far IU football attendance has come, which games could be hardest to get into, and why the home-field atmosphere may matter more than ever for Curt Cignetti's Hoosiers.Subscribe to CrimsonCast for coverage of Indiana football, IU athletics, Curt Cignetti, the Hoosiers, Big Ten football, and the 2026 college football season.

Kimberly Daley, chief operation and chief revenue officer for Transcend Cruises, talks with James Shillinglaw of Insider Travel Report about her new Transcend MS Connect, a river ship sailing the rivers of Europe designed for group travel, from corporate meetings to weddings and beyond. Daley gives us a tour of the ship's 60 staterooms (carrying 120 guests), which can be reconfigured into 30 larger suites; the unique two-level lounge and restaurant linked by forum space dominated by a large video screen; a revolutionary spa with multiple treatment rooms and a fitness center, and much more. For more information, visit www.transcendcruises.com. All our Insider Travel Report video interviews are archived and available on our Youtube channel  (youtube.com/insidertravelreport), and as podcasts with the same title on: Spotify, Pandora, Stitcher, PlayerFM, Listen Notes, Podchaser, TuneIn + Alexa, Podbean,  iHeartRadio,  Google, Amazon Music/Audible, Deezer, Podcast Addict, and iTunes Apple Podcasts, which supports Overcast, Pocket Cast, Castro and Castbox. 

There is no one-size-fits-all method to guarantee your publisher's success. We all come out with different titles, balance finding a comfortable niche vs branching out to new audiences, and find the structures and systems that work for us.But there are universal things publishers can do to make their lives easier! This week on the pod, Microcosm' Marketing & Publicity specialist Daley Farr is back to talk to Joe and Elly about Microcosm's strengths, places we can grow, blurbs, pub dates, discoverability, and so much more.************Thank you for catching the People's Guide to Publishing vlogcast!  We post new episodes every Thursday about publishing, authors, and the book industry. You can also listen via your preferred podcast app, or by visiting linktree.com/microcosmGet the book: https://microcosmpublishing.com/catalog/books/3663Get the workbook: https://microcosmpublishing.com/catalog/zines/10031More from Microcosm: http://microcosmpublishing.comMore by Joe Biel: http://joebiel.netMore by Elly Blue: http://takingthelane.comSubscribe to our monthly email newsletter: http://eepurl.com/gIXT6vFind us on social media:Facebook: http://facebook.com/microcosmpublishingBlueSky: https://bsky.app/profile/microcosm.bsky.socialInstagram: http://instagram.com/microcosm_pub************

Dertig jaar geleden opende in Amsterdam Zuidoost een stadion dat de standaard voor Europa zou zetten, ook al wilde het gras er toen nog niet groeien.In deze eerste aflevering van 30 jaar ArenA: De Podcast neemt Arco Gnocchi je mee terug naar de bouw, de opening en de turbulente eerste jaren van het stadion. Aan tafel: Danny Blind, aanvoerder van het Ajax dat als eerste van De Meer naar de ArenA verhuisde, en zijn zoon Daley Blind, die in de ArenA is opgegroeid en er in de zomer van 2026 voor de derde keer terugkeerde.We hebben het over hoe de ArenA voor de bouw werd gezien, de beroemde grasmat die maar niet wilde groeien en hoe Danny zelf nog betrokken raakte bij de oplossing van dat probleem. Ook horen we van Daley hoe het is om op te groeien in en rond het stadion en hoe hij het stadion in drie periodes bij Ajax heeft zien veranderen.Kijk voor alle alle info en de volgende afleveringen op johancruijffarena.nl/podcast

Sam Webb 1-on-1 with DE John Henry Daley pt2See omnystudio.com/listener for privacy information.

Sam Webb 1-on-1 with DE John Henry Daley pt1See omnystudio.com/listener for privacy information.

Jon and Brian are back for a new season of In the Trenches, presented by Meijer! They react to some of the key storylines during training camp on the return of our "Seven from 77" segment. Then, around the 26-minute mark, defensive end John Henry Daley reflects on his fascinating football journey, details his recovery process from an injury last season, and shares some of his goals for the upcoming season.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this inspiring episode of The Krista Escamilla Show, Krista sits down with Devyn Daley, founder of Permian Paws in Need, to discuss the heart behind one of West Texas' most compassionate nonprofits. Devyn shares what inspired her to start the organization, the growing need for animal rescue and support throughout the Permian Basin, and the incredible difference a caring community can make. She also gives listeners a preview of Permian Paws in Need's upcoming fundraiser Bags for Bowls, explaining how the event helps provide lifesaving care, resources, and hope for animals in need. Whether you're an animal lover, looking for ways to give back, or simply enjoy hearing stories of people making a difference, this episode is filled with inspiration and practical ways to get involved. In this episode you'll learn: Why Devyn founded Permian Paws in Need The biggest challenges facing local animal rescue efforts How the nonprofit is changing lives, both for animals and the people who help them Details about the upcoming fundraiser and how you can support the mission Why every volunteer, donor, foster family, and adopter matters

Indiana football is through its first week of fall camp, and CrimsonCast breaks down the biggest questions around the Hoosiers as Curt Cignetti's defending national champions move closer to the 2026 season.Galen Clavio and Scott Caulfield discuss the new reality of following IU football like a national power, the wave of Hoosiers making noise in NFL camps, and the massive defensive-line boost created by Stephen Daley and Kellan Wyatt returning to Indiana. They also dig into what fans should watch for in the first four games, how to evaluate Josh Hoover early in the season, whether Indiana can meet playoff-level expectations, and why the Hoosiers' defense may again be one of the best units in college football.The show closes with reaction to Indiana's Coaches Poll ranking, the possibility of Holden Staes returning, points/touchdowns allowed projections for Bryant Haines' defense, and the national roasting of Purdue's AD comments about IU.Subscribe to the Back Home Network for more CrimsonCast coverage of Indiana football, IU athletics, Curt Cignetti, the Hoosiers, Big Ten football, and the 2026 college football season.

Indiana benefits from court ruling and gets another year of Stephen Daley: August 6th, 2:45pmAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Galen Clavio jumps on CrimsonCast for a shorter solo episode as Indiana football gets ready to open fall camp in Bloomington.The first half focuses on the preseason USA Today Coaches Poll, where defending national champion Indiana lands at No. 6 despite receiving the second-most first-place votes in the country. Galen talks through why the coaches poll should be treated carefully, why the result still says something about IU's national perception, and how the lingering skepticism around the Hoosiers may fit perfectly into Curt Cignetti's approach.Then the episode turns to breaking IU football news: Stephen Daley is returning to Indiana. Galen explains why Daley's comeback matters, how his 2025 breakout changed the Hoosiers' defense, and why adding him back into a front that already includes Tyrique Tucker, Mario Landino, Tobi Osunsanmi, Chiddi Obiazor, Josh Burnham, Joe Hjelle, and Daniel Ndukwe could give Indiana one of the deepest defensive fronts in the country.The final segment shifts away from Bloomington and into soccer, with Galen reacting to Mauricio Pochettino returning with the USMNT for the next World Cup cycle. He discusses why continuity matters, what Pochettino can do with a full four-year runway, and why the U.S. men's national team still needs a clearer identity to move beyond its old ceiling.

How do you make marketing your book work for you? The inclination can be to get it in front of as many people as possible, with as much exposure as you can. But does that actually work? Microcosm's own Marketing & Publicity Specialist, Daley Farr, is back on the pod this week with Joe and Elly to talk about marketing, why knowing your target audience is better than just getting into Target,  and how the media landscape is changing.************Thank you for catching the People's Guide to Publishing vlogcast!  We post new episodes every Thursday about publishing, authors, and the book industry. You can also listen via your preferred podcast app, or by visiting linktree.com/microcosmGet the book: https://microcosmpublishing.com/catalog/books/3663Get the workbook: https://microcosmpublishing.com/catalog/zines/10031More from Microcosm: http://microcosmpublishing.comMore by Joe Biel: http://joebiel.netMore by Elly Blue: http://takingthelane.comSubscribe to our monthly email newsletter: http://eepurl.com/gIXT6vFind us on social media:Facebook: http://facebook.com/microcosmpublishingBlueSky: https://bsky.app/profile/microcosm.bsky.socialInstagram: http://instagram.com/microcosm_pub************

Welcome back!It's hard to believe we're almost to the end of July.I have another great episode for you this week as I welcome Kimberly Daley of Transcend Cruises.What does it take to introduce an entirely new travel concept to the world? Kimberly is a hospitality executive leading the launch of Transcend Cruises, a revolutionary luxury European river cruise brand created exclusively for private charters, corporate events, incentives, and unforgettable celebrations. Kimberly shares the vision behind disrupting the traditional group travel model, what inspired the creation of this purpose-built "river yacht" experience, and how innovation, resilience, and bold leadership are shaping the future of meetings and incentive travel. Whether you're a travel advisor, meeting planner, hospitality professional, or simply fascinated by building a brand from the ground up, this conversation offers an inspiring look at redefining what's possible in luxury group experiences.Tune in and get ready for another incredible guest!XO, CindyContact & Follow Cindy!Follow on Instagram at cindy_novotny, Facebook and LinkedIn for every day inspirational posts.Email at cindynovotny@masterconnection.com

New South Wales league coach Laurie Daley believes players and fans on both sides of the Tasman will jump at the chance to experience State of Origin in New Zealand. Game two of next year's series is at Auckland's Eden Park. Daley told Mike Hosking it's such an iconic venue, so for the players to experience that and for Kiwis to experience Australia's greatest sporting product, it's exceptional. And, he says, there will be plenty of Australian fans making the trip over to watch and support the game as well. LISTEN ABOVE See 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

Brandon Daley's $Positions has the makings of a cult classic. Nerve shredding at times, before hollowing you out with giddy laughter at others. It screens at Revelation Perth International Film Festival on 13 & 14 July 2026. Tickets are available via RevelationFilmFest.org.the Curb is a completely independent and ad free website that lives on the support of listeners and readers just like you. Visit thecurb.com.au/subscribe, where you can support our work from $2 a month. Paid subscribers get access to our monthly competitions, exclusive interviews and articles, and more.Sign up for the latest interviews, reviews, and more via https://www.thecurb.com.au/subscribe/ Hosted on Acast. See acast.com/privacy for more information.

Brandon Daley's $Positions has the makings of a cult classic. Nerve shredding at times, before hollowing you out with giddy laughter at others. It screens at Revelation Perth International Film Festival on 13 & 14 July 2026. Tickets are available via RevelationFilmFest.org.the Curb is a completely independent and ad free website that lives on the support of listeners and readers just like you. Visit thecurb.com.au/subscribe, where you can support our work from $2 a month. Paid subscribers get access to our monthly competitions, exclusive interviews and articles, and more.Sign up for the latest interviews, reviews, and more via https://www.thecurb.com.au/subscribe/ Hosted on Acast. See acast.com/privacy for more information.

Today on the conduct(her) podcast, Kyra and McKenna interview Dr. Carol Daley, Director of Choral Studies and Chair of the Performance Department at Duquesne University.

Looking for your team Clubcast? Find it here: https://linktr.ee/NRLClubCast The NSW Blues Clubcast lands with the dust barely settled on an unforgettable Origin decider at Suncorp. Mitch Moses lets rip with an F-bomb live on Triple M as the Blues fire back at every doubter The emotional Laurie Daley moment that says everything about this series – and who owes him a massive apology The bunker controversy, the grassy knoll theory, and Nathan Cleary's lightning-fast escape from Ben Dobbin Aaron Woods unloads on the critics, Billy Slater's Suncorp hoodoo grows, and why this Blues team has etched its place in Origin history See omnystudio.com/listener for privacy information.

Bryce Daley, coach at Salisbury School, shares how to get recruited for basketball, what families should know about a post grad year for basketball, and how prep school can help players prepare for college.In this episode of the PREP Athletics Podcast, we talk with Bryce about his own path from Salisbury School to Division I basketball at UMass Lowell, what surprised him about the D1 level, and how he now helps players develop at Salisbury.We also cover campus visits, all-boys school advantages, player development, playing time expectations, college placement, NEPSAC exposure, reclassification, post-grad eligibility questions, and what it takes to become a scholarship-level guard.⏰ Timestamps:00:00 - Episode Intro01:57 - Bryce Daley Joins the Podcast02:09 - Bryce's Basketball Background and Prep School Path08:10 - From Salisbury School to UMass Lowell10:41 - What Playing D1 Basketball Really Takes13:18 - Why Salisbury School Works16:45 - All-Boys School and Player Development21:43 - Sports Requirements, Strength Training, and Post-Grad Academics27:38 - College Placement and Playing Time Expectations32:18 - NEPSAC Exposure, Reclassing, and Post-Grad Decisions41:02 - NEPSAC Class A and What It Takes to Be a D1 Guard45:33 - The Future of Prep School Basketball and Quick Hitters52:24 - How Prep School Changed Bryce's Life53:52 - Bryce's Contact Info and Final PREP Athletics CTA

Listen to the full interview with Mitchell Moses.See omnystudio.com/listener for privacy information.

The Suncorp Humble Pie Show: The panel unloads on Queensland's inept, mediocre decider performance. The New King of NSW: Nathan Cleary's untouchable 15-minute blitz and why the Immortal debate is officially over. Calling Out Gus Gould: Why Gould is dead wrong about "owning Origin". Mitchell Moses Silences the Panel: Readie pulls out the receipts on the hosts wanting Moses dropped. The Forward Monster Class: How Payne Haas, Mitch Barnett, and Addin Fonua-Blake completely destroyed the Queensland pack. Daley vs. Slater: Laurie Daley’s ultimate tactical vindication. The Bunker Robbery Debate: Breaking down the "very dodgy" Bradman Best try and the hidden camera angle home viewers didn't see.See omnystudio.com/listener for privacy information.

This week on Turf Today, we sit down with Nick Daley, Golf Course Superintendent at Capilano Golf & Country Club. Originally from Sydney, Australia, Nick's journey through the turf industry has taken him from his first days at Nicklaus North Golf Course to becoming one of Canada's rising leaders in golf course management. A graduate of Penn State World Campus, Nick has worked his way through nearly every level of the profession, gaining valuable experience as a grounds crew member, irrigation technician, Assistant Superintendent, and now Superintendent at the private West Vancouver club. In this episode, we discuss Nick's transition into the Superintendent role and the challenges that come with moving from a hands-on agronomic focus to overseeing the entire golf course operation. We explore leadership, communication, delegation, staff development, and what it takes to manage both people and turf at a high level.  Nick shares insights from hosting and volunteering at championship events and reflects on winning the 2023 CGSA Assistant Superintendent of the Year award. We also talk about the moments that continue to fuel his passion for the industry, from early mornings on the golf course to major projects, aeration weeks, and helping team members advance in their careers. Whether you're an aspiring Superintendent, a seasoned turf professional, or simply interested in the people behind great golf courses, this conversation offers an honest look at career progression, leadership, and the evolving role of today's golf course superintendent.

Wade Graham, James Graham and Charlie White are in off the back of the final Origin team lists for 2026, and Laurie Daley has made some massive changes. To'o has been replaced by Bostock in a tactical move, while Best and Critta return to the centres. Haumole and Liam Martin are also back to bolster the forward stocks. Queensland is relatively unchanged aside from the returns of Carrigan and Nanai, but Billy Slater's press conference bombshell on his coaching future has left the state in shock. We then head to clubland to look at the season-ending injuries suffered by May and Brooks, Joey Walsh getting his chance to shine for Manly, and another Sunday bunker howler that cost the Dragons. Plus, we break down the run home for 2026 and the unpredictable race for the top eight! Donate to Jai Arrow here: https://www.gofundme.com/f/stand-with-me-jai-arrow Check out Triple M NRL's Instagram, Facebook, TikTok and YouTube!See omnystudio.com/listener for privacy information.

Word of player unrest at the Broncos grow louder. The Australian's Andrew Webster joins Mike Pearsall to discuss whether Michael Maguire can push through the noise. Brian To'o may go down as NSW's greatest ever winger, but poor form has led to Laurie giving him the punt for Origin 3. While speculation about Daley's future won't go away, there is no guarantee that Billy Slater will back up for Queensland again. Plus, the NRL bunker's forgettable weekend. See omnystudio.com/listener for privacy information.

Welcome back to the Hangar Z Podcast, brought to you by Vertical HeliCASTS, in partnership with Vertical Valor Plus.  Our guest is retired Lieutenant Glenn Daley of the New York City Police Department Aviation Unit. Glenn's career in airborne law enforcement spans decades of service, leadership, instruction, and experience, that has taken him around the world. This conversation is powerful, emotional, educational, and, without question, one of the most important discussions we have had on this podcast.This series begins on Sept. 11, 2001, at 8:46 a.m., the moment American Airlines Flight 11 struck the North Tower of the World Trade Center. Glenn takes us back to that horrific morning and provides a firsthand account of the response by NYPD Aviation assets during one of the darkest days in American history. He shares not only the operational response, but also his personal experiences and how that day forever changed him both professionally and personally.Throughout this series, we walk through Glenn's remarkable NYPD career, including his time assigned to the Special Enforcement Unit, and discuss the transition into flying and instructing after retirement from the department. Glenn's passion for aviation safety and training is evident throughout every episode.One of the most impactful parts of this conversation is our deep dive into IIMC (inadvertent flight into instrument meteorological conditions). Glenn shares his extensive knowledge and experience on what pilots and crews must do to prevent and survive these situations. We discuss go and no-go decision making, simulator training, proficiency versus currency, instrument ratings, crew coordination, and the mindset required to avoid tragedy. These lessons are real-world, practical, and potentially lifesaving.Episodes like this truly have the power to save lives someday, and we are incredibly fortunate that Glenn was willing to share his experiences, knowledge, and perspective with all our listeners.This is a conversation you will not forget.Thank you to our sponsors Airbus, Dallas Avionics and Spectrolab.

Welcome back to the Hangar Z Podcast, brought to you by Vertical HeliCASTS, in partnership with Vertical Valor Plus.  Our guest is retired Lieutenant Glenn Daley of the New York City Police Department Aviation Unit. Glenn's career in airborne law enforcement spans decades of service, leadership, instruction, and experience, that has taken him around the world. This conversation is powerful, emotional, educational, and, without question, one of the most important discussions we have had on this podcast.This series begins on Sept. 11, 2001, at 8:46 a.m., the moment American Airlines Flight 11 struck the North Tower of the World Trade Center. Glenn takes us back to that horrific morning and provides a firsthand account of the response by NYPD Aviation assets during one of the darkest days in American history. He shares not only the operational response, but also his personal experiences and how that day forever changed him both professionally and personally.Throughout this series, we walk through Glenn's remarkable NYPD career, including his time assigned to the Special Enforcement Unit, and discuss the transition into flying and instructing after retirement from the department. Glenn's passion for aviation safety and training is evident throughout every episode.One of the most impactful parts of this conversation is our deep dive into IIMC (inadvertent flight into instrument meteorological conditions). Glenn shares his extensive knowledge and experience on what pilots and crews must do to prevent and survive these situations. We discuss go and no-go decision making, simulator training, proficiency versus currency, instrument ratings, crew coordination, and the mindset required to avoid tragedy. These lessons are real-world, practical, and potentially lifesaving.Episodes like this truly have the power to save lives someday, and we are incredibly fortunate that Glenn was willing to share his experiences, knowledge, and perspective with all our listeners.This is a conversation you will not forget.Thank you to our sponsors Precision Aviation Group, Robinson Helicopter and SHOTOVER.

Welcome back to the Hangar Z Podcast, brought to you by Vertical HeliCASTS, in partnership with Vertical Valor Plus.  Our guest is retired Lieutenant Glenn Daley of the New York City Police Department Aviation Unit. Glenn's career in airborne law enforcement spans decades of service, leadership, instruction, and experience, that has taken him around the world. This conversation is powerful, emotional, educational, and, without question, one of the most important discussions we have had on this podcast.This series begins on Sept. 11, 2001, at 8:46 a.m., the moment American Airlines Flight 11 struck the North Tower of the World Trade Center. Glenn takes us back to that horrific morning and provides a firsthand account of the response by NYPD Aviation assets during one of the darkest days in American history. He shares not only the operational response, but also his personal experiences and how that day forever changed him both professionally and personally.Throughout this series, we walk through Glenn's remarkable NYPD career, including his time assigned to the Special Enforcement Unit, and discuss the transition into flying and instructing after retirement from the department. Glenn's passion for aviation safety and training is evident throughout every episode.One of the most impactful parts of this conversation is our deep dive into IIMC (inadvertent flight into instrument meteorological conditions). Glenn shares his extensive knowledge and experience on what pilots and crews must do to prevent and survive these situations. We discuss go and no-go decision making, simulator training, proficiency versus currency, instrument ratings, crew coordination, and the mindset required to avoid tragedy. These lessons are real-world, practical, and potentially lifesaving.Episodes like this truly have the power to save lives someday, and we are incredibly fortunate that Glenn was willing to share his experiences, knowledge, and perspective with all our listeners.This is a conversation you will not forget.Thank you to our sponsors CNC Technologies, Metro Aviation and Trakka Systems.

This week, we're chatting to Lucy Ashe. Lucy trained at the Royal Ballet school, and now works as a teacher in Brooklyn, whilst writing brilliant books. Her debut, 'Clara and Olivia', was shortlisted for the CWA Historical Dagger Award. Her follow up, 'The Sleeping Beauties', was also set in the world of ballet. The new novel is 'The Model Patient'. Set in 1960s London, it explores obsession and betrayal. In the quiet hush of her therapists office, Evelyn Westbrook finds herself revealing secrets she'd prefer to stay hidden. When her sessions with the enigmatic Dr. Daley starts to give more questions than answers, she finds her interest in him turn into an obsession. It was inspired by Lucy's own traumatic relationship with a therapist, and it helped her find some control in that strange situation.We talk about Lucy's writing life, after recently having her first child, and how that's changed how much time she thought she'd have to write. Also, hear how a book deal changes how you write... does it add confidence or pressure? And, how it's a slight diversion from her normal historical fiction book - she's found the psychological thriller in this one.Get a copy of the book at uk.bookshop.org/shop/writersroutineThis week's episode is sponsored by IngramSpark. Get 15% off your first 15 books when you use the code ROUTINE15 at ingramspark.comAlso, this week we're supported by the Quick Book Reviews podcast with Philippa Hall. Take a listen wherever you've got this show.Support us at patreon.com/writersroutineko-fi.com/writersroutine@writerspodwritersroutine.com Hosted on Acast. See acast.com/privacy for more information.

Live from Zanies in Rosemont, Doug welcomes Brandon Daley, Kevin Kellam and Alex Stopak to the show.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

I start with Eric and Daley at about 35 mins after news and clips Subscribe and Watch Interviews LIVE : On YOUTUBE.com/StandUpWithPete ON SubstackStandUpWithPete Stand Up is a daily podcast. I book,host,edit, post and promote new episodes with brilliant guests every day. This show is Ad free and fully supported by listeners like you! Please subscribe now for as little as 5$ and gain access to a community of over 750 awesome, curious, kind, funny, brilliant, generous soul Follow Eric on Blue Sky Read Eric on Dorf on Law Listen to Supreme Myths Podcast Eric Segall teaches federal courts and constitutional law I and II. He is the author of the book Supreme Myths: Why the Supreme Court is not a Court and its Justices are not Judges. He has served on the Executive Committee of the AALS section on federal courts, and has given numerous speeches both inside and outside the academy on constitutional law questions and the Supreme Court. He appears regularly on the national XM Radio show StandUp with Pete Dominick talking about the Supreme Court and constitutional law. David Daley is a senior fellow for FairVote and the author of Ratf**ked: The True Story Behind the Secret Plan to Steal America's Democracy, which helped spark the recent drive to reform gerrymandering. Dave's second book, Unrigged: How Americans Are Battling Back to Save Democracy, chronicles the victories and defeats in state efforts to reform elections and uphold voting rights. A frequent lecturer and media source about gerrymandering, he is the former editor-in-chief of Salon.com, and the former CEO and publisher of the Connecticut News Project. He is a digital media fellow at the Wilson Center for the Humanities and the Grady School of Journalism at the University of Georgia. His work has appeared in the New Yorker, The Washington Post, The Guardian, New York magazine, the Atlantic, the Boston Globe, Rolling Stone, Details, and he's been on CNN and NPR. When writing for the Hartford Courant, he helped identify Mark Felt as the "Deep Throat" source for Bob Woodward and Carl Bernstein.    On YOUTUBE.com/StandUpWithPete ON SubstackStandUpWithPete   Listen rate and review on Apple Podcasts Listen rate and review on Spotify Pete On Instagram Pete on Blue Sky Pete on Threads Pete on Tik Tok Pete on Twitter Pete Personal FB page Stand Up with Pete FB page     Gift a Subscription https://www.patreon.com/PeteDominick/gift Send Pete $ Directly on Venmo All things Jon Carroll  Buy Ava's Art    Subscribe to Piano Tuner Paul Paul Wesley on Substack Listen to Barry and Abigail Hummel Podcast Listen to Matty C Podcast and Substack Follow and Support Pete Coe Hire DJ Monzyk to build your website or help you with Marketing