Podcasts about Manus

It's not clear which states are involved, but they're asking about everything from OpenAI's ad policies to its handling of health data. Also, Meta started dismantling its $2 billion Manus acquisition after Beijing ordered the deal reversed. And, Amazon CEO Andy Jassy may have been the source of security concerns that led Anthropic to cut off worldwide access to two models on Friday. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Flera personer visste att 21-årige James Stoneham ville mörda sin ex-flickvän, 20-åriga Adriana Donato. Ingen sa något till Adriana. Och därför gick hon med på att sätta sig i James bil den 23 augusti 2012. Kvällen som skulle bli hennes sista i livet.Manus av Sofie Karlsson. Klippning av Josefine Molén.Reklam. Om du gillar Mördarpodden kan du vara med och sponsra den på Patreon. https://www.patreon.com/user?u=10466265.Som tack får du tillgång till förhandlyssning och alla avsnitt från Richard Chase del 1 och framåt utan reklam. Vill du höra ett specifikt fall i podden? Önska dina fall i det här formuläret: https://docs.google.com/forms/d/e/1FAIpQLSfDlQxf9SgZyeGS-qFPaB4BP-L59lQhs7BbZACfwk7xSs-AFw/viewform?fbclid=IwAR0astYAY_SJLcst89FwKaPIeHHV9zlfAxEz6Cmrh37bbMwvMHGc8z5cwg4Det här är en podcast av Dan Hörning och Josefine Molén.Instagram: @mordarpoddenE-post: zimwaypodcast@gmail.comFölj Josefine Molén här:https://www.instagram.com/j.molenFölj Dan Hörning här:X: @danhorningInstagram: https://www.instagram.com/dan_horning/?hl=enYoutube: https://www.youtube.com/channel/UCV2Qb7SmL9mejE5RCv1chwgErik SegerstedtSpotify:https://open.spotify.com/artist/63q3l3pKBpvqEjUM5Vf1TG?si=fYtdOwIvTn6noQJW6ffPwwInstagram: https://instagram.com/e Hosted on Acast. See acast.com/privacy for more information.

A viral Wall Street chart has kicked off a new round of AI bubble panic, but NLW argues the market is reading it wrong. The real story isn't collapsing demand — it's the shift from the token subsidy era to the token scarcity era, where companies are learning to route AI usage more efficiently. In the headlines: SpaceX's IPO, Bezos' Prometheus raise, Meta's Manus split, chip supply chain crunches, and Goldman's trillion-dollar AI infrastructure forecast.Check out the new ⁠https://aidailybrief.ai/⁠Brought to you by:KPMG – Research from KPMG and the University of Texas at Austin shows the highest-impact AI users treat AI like a reasoning partner — and those skills can be taught at scale. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠kpmg.com/us/Sophisticated⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Bolt - Claim a free month of Bolt Pro - ⁠⁠⁠⁠⁠⁠⁠https://bolt.new/partner/aidb/⁠⁠⁠⁠⁠⁠⁠Outsystems - Stop wondering how AI will change your business and start building the agents that will lead it - http://outsystems.com/Scrunch - The AI customer experience platform - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://scrunch.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Zenflow Work - Agents for knowledge work - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://zenflow.free/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Our Newsletter is BACK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai

Ce jeudi 11 juin, François Sorel a reçu Jérôme Marin, fondateur de cafetech.fr, Claudia Cohen, journaliste chez Bloomberg, et Frédéric Simottel, journaliste BFM Business. Ils sont revenus sur la possible baisse des prix d'OpenAI face à la concurrence, la finalisation de la séparation opérationnelle entre Meta et Manus, ainsi que la restructuration chez Ubisoft, dans l'émission Tech & Co, la quotidienne, sur BFM Business. Retrouvez l'émission du lundi au jeudi et réécoutez la en podcast.

Jocke krisar och tvingas flytta hem till sin mammas hyreshus. Som aldrig är tyst. En kväll har någon klottat i trapphuset och budskapet är riktat mot Jocke personligen. Vem? Varför? Fuck Jocke Fransson är en psykologisk thriller i fem delar, som blandar pulshöjande spänning med humor och lätthet. Manus av Paolo Iskra, i regi av Henrik Georgsson. Dramaturg: Magnus Lindman.Lyssna på Fuck Jocke Fransson, och följ P3 Serie i Sveriges Radios app.

In Pacific Waves today: Livestock deaths impact Sinlaku recovery on Saipan; Manus communities affected by pumice from Titan Ridge volcano; PNG Pumice rafts could linger for months - scientist. Go to this episode on rnz.co.nz for more details

Jocke krisar och tvingas flytta hem till sin mammas hyreshus. Som aldrig är tyst. En kväll har någon klottat i trapphuset och budskapet är riktat mot Jocke personligen. Vem? Varför? Fuck Jocke Fransson är en psykologisk thriller i fem delar, som blandar pulshöjande spänning med humor och lätthet. Manus av Paolo Iskra, i regi av Henrik Georgsson. Dramaturg: Magnus Lindman.Lyssna på Fuck Jocke Fransson, och följ P3 Serie i Sveriges Radios app.

Frågan om vem som är mannen på bron kvarstår. Polisen undersöker flera spår men fallet blir kallare och kallare. I oktober 2022 hittas dock en gammal rapport med information som aldrig följts upp. Den rapporten leder utredningen till Richard Allen. Manus av Sofie Karlsson. Klippning av Josefine Molén.Reklam. Om du gillar Mördarpodden kan du vara med och sponsra den på Patreon. https://www.patreon.com/user?u=10466265 Som tack får du tillgång till förhandlyssning och alla avsnitt från Richard Chase del 1 och framåt utan reklam. För dig som sponsrar Mördarpodden via Patreon finns samtliga delar i vår serie om Delphi Murders tillgängliga redan nu helt reklamfritt!Vill du som inte redan sponsrar oss via Patreon ta del av serien om Delphi Murders helt reklamfritt så var med och sponsra podden på Patreon med ett valfritt belopp: https://www.patreon.com/user?u=10466265Vill du höra ett specifikt fall i podden? Önska dina fall i det här formuläret: https://docs.google.com/forms/d/e/1FAIpQLSfDlQxf9SgZyeGS-qFPaB4BP-L59lQhs7BbZACfwk7xSs-AFw/viewform?fbclid=IwAR0astYAY_SJLcst89FwKaPIeHHV9zlfAxEz6Cmrh37bbMwvMHGc8z5cwg4Det här är en podcast av Dan Hörning och Josefine Molén.Instagram: @mordarpoddenE-post: zimwaypodcast@gmail.comFölj Josefine Molén här:https://www.instagram.com/j.molenFölj Dan Hörning här:X: @danhorningInstagram: https://www.instagram.com/dan_horning/?hl=enYoutube: https://www.youtube.com/channel/UCV2Qb7SmL9mejE5RCv1chwgErik SegerstedtSpotify:https://open.spotify.com/artist/63q3l3pKBpvqEjUM5Vf1TG?si=fYtdOwIvTn6noQJW6ffPwwInstagram: https://instagram.com/e Hosted on Acast. See acast.com/privacy for more information.

Microsoft dominated Build with Scout, an always-on Teams agent, the Surface RTX Spark Dev Box, its first reasoning model MAI-Thinking-1 aimed squarely at Anthropic, and Project Solara for agent-first devices. Trump signed a scaled-back AI executive order on cybersecurity. Microsoft announces Scout, an always-on enterprise AI agent built on OpenClaw that appears as a Microsoft Teams contact to automate tasks such as scheduling (Wired) Microsoft unveils a Surface RTX Spark Dev Box, featuring Nvidia's Arm-based RTX Spark, 128GB of unified memory, and a 100W thermal envelope, for local AI tasks (The Verge) Microsoft debuts MAI-Thinking-1, its first advanced reasoning AI model, trained "from the ground up on clean data, without distillation from third-party models" (The Verge) Microsoft unveils Project Solara, an Android-based platform for agent-first devices, with concept hardware and pilots planned at Best Buy, Target, and others (GeekWire) Microsoft unveils Microsoft Execution Containers, a Windows-level sandbox for AI agents, and says partners OpenAI, Nvidia, Manus, and Nous Research are using it (VentureBeat) President Trump signs a scaled-back AI EO that seeks to address AI's cybersecurity threats; sources say it imposes less scrutiny on AI than the scrapped version (Politico) Learn more about your ad choices. Visit megaphone.fm/adchoices

China is running the EV playbook on humanoid robots — and it's working https://restofworld.org/2026/china-humanoid-robots-unitree-agibot-tesla-optimus/Flexion https://flexion .ai/ ETH robotics club https://www.ethrobotics.ch/ The co-founders of Manus are exploring options to fulfill Beijing's demand to unwind a controversial takeover by Meta, including raising about $1 billion from external investors to buy back the Chinese-founded AI operation https://www.bloomberg.com/news/articles/2026-05-21/manus-weighs-raising-1-billion-to-unwind-meta-takeover Agentic AI in Retail: How Autonomous Shopping Is Redefining the Customer Journeyhttps://www.bain.com/insights/agentic-ai-in-retail-how-autonomous-shopping-redefining-customer-journey/The fundamental issue with independent agentic commerce https://x.com/eric_seufert/status/2034727848498667642 Softbank announced a plan to spend ‘up to' €75bn ($87bn) to build 5GW of AI data centres in France, leveraging ‘data sovereignty' on one hand and France's nuclear-generated electricity on the other. https://group.softbank/en/news/press/20260531_0 IA jobpocalypse ou WFH ? https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6787638 Ferrari Luce https://www.ferrari.com/en-EN/auto/ferrari-luce Acquired podcast https://www.acquired.fm/episodes/ferrari INSPIRATION #EVENT :: Niptech Explore - Olivier Clerc 30.06 à Lausanne https://boutique.cah.ch/products/niptech-presente-au-dela-des-4-accords-tolteques-avec-olivier-clerc #LEARNING :: The "Gell-Mann amnesia effect" https://x.com/syde/status/2060680824324821445?s=20 #BOOK :: The Unheard Cry for Meaning: Psychotherapy and Humanism by Viktor Emil Frankl https://www.amazon.com/Unheard-Cry-Meaning-Psychotherapy-Humanism/dp/0671247360 #PODCAST :: Yuval Noah Harari https://www.nytimes.com/2026/05/26/opinion/ezra-klein-podcast-yuval-noah-harari.html #QUOTE ::“The truth is that as the struggle for survival has subsided, the question has emerged: survival for what? Ever more people today have the means to live but no meaning to live for.” Viktor Frankl, The Unheard Cry for Meaning Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Den 13 februari 2017 skakas den lilla staden Delphi i Indiana om av ett dubbelmord. Offren är 14-åriga Libby German och 13-åriga Abby Williams. Två dagar efter mordet går polisen ut med att de har hittat en film i Libbys telefon. En film som fångar mördaren.Manus av Sofie Karlsson. Klippning av Josefine Molén.Reklam. Om du gillar Mördarpodden kan du vara med och sponsra den på Patreon. https://www.patreon.com/user?u=10466265 Som tack får du tillgång till förhandlyssning och alla avsnitt från Richard Chase del 1 och framåt utan reklam. För dig som sponsrar Mördarpodden via Patreon finns samtliga delar i vår serie om Delphi Murders tillgängliga redan nu helt reklamfritt!Vill du som inte redan sponsrar oss via Patreon ta del av serien om Delphi Murders helt reklamfritt så var med och sponsra podden på Patreon med ett valfritt belopp: https://www.patreon.com/user?u=10466265Delphimorden Delphi-morden Delphi mordenVill du höra ett specifikt fall i podden? Önska dina fall i det här formuläret: https://docs.google.com/forms/d/e/1FAIpQLSfDlQxf9SgZyeGS-qFPaB4BP-L59lQhs7BbZACfwk7xSs-AFw/viewform?fbclid=IwAR0astYAY_SJLcst89FwKaPIeHHV9zlfAxEz6Cmrh37bbMwvMHGc8z5cwg4Det här är en podcast av Dan Hörning och Josefine Molén.Instagram: @mordarpoddenE-post: zimwaypodcast@gmail.comFölj Josefine Molén här:https://www.instagram.com/j.molenFölj Dan Hörning här:X: @danhorningInstagram: https://www.instagram.com/dan_horning/?hl=enYoutube: https://www.youtube.com/channel/UCV2Qb7SmL9mejE5RCv1chwgErik SegerstedtSpotify:https://open.spotify.com/artist/63q3l3pKBpvqEjUM5Vf1TG?si=fYtdOwIvTn6noQJW6ffPwwInstagram: https://instagram.com/e Hosted on Acast. See acast.com/privacy for more information.

In this week's Behind The Scenes episode of The FasterFreedom Show, Sam breaks down how he's using AI across his educational business and social media content creation—and where he believes these tools are helping the most.He walks through the different platforms and programs he's experimented with, including tools like Claude, ChatGPT, Manus, and others, sharing which ones he uses the most today, which ones he's pulled back from, and why. You'll hear how AI has improved efficiency, brainstorming, content workflows, and idea generation, while also learning where overreliance on AI can start to hurt authenticity and creativity.From practical business applications to the evolving role of AI in content creation, this episode gives a real, behind-the-scenes look at how these tools can be leveraged effectively without losing the human side that actually builds trust and connection.Join my PREMIUM real estate community on Skool: ⁠⁠⁠https://www.skool.com/fasterfreedomrelaunchpro⁠⁠⁠FasterFreedom Capital Connection: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://fasterfreedomcapital.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Free Rental Investment Training: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://freerentalwebinar.com⁠⁠⁠⁠

In this episode, Dylan Silver and David Berneman discuss the intricacies of property management, the impact of AI tools like Claude and Manus on real estate operations, and strategies for maintaining control and quality in property management. They explore how technology is transforming the industry and share practical insights for investors and managers.   Professional Real Estate Investors - How we can help you: Investor Fuel Mastermind:  Learn more about the Investor Fuel Mastermind, including 100% deal financing, massive discounts from vendors and sponsors you're already using, our world class community of over 150 members, and SO much more here: http://www.investorfuel.com/apply   Investor Machine Marketing Partnership:  Are you looking for consistent, high quality lead generation? Investor Machine is America's #1 lead generation service professional investors. Investor Machine provides true 'white glove' support to help you build the perfect marketing plan, then we'll execute it for you…talking and working together on an ongoing basis to help you hit YOUR goals! Learn more here: http://www.investormachine.com   Coaching with Mike Hambright:  Interested in 1 on 1 coaching with Mike Hambright? Mike coaches entrepreneurs looking to level up, build coaching or service based businesses (Mike runs multiple 7 and 8 figure a year businesses), building a coaching program and more. Learn more here: https://investorfuel.com/coachingwithmike   Attend a Vacation/Mastermind Retreat with Mike Hambright: Interested in joining a "mini-mastermind" with Mike and his private clients on an upcoming "Retreat", either at locations like Cabo San Lucas, Napa, Park City ski trip, Yellowstone, or even at Mike's East Texas "Big H Ranch"? Learn more here: http://www.investorfuel.com/retreat   Property Insurance: Join the largest and most investor friendly property insurance provider in 2 minutes. Free to join, and insure all your flips and rentals within minutes! There is NO easier insurance provider on the planet (turn insurance on or off in 1 minute without talking to anyone!), and there's no 15-30% agent mark up through this platform!  Register here: https://myinvestorinsurance.com/   New Real Estate Investors - How we can work together: Investor Fuel Club (Coaching and Deal Partner Community): Looking to kickstart your real estate investing career? Join our one of a kind Coaching Community, Investor Fuel Club, where you'll get trained by some of the best real estate investors in America, and partner with them on deals! You don't need $ for deals…we'll partner with you and hold your hand along the way! Learn More here: http://www.investorfuel.com/club   —--------------------

How to turn one 20 minute recording into 100 pieces of content that actually cut through.Content is king. Distribution is the kingdom. But volume only works when it stays engaging and native to each channel. In this episode of The Unlock, Oliver Bruce walks founders and business owners through the exact versioning workflow that takes you from producing no content to producing volume content that performs, without spamming your audience or burning your time.Record once. Version everything. One 20 minute sitting becomes one long form video, 50 plus shorts, one podcast, one piece of audio, and one GEO and SEO optimised blog. You sweat a single asset instead of recording a hundred from scratch.Oliver breaks down the full stack and the channel logic most founders get wrong. Opus Clips does the heavy lifting, turning long form into hook-led, subtitled shorts, then scheduling and writing channel-native copy. Manus builds out the GEO strategy, transcripts, and blogs. TikTok is your testing bed for volume. Instagram takes only the proven winners because it punishes spam. YouTube is the real engine because it carries long form, short form, and audio first, all feeding a search platform surfaced on Google, ChatGPT, and Claude.In this episode you will learn: How to produce volume content without spamming your audience The one to a hundred versioning workflow for founders  How to use Opus Clips to version, schedule, and write native copy  How to use Manus to build GEO strategy, transcripts, and blogs  Why TikTok is your testing bed and Instagram takes only the winners  Why YouTube is the most valuable channel for long form, short form, and audio How to pull a GEO and SEO optimised transcript and blog from every recording Key takeaway: One 20 minute sitting, recorded with intent and versioned well, gives you a hundred assets that work harder than a hundred recordings ever could.Sponsored by Incard — Sponsored by Incard. Sign up now. All your finances. One platform.More Value:Follow on YouTube for deep-dives & video episodes: www.youtube.com/@TheUnlockOliverBruceNeed a 1-2-1 with Oliver or want to be on the show, visit: www.oliverbruce.co.ukRead more information on key points in Oliver's newsletter: The Brucey Bonus newsletterFollow The Unlock & Oliver's socials:LinkedIn | TikTok | YouTube | Instagram | Apple Podcast | Spotify podcast

No Braincast 634, Carlos Merigo, Cris Dias, Hiago Vinícius e Luiz Yassuda discutem o vibe coding, a nova febre da IA que promete permitir que qualquer pessoa crie aplicativos, dashboards, automações e protótipos apenas descrevendo o que quer. A conversa passa por Claude, Codex, Lovable, Replit, Bolt, Cursor, Manus, low-code, SaaSpocalipse, token maxing e a fantasia do “unicórnio de uma pessoa só”. Afinal, estamos diante de uma revolução criativa, em que mais gente pode transformar ideias em produtos, ou de uma fábrica de gambiarras em escala industrial? Também entram no papo os riscos de segurança, vazamento de dados, dependência das big techs, código ruim, Shadow IT, empresas tentando substituir times inteiros por IA e a importância de repertório, critério e bom gosto num mundo onde executar ficou mais fácil, mas saber o que pedir continua sendo o grande desafio. No Qual é a Boa, ainda tem Cinemático sobre Obsessão, jogos como Crimson Desert e The Last Caretaker, o Anti-Authoritarian Toolkit, IA em Curso, The Traitors e Momento Faustão. -- CONHEÇA OS CURSOS DA ESCOLA DE IA DA PUCPR https://posdigital.pucpr.br/areas/escola-de-ia?utm_source=podcast&utm_medium=braincast&utm_campaign=pucpr_externo_leads_ativacao-1_escola-ia&utm_content=audio_atributo_26-05-17 -- 04:17 PAUTA 05:37 O que é vibe coding 08:31 Origem e ferramentas 09:52 É programação mesmo 14:50 SaaSpocalipse e limites 19:59 Dilema do monstro 25:30 Token maxing e tralha 27:50 Low code e democratização 30:37 Agentes e checagem 34:10 Programadores e IA 34:52 Autocomplete e Vibe Code 38:52 Hype e corrida da IA 39:56 Segurança e dados 41:45 Automação pessoal útil 43:55 SaaS pequeno vs grande 46:07 Sites leves sem WordPress 49:57 Canva e custos ocultos 57:09 Dependência e mediação 59:45 Legado corporativo e suporte 01:02:57 Habilidades e formação 01:11:40 Bom gosto e repertório 01:12:46 Curiosidade como profissão 01:15:03 Educação e base teórica 01:18:00 A febre dos prompts 01:18:50 QUAL É A BOA 01:28:56 Toolkit anti autoritário 01:34:38 Cupom IA em Curso 01:35:24 Reality The Traitors 01:40:06 Momento Faustão -- ✳️ TORNE-SE MEMBRO DO B9 E GANHE BENEFÍCIOS: Braincast secreto; grupo de assinantes no Telegram; e episódios sem anúncios!

I det här avsnittet får du två helt olika versioner av vad som hände dygnen och timmarna innan massmordet.Manus av Jennie Sterner. Klippning av Johannes Rae från poddklipparen.seReklam. Om du gillar Mördarpodden kan du vara med och sponsra den på Patreon. https://www.patreon.com/user?u=10466265 Som tack får du tillgång till förhandlyssning och alla avsnitt från Richard Chase del 1 och framåt utan reklam. För dig som sponsrar Mördarpodden via Patreon finns samtliga 16 delar i vår serie om Charles Manson tillgängliga redan nu helt reklamfritt!Vill du som inte redan sponsrar oss via Patreon ta del av serien om Amy Bishop helt reklamfritt så var med och sponsra podden på Patreon med ett valfritt belopp: https://www.patreon.com/user?u=10466265Vill du höra ett specifikt fall i podden? Önska dina fall i det här formuläret: https://docs.google.com/forms/d/e/1FAIpQLSfDlQxf9SgZyeGS-qFPaB4BP-L59lQhs7BbZACfwk7xSs-AFw/viewform?fbclid=IwAR0astYAY_SJLcst89FwKaPIeHHV9zlfAxEz6Cmrh37bbMwvMHGc8z5cwg4Det här är en podcast av Dan Hörning och Josefine Molén.Instagram: @mordarpoddenE-post: zimwaypodcast@gmail.comFölj Josefine Molén här:https://www.instagram.com/j.molenFölj Dan Hörning här:X: @danhorningInstagram: https://www.instagram.com/dan_horning/?hl=enYoutube: https://www.youtube.com/channel/UCV2Qb7SmL9mejE5RCv1chwgErik SegerstedtSpotify:https://open.spotify.com/artist/63q3l3pKBpvqEjUM5Vf1TG?si=fYtdOwIvTn6noQJW6ffPwwInstagram: https://instagram.com/e Hosted on Acast. See acast.com/privacy for more information.

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!On the product side, everyone is getting Computer - Perplexity, Manus, Cursor, and so on. Meanwhile on the research side, agentic evals like TerminalBench and GDPVal are also assuming computer (Harbor). On both ends, the consolidating LLM OS stack has become a standard toolkit, and Daytona is one of a small set of AI Infra companies that are booming because of it.“The end of localhost” has been Ivan Burazin's obsession for more than a decade.Something that is all too familiar…Long before agents became the default way people talked about software development, Ivan was already chasing the idea that development should not depend on a fragile local machine. CodeAnywhere, one of the first browser-based IDEs, was an early attempt at that future: move the development environment into the cloud, make setup reproducible, and free developers from the endless “works on my machine” tax.The thesis was directionally right, but the market wasn't ready yet.However, agents changed that. They do not care about a laptop, desk setup, or favorite editor. They need a computer they can access through an API: something stateful enough to keep working, fast enough to spin up instantly, flexible enough to resize, isolated enough to be safe, and composable enough to run the messy real-world workflows that real software engineering actually requires.Daytona isn't just selling “sandboxes” in the narrow code-execution sense. It is the latest version of Ivan's original localhost thesis.In this episode, Daytona's CEO joins swyx to explain why AI agents need more than code execution boxes: they need composable computers, stateful sandboxes, instant startup, dynamic resources, and infrastructure that can survive workloads going from zero to 100,000 CPUs.We go deep on the new agent compute market: Daytona's hard pivot from human dev environments to AI sandboxes, the New Year's Eve MVP that customers begged for, why Daytona runs on bare metal with its own scheduler, how one customer runs almost 850,000 sandboxes a day, and why RL/eval workloads went from 0% to roughly 50% of usage in just months. Ivan also explains why agents need Windows and macOS machines, why CLI may matter more than MCP, why Kubernetes is painful for this workload, and why the future AI cloud may look more like Stripe than AWS.We discuss:* How Daytona grew out of CodeAnywhere, Shift, and the “end of localhost” thesis* Why Daytona pivoted from human dev environments to AI sandboxes* Why agents need composable computers instead of disposable code execution boxes* The New Year's Eve MVP that customers chased API keys for* Why Daytona chose bare metal, stateful snapshots, and its own scheduler* How Daytona spins up one sandbox in ~60ms and 50,000 sandboxes in ~75 seconds* Why Daytona's biggest customer runs ~850,000 sandboxes a day* How RL/eval workloads create zero-to-100,000 CPU spikes* Why RL workloads went from 0% to roughly 50% of Daytona usage* Why customers compare Daytona against EKS/GKS and say they're “never going back”* Why every AI agent may need a computer, including Windows and macOS environments* The Apple licensing constraints that make macOS sandboxes hard* Why CLI gives agents more power than MCP* How open source helps agents integrate Daytona* Why agent-generated PRs may break today's CI/CD assumptions* Why AI SaaS companies reselling tokens may face a cold shower* Why the AI cloud may look more like Stripe than AWSIvan Burazin* LinkedIn: https://www.linkedin.com/in/ivanburazin* X: https://x.com/ivanburazinDaytona* Website: https://www.daytona.io* X: https://x.com/daytonaioTimestamps* 00:00:00 Hook* 00:01:12 Introduction* 00:03:15 CodeAnywhere, Shift, and the end of localhost* 00:05:58 What Daytona is: composable computers for AI agents* 00:08:07 The pivot from dev environments to AI sandboxes* 00:10:17 The New Year's Eve MVP and customers begging for API keys* 00:12:56 Bare metal, stateful sandboxes, and Daytona's scheduler* 00:17:28 60ms startup, 50,000 sandboxes, and 850K daily runs* 00:21:53 Spiky RL/eval workloads and the new agent infra problem* 00:28:12 RL workloads, Kubernetes pain, and dynamic resizing* 00:33:31 Why every AI agent needs a computer* 00:38:48 macOS sandboxes and Apple's licensing problem* 00:44:28 Why CLI may matter more than MCP* 00:48:11 Open source, GitHub stars, and agent integration* 00:53:11 Git, CI/CD, and agent collaboration bottlenecks* 00:58:15 Founder life and building a 25-person infra company* 01:02:44 AI SaaS, token resale, and API-first business models* 01:06:10 GPU sandboxes, data centers, and compute growth* 01:09:48 Why the AI cloud may look more like Stripe than AWS* 01:11:26 Closing thoughtsTranscriptIntroduction: Daytona, CodeAnywhere, and the End of LocalhostSwyx [00:00:02]: Okay, we're in the studio with Ivan Burazin, CEO of Daytona. Welcome.Ivan [00:00:07]: Thanks for having me, man.Swyx [00:00:08]: Ivan, you and I go back.Ivan [00:00:10]: Way back.Swyx [00:00:11]: How I don't even know how, you found, did you reach out or, for Shift.Ivan [00:00:17]: I reached out to you. The reason was you - we were just - we were thinking about I was one of the co-founders of CodeAnywhere, the first browser-based IDE, and so we were thinking a long time of, localhost should die. And you had this article.Swyx [00:00:29]: End of localhost.Ivan [00:00:30]: Then I reached out to you because of that, and then we talked, and I was actually at a different job and learning about I was the head of, developer experience, and you were quite well-versed in that, and I actually reached out to you, among other people, how do we go about that? What are the key things and whatnot at this point in time? And you were nice enough to take the call, and I remember I was late on your call with you.Swyx [00:00:51]: I don't remember.Ivan [00:00:52]: I remember because I was with my then I'm thinking of a girlfriend or wife at that point in time, I'm not sure. It's the same person, so that's great, and I was late ‘cause we were, in, Italy on, vacation, and then I was late for something. I felt so bad, and you were so nice to be, good about.Swyx [00:01:10]: The reason I'm nice is because I'm also late to other people, so it's like, who's, who's without sin here, yeah, so I have to, for those who don't know, InfoBip Shift, there's this whole thing that, you did in the past, and, and that was basically one of the inspirations for me starting AI Engineer, which is like, I have to thank you for giving me that push to be like, “Oh, you can, you can build and sell conferences?”Ivan [00:01:34]: I remember you asked you asked me at the beginning to give me advisory shares, and I was so focused on what we were doing, I said no, and I should've took the advisory shares. So I'm sorry, dude. But anyway.Swyx [00:01:43]: We're not, we're not venture backed.Ivan [00:01:44]: No, it doesn't matter.Swyx [00:01:45]: It's Yeah, anyway, so I think what's impressive about you is that CodeAnywhere is the thing that you've been trying to build, and, you kind of put it on hold and then came back after InfoBip. Just give us the story, do you - the story and the origin story, going into Daytona.From CodeAnywhere and Shift to DaytonaIvan [00:02:05]: Sure. Like, really way back, me and my co-founder have been together. I say this, I've said this multiple times, it's like we were married and divorced and married. Some people actually ask me is my co-founder my partner. they thought it literally. It's not literally, but we have done multiple companies together, and to your point, we had this shift where we went from the CodeAnywhere to the conference called Shift, and then back to, Daytona. We originally started stacking servers, doing like virtualization in the early 2000s and, routers and doing basically all these things, at a foundational level, and that was a services company which we sold to focus on what my co-founder actually invented, which was the very first browser-based IDE, right, I say the first. Before us was actually Heroku. They did it for a very short time until they became Heroku. But outside of them, we were the only one, and it was called.Swyx [00:02:55]: There was Cloud9.Ivan [00:02:57]: Cloud9 came out slightly after us. There was Replit, which came out when we stopped doing it, Replit came out, and they have been successful since then, which is great. There was Nitrous.io. There was quite a few that existed at the time, but it was like too early. But the interesting part is that we, at that point in time, because there was no VS Code, there was no Kubernetes, and Docker had just started when we Or I'm not sure if it was even public at that point in time. And so we had to build everything to the whole stack ourselves and that was the key learning that we brought into and that we've been using in Daytona today. So it was super early. There's about 3 million people used CodeAnywhere. It was slightly, it was angel-backed more than venture-backed. We ended up paying everyone back because it didn't have that sort of scale. But, three years ago, we started something similar with Daytona, which is not what we are today, but it was automating dev environments for human engineers, the basically the underlying stack of CodeAnywhere. And then we did a hard pivot last January to sandboxes. And so here we are.Swyx [00:04:01]: Historic pivot, yeah, and, it's one of those things where, I had independently invested in CodeAnywhere, but also in E2B, and then both of you pivoted into the same thing, and I'm like, “F**k.”Ivan [00:04:12]: You invested, you invested in Daytona. You invested in Daytona. But you were the first If we had not got your check, we wouldn't have done it.Swyx [00:04:18]: No way.Ivan [00:04:19]: No, it was like, “We have to get him on board first,” and you were that kicker that we, that got us off the ground.Swyx [00:04:23]: No, because you were putting me on your pitch deck, man. I was like, “Man, this is like a good trip if I don't invest.”Ivan [00:04:29]: That's because it was your quote. It's like we.Swyx [00:04:30]: Yeah. It's the end of localhost.Ivan [00:04:31]: Did a bunch of research about end of localhost and who was interested in that,.Swyx [00:04:34]: No, that's like, I put, I wrote that blog post, and every single company in that field reached out to me, and then every VC who was receiving those pitches then also had to call me and, talk it, talk through it with me.Ivan [00:04:47]: It's finally happening though.Swyx [00:04:48]: It was really super interesting.Ivan [00:04:48]: It's finally happening.Swyx [00:04:49]: It's finally happening.Ivan [00:04:49]: Yeah, it's finally.Swyx [00:04:49]: It's finally happening, with maybe sort of non-human users. Yeah, so what is Daytona today? Let's get like a quick description. I'm wearing the shirt.What Daytona Is Today: Composable Computers for AI AgentsIvan [00:04:58]: You're wearing the shirt. Yes,.Swyx [00:04:59]: It says, I think your branding is very good. Like, it's very consistent. It runs AI code. Like, it cannot be simpler.Ivan [00:05:05]: Exactly, but we're gonna probably have to change that.Swyx [00:05:07]: Oh, s**t.Ivan [00:05:07]: It's also a subset of what we do. Unfortunately, we really love this, Run AI Code is super simple. People interpret it different ways. I think we've given out 5,000, 6,000 of these shirts. People wear them with pride because it doesn't really market about us.Swyx [00:05:21]: Yeah, Daytona's on the back.Ivan [00:05:22]: It markets the back. It markets to the person itself, so I think we did a really good job on that one. But it is also a subset of what we do, because people, when they think about Run AI Code, they just think about these small, let's call it isolates, code execution boxes that, you send some code, you get an output. Whereas what Daytona is today is essentially composable computers for AI agents. It is, the market calls them sandboxes which can be misleading.Swyx [00:05:44]: All these things. All these things on.Ivan [00:05:45]: Yeah, exactly, ‘cause it can be misleading ‘cause people usually think about sandboxes as a demo or a test environment versus a production-grade environment. But what Daytona does, if you think of the laptop that you have in front of you or the computer that's over there, or, my wife is an architect, so she has like a Windows with a 3D graphics card inside to do 3D rendering. Like, as humans, we have different computers or different compositions of computers. And our belief is strongly that agents today and going forward will need all these different compositions of computers to do different types of tasks. And so we offer that basically through an API.Swyx [00:06:19]: Yeah, to give people - I'm trying to sort of front-load all the aha moments or the wow moments so that people can, stay engaged and click like and subscribe. the market is exploding, right? Like, you have been reporting 74% month-on-month growth, and it also, it's just been growing for a while. Like, it's been going like this. And every single - It's not just you guys. It's every single.Ivan [00:06:41]: Everyone, yeah.Swyx [00:06:42]: Sort of, compute provider. I don't know if you agree with me saying compute provider or not.Ivan [00:06:48]: It's fine.Swyx [00:06:48]: Yeah. So like organically PLG-driven growth, but also enterprise is doing super well, I think I wanna rewind to January of last year when you did the pivot. Like, so you obviously called this market early, and you were positioned for it, and you are now one of the market leaders. But what was the insight that made you do the pivot?The Pivot: From Human Dev Environments to Agent SandboxesIvan [00:07:06]: The insight that made us do this pivot is the quarter before that, so end of 2024, when we had - Basically, we did a demo with - I don't I think we discussed this as well, Devin was not public. You actually gave me access to Devin at that time. So Devin.Swyx [00:07:25]: I did?Ivan [00:07:26]: Yeah, you gave me access.Swyx [00:07:26]: I don't think I was supposed.Ivan [00:07:27]: Yeah, exactly.Swyx [00:07:28]: Yeah, I.Ivan [00:07:28]: So it doesn't matter. You.Swyx [00:07:29]: Yeah. I gave like three friends access.Ivan [00:07:31]: Yeah, or it was a call and you showed it to me. It doesn't matter. but OpenDevin was available, which is now called OpenHands. And so we're like, “Oh, this seems to be a thing. This is not public. Let's take our for human automation of dev environments and take, OpenDevin and launch that as a SaaS.” And we did that. Not very many people signed up and used it, but a lot of people reached out that were building agents, and they were like, “Hey, my agent needs a compute sandbox runtime,” whatever you wanna call it. I forgot what it was called at that point. And then we were like, “Oh, amazing. This is a new market. Here is our infrastructure. Here's our product, and go.” And what we found really fast, soon, was that people did not like what we had built. It didn't work. And I remember talking to people at the beginning when we're doing this, the sandbox we're building for agents. People were like, “Oh, why is it different? It's the same thing. We have like EC2, we have VMs, we have all these things.” But we saw that everyone we gave it to, it was like 20, 30 people, they all said, “No.” Like, “This is not what we need. This sort of breaks.” And basically, me and my co-founder not knowing a lot about - ‘cause we're infra people. We're not AI people. So I basically took it upon myself to like watch every single podcast that exists, including all of, all of these and all that, and sort of get up to date, read all the blogs, like get, understand what's going on.Swyx [00:08:45]: Do you wanna shout out who else was useful, just in case people are also looking.Ivan [00:08:49]: Generally we -, I looked at There's a few of podcast, different segments and different types. So there's you guys, No Priors, Bill Gurley's was great while.Swyx [00:09:04]: VG2, yeah.Ivan [00:09:05]: Yeah, while it was around. So there's a few. 20VC is interesting from a different dynamic, and some are different dynamic. But there was, also Red Points.Swyx [00:09:14]: We're not really about the compute market.Ivan [00:09:15]: It was also already - Sorry?Swyx [00:09:16]: You're, you want - You're looking at the agent infra market.Ivan [00:09:19]: I was looking at the agent market and the AI market in general and sort of understanding who are the players, what the perception, and how that goes. And like obviously you complement this with like going to conferences, going to events, going to meetups, reading white papers, like doing all the things that you have to do to understand what's happening. And so when we figured, when we sort of had an idea of what we had to build, literally over the New Year's Eve, literally on New Year's Eve, I half vibe coded the first MVP, first minimal viable product of what Daytona is today. And I went to sleep at like 3:00 AM or something like that. I was doing - I just put my like baby daughter and wife to sleep and, Happy New Year's, and go back to just, doing this. And I sent it to my co-founder, my CTO, and he saw it in the morning. He's like, “This is absolute garbage.” “Do not show this to anybody at all, but the idea is good.” And so he took two weeks, and he rebuilt it.Swyx [00:10:09]: Did it like look like that? Listen, I - It was rough idea.Ivan [00:10:12]: Oh, not even, not even close. Like it was it was way worse. But it was like a very - It was a simplistic view of what it should be. Like, it worked, but it was not ideal. And so he went, we went down the whole, which is his job as CTO, to go, and he came back with this version. We then called all the people that had said like, “This is garbage,” a quarter ago. And we set up these calls, and we gave it to - We just demoed it to everyone. And all the calls went long, every single one. They were 15-minute calls, and they all went to like 25, 30 minutes or whatnot. And everyone said, “We need, we want access.” There was no login, just an API key, ‘cause it was just a beta or an alpha. And they said, “Oh, we want access.” And we're like, “Sure, yeah. Okay, thank you very much.” But after like the next day, if we'd not send it, every single one, like every call that we did, everyone came back, “Where is my API key?” Like everyone wanted it. We're like, “S**t.” Like this is it. Like I've never felt So one, the understanding to your point was like most people thought it was the same infrastructure for humans and agents. We understood a quarter ago it's not. We just didn't know what was the right primitive. And then when we came, and we can talk about what that is, and we gave it to these people, I've never seen, I've never experienced - I've done multiple companies in my life. I've never experienced this, that people literally call you if you do not give them access. Like they want access right now. And so it's like, okay, they don't want this. the thing that they want doesn't seem to exist, or they have not found it, and they really want what we want. And then when we understood that we're onto something, and then when you think about the size of the market, like the market for human engineers and enterprise is a very large market, so think GitLab or whatnot. But the market for every single agent that will exist ever in the future is just like, what is that market? How big is that? And we're like, “We are all in on this.” And so that is where we made sort of the cut between the old product and the new one.Bare Metal, Stateful Sandboxes, and the Lambda + EC2 ModelSwyx [00:12:02]: Yeah. But it wasn't composable at the time?Ivan [00:12:05]: It was very - It was basically just a Linux box that you could change, that you could define number of CPUs, disk, and RAM. Like that is what you could do, but you couldn't have multiple operating systems, you couldn't resize it on the fly, you couldn't add a GPU, you couldn't do like all the things. It was just the, just the first sort of variation of that, yeah.Swyx [00:12:22]: Was it bare metal from the start?Ivan [00:12:24]: It was bare metal from the start. And so the interesting thing that we thought about right away, so our.Swyx [00:12:29]: Which, give people the background, what is the normal path?Ivan [00:12:32]: Yeah, so, basically most providers run this on top of VMs. And also.Swyx [00:12:37]: Firecracker.Ivan [00:12:38]: Yeah, they run on Firecracker and VM. And so we also fire - We can get - We have multiple isolation layers and we can do that. But the common way to do it is that they, one, that the state of the machine, or the hard disk is not part of the sandbox itself. And the other thing is they're not meant to last forever. So most of them are preemptible, like they can There's a time that they can live. And so our thought was when we were going into this is, agents will be like humans in the sense of you don't want your laptop to be shut down until you're done with work. Like, and you want to close the lid and open the lid, it's the same state. So you - Agents would want that, like the pause and come back. They want those two things. But also agents really want speed, right? Can they get it? So when we thought about it's like we need something insanely fast, how to make it fast, how to make it long-running, and stateful. And so those two things, it's like combining a Lambda and an EC2, right? Those two things together. And so we didn't have an idea how others did it, ‘cause we didn't know too that there was a market around this. It was more like, okay, this is what we need, what they need. And we looked at Kubernetes, it wasn't wasn't good enough for that. We looked at Nomad, it didn't enable that. And so our history in rewriting our own scheduler at CodeAnywhere is basically what my CTO came up with. Like, he's like, “Oh, the learnings from there,” and he brought it. And the funny thing is, our third co-founder, when he saw it, he's like, “Dude, what is this? This is like 2008.” Like, we went back in time, and he's like, “Exactly.” And so the reason why Daytona is like super fast, and you see this on benchmarks, is we essentially, we run on bare metal. We have our own scheduler, we use the underlying, disk, CPU, and RAM of the underlying machine, which means your IOPS are insanely fast because there's no, there's no network between an EBS or something like that. But also the snapshot, the point in time, the templates, are also preloaded on the bare metal machines. So when you fire off a sandbox from a template or a snapshot, you're essentially directed to the bare metal machine where that snapshot is based on that NVMe drive, and then it literally just turns on that machine, and it's local. There's no network latency, anything on there. And so that is sort of the specificities that we, when we're thinking from first principles, what a computer would look like for an agent, that is what we came up with, and that's what we created.Benchmarks, 60ms Startup, and 50,000 SandboxesSwyx [00:15:02]: Yeah. I should maybe, I don't know if you endorse this, but there's someone that does compute SDK, you guys do very well on there, with like the TTI, right? I. is this a, is this a is this a relevant benchmark for you guys? I don't know.Ivan [00:15:16]: I don't know, and it changes every day. So today RKL is.Swyx [00:15:18]: I don't know what RKL is. Never heard of it.Ivan [00:15:20]: Yeah. RK, yeah, so it is there.Swyx [00:15:22]: You are, at least a third of the next tier of performance, and then, there's a lot of other better-known names that are very slow to start.Ivan [00:15:31]: Yeah. We've been the number one by far for a long time, and now there's different, there's different definitions also of sandboxes, different isolation patterns, different other things. So RKL runs it literally on the S3, the data, so it's very different, and they spin up a sandbox, spin up a container for that, so it's a different type of thing. So the definition of a sandbox is something that we can all, we all need to get along with. But yeah, we're insanely fast on getting these things, up and running. And so you can see even there that it's a zero point 0.10 to 0.11, so.Swyx [00:16:03]: Close enough. Yeah. what else do you need, right?Ivan [00:16:05]: Yeah. So the benchmarks itself, so, in this, in I don't think the benchmarks equate to market ownership or revenue or anything like that. and I've seen this with multiple benchmarks, not just in sandboxes, but in general benchmarks around.Swyx [00:16:20]: It's table stakes. It's just like.Ivan [00:16:21]: Exactly. But it doesn't hurt.Swyx [00:16:22]: Just roughly check.Ivan [00:16:22]: Like you definitely have to be up there and you have to be competing so that people know that, oh, this is definitely one of the top. Because this is only one dimension of what customers look for. There's other things like how many can you spin up consecutively? There's a feature set, there's support, there's like all different things that people look at, but you definitely have to be there, on the benchmarks.Swyx [00:16:40]: How many people do people spin up consecutively?Ivan [00:16:43]: So we have.Swyx [00:16:43]: Or concurrently, is the Concurrency, right?Ivan [00:16:45]: There's three metrics that we look at. And so one is like time to spin up one, and so our time to spin up one is 60 milliseconds with network latency. So request, spin up, reply, 60, the whole thing, 60 milliseconds. That is one. But if you wanna spin up 50,000 at once, we are now at about 75 seconds. So it takes about 75 seconds to spin up concurrently 50,000. Some others, there's public data around this, like take 2,000 seconds, which is 30 minutes. Like there's different variations of that. And then there is the so it is speed of one, speed of like multiple, and then how many can you consistently have up and running. And so we basically have right now no limit to how much we can add because we basically own our own metal. But the biggest customer of ours does like about 850,000 every single day is sort of where they're, where they're just shy of a million every single day that they're running, we do have a request for half a million concurrent, which is literally half a million CPUs somewhere running. So that's an interesting.Swyx [00:17:44]: They pay by like vCPU seconds.Ivan [00:17:47]: By seconds, yeah.Swyx [00:17:47]: Or whatever. Yeah. Okay, and so and then, and the other thing is, the sleeping and the resuming, ‘cause it's all the stateful resumption of all these things, how, what kind of workload are people putting through this, right? Like how is it Do we measure by gigabytes in memory, gigabytes in storage? I don't In like network attached storage. I, what are the costly ones of, out of all these features?Workload Economics: CPU, RAM, Network, and StorageIvan [00:18:15]: The most expensive thing are CPU.Swyx [00:18:18]: Okay. Yeah, of course.Ivan [00:18:18]: The second one, yeah Then it's RAM, then it's disk. We actually don't charge.Swyx [00:18:22]: Which is snapshotting, right?Ivan [00:18:23]: No, it's actually the, snapshotting's part of it, but basically the size of your hard disk, of your machine. So do you have 10 gigabytes, do you have 20, do you have 50, do you have whatever? And then the transference of that. Right now, currently we don't charge for, network at all at Polychron.Swyx [00:18:37]: Oh, you gotta, yeah, you gotta fix.Ivan [00:18:38]: Yeah. It is very much a it's a larger and larger part of our bill, so we're working around, that part there. Obviously, that is the least, expensive, so the hard disk is the least expensive, so it's basically CPU, RAM, for us network, ‘cause we don't charge the customer, and then hard disk, is how it's split up. But there's also different types of workloads, so we basically split it up into two types of workloads in Daytona. One is what we call background agents or long-running agents. and the other is, basically RLs and evals, which I put sort of together. And so they have very different patterns of usage, and if you look at the usage of a background And I'll just name names of companies, not specifically.Background Agents vs. RL/Evals: Two Usage ShapesSwyx [00:19:21]: Yeah, open, all hands.Ivan [00:19:23]: Yeah. So like a background agent's a Cognition, a Lovable, a like all these things are Harvey. These are all long-running, background agents. And so if you look at their usage patterns, their usage patterns are similar to human, which is like follow the sun. Basically, the usage patterns of that is like noon is probably the highest, and the midnight is the lowest, and then weekends are lower. weekday is higher.Swyx [00:19:42]: Yeah, that's a fun question. How global is it? Is it very US-centric or?Ivan [00:19:46]: The US is a large part, but we have currently, we have Asia, Europe, and the US regions.Swyx [00:19:52]: So it's quite global.Ivan [00:19:53]: Yeah, it's quite global. We have it all over. It's interesting that our I talked to you a bit about this. Our number one city by user.Swyx [00:20:01]: Hmm.Ivan [00:20:02]: Is Singapore.Swyx [00:20:04]: Oh, wow. Amazing.Ivan [00:20:05]: Which is an interesting one, right? Not by revenue, just by just like by individual head count.Swyx [00:20:09]: Really?Ivan [00:20:09]: Just like an interesting thing.Swyx [00:20:10]: Singapore is, Singapore is weirdly high in the adoption charts of AI for the population. It's like an, seven, eight million population. And it's like keeps showing up.Ivan [00:20:20]: No, it's quite interesting. We were quite shocked, and I was like, “Oh, this is interesting.” And also one that's up there.Swyx [00:20:24]: There's a reason I'm doing AI using Singapore. it's because I'm from there.Ivan [00:20:27]: We're there. We're gonna, we're gonna be there as well. and it's interesting that Japan is in the top or like Tokyo's in the top, which is in all the tech cycles it has never been. It has never been, so it's quite interesting that they're.Swyx [00:20:39]: I think the Japanese just love AI. Yeah. It's that, and then it's Brazil. That's it.Ivan [00:20:44]: Brazil has always been in.Swyx [00:20:45]: I think.Ivan [00:20:46]: Even when I look, if you look at like GitHub's data and ask historically with CodeAnywhere, it was always like US, Western Europe, and then you'd have like India, Brazil, China, like that would be there. But like Singapore was not in, specifically Japan was never in sort of that top, that top.Swyx [00:21:01]: Yeah. Weird pockets.Ivan [00:21:01]: Weird. Yeah, so it's very global.Swyx [00:21:02]: Okay, so actually that, but that's helps you to distribute your load through, all time?Ivan [00:21:08]: The interesting thing is like we have those kind of loads, but if you look at the researcher loads, they're quite different. So what they are is like if you give them concurrency of 10,000 or 50,000 or 100,000 CPUs at ARMb, when they fire off a run, it's just 100%. And then it just runs, and then it stops. So it's very, the usage pattern is squares basically, right? And it's also not follow the sun, because people will fire it off at midnight before they go to sleep but then wake up and so it's very unpredictable, so you don't know where that is. So the shapes of the usage are quite different than we have had before. And also what's interesting is when it's sort of a follow the sun, even if you have a high growth company, you can sort of predict your usage patterns and have enough capacity for that, because it's sort of, it grows in a, in a way you can project. When you have companies doing sort of like evals and RL, they're super spiky. So they're gonna come in, it's like, “We're gonna use nothing, then can we have 100,000?” Right? And then go back down. And then 100,000, go back down. So it's very different, right? And.Swyx [00:22:09]: Do you want to lock them into commits so.Ivan [00:22:11]: Yeah, we do.Swyx [00:22:12]: Yeah, okay.Ivan [00:22:12]: We so we have to lock them into some sort of commits to have that capacity, because we have to have, basically we have to have the capacity for peak. Right? And so right now, Daytona's mean utilization is 15%, 1-5.Swyx [00:22:25]: Oh my God.Ivan [00:22:26]: So it's very low.Swyx [00:22:27]: Because it's very spiky.Ivan [00:22:27]: It's very spiky, but we get up to 90%. so we have these things. And so what we're, what we're looking at right now as a company is similar to Cloudflare where you can like geo move things around, but that works really well for basically the background agent where it's follow the sun. But this, it's not. Like it's a very different shape. Obviously with scale you figure these things out, but that's an interesting new problem that we have, as a compute provider in the agent space. And when we were doing the conference recently, and so we talked to like Nikita from Neon and.Swyx [00:22:57]: I should bring it up.Ivan [00:22:58]: Parag from Parallel and whatnot, everyone has the same problem. Whereas the usage is super spiky, and this is something that has not happened before, that you have these types of like it was always, it the amplitudes were not this high, right? So it's quite interesting use case and problem solve.Compute Conference and Spiky Agent InfrastructureSwyx [00:23:12]: Yeah, I don't know if we're gonna bring this up again, but let's just talk about the conference, you had like 1,000 something people at the Warriors game, at the Sorry, where is it? What's.Ivan [00:23:22]: Chase Center.Swyx [00:23:23]: Chase Center.Ivan [00:23:23]: Chase Center.Swyx [00:23:24]: I went. It was, it was very impressive. Obviously, you can, how to throw a conference, what did you learn? you put, you pulled together all these impressive names.Ivan [00:23:33]: What I.Swyx [00:23:34]: What were you looking for?Ivan [00:23:35]: My thesis behind the Compute Conference was let's bring together people that are building infrastructure for AI agents. Because when I think of what we're building, it is the agent is the primary user, what are the ergonomics and usage patterns of agents, and so we can do that. And what I found, this was a theory, it wasn't proven, is that we all have these problems, as I touched onto. And I was, as I was talking on stage, it was like we all have the same underlying infra problems, which is this spiky workloads, unpredictable workloads that we've never had before, in human, compute or human infrastructure. And it's, again, it's the same when I was talking to Parag or when I was talking.Swyx [00:24:20]: Lynn. Nikita.Ivan [00:24:21]: Lynn, Nikita. Lynn especially, I was talking to her the other day as well. Like the It is a very interesting type of problem to solve because I can touch on Cloudflare because there's a lot of like talk about that recently as to how they solve that, which is they have a bunch of geos, and basically, as users work in different places, and depending on your tier, they can move you around the geos. And so that how, that's how they get the higher utilization. But you can sort of predict these, and it's If it's something in You'll rarely get a spike that is 10 orders of magnitude. Like you'll get a like let's say one of your customers has some like an exponential curve. What is that to I'm using Cloudflare as an example. 10%, 20%, whatever it is. I don't, I don't have this data, I'm just assessing. It's surely not 10x, right? It's surely not something there. And so how do you go out and solve this problem? And we're all solving this in different ways. So we have.Swyx [00:25:11]: She also has the same thing.Ivan [00:25:12]: Yeah, I know specifically that like Neon had that issue as well. Like how are we solving these spiky loads and things like that ‘cause we talked about it. And so the interesting thing for me to actually internalize was, yes, everyone that's building for agents first is going through this, and we're all solving similar problems, which is quite.Swyx [00:25:28]: Let me let me double-click on this. Okay. So for example, Neon, I happen to know that they're very sort of S3 oriented, right? so they're just like fully bet on S3. And you get to benefit from S3's distribution and infrastructure. So I would imagine that Neon doesn't have to care, whereas Lynn maybe has to care a bit more because obviously she's doing GPU inference. And, for listeners, we did an episode with her, one and a half years ago. And you have to care. But like, right?Ivan [00:25:54]: Parag cares for sure, and Nikita.Swyx [00:25:58]: And Parag is C of, Parallel.Ivan [00:25:59]: Parallel, yeah.Swyx [00:26:00]: Former CTO of Twitter.Ivan [00:26:01]: Twitter, yeah.Swyx [00:26:02]: They are the search.Ivan [00:26:03]: Yeah, they're search, yeah.Swyx [00:26:03]: I You and I know but the listeners don't know.Ivan [00:26:08]: Yeah, we can put it down in the screen, and so ‘cause we, when we were talking.Swyx [00:26:11]: I'll put it up on the, on the screen.Ivan [00:26:12]: Yeah, right.Swyx [00:26:12]: People can look it up if they need.Ivan [00:26:14]: Look it up. And, yes, but they still have CPU and RAM, allocation that you have to have up and running. And so CPU and RAM, you have to allocate that and have that ready. And so there's basically two ways to do it. One is you either over-provision and you can handle the bursts, or two, you basically have, I don't know if this is a term, just-in-time compute, which is like as your load becomes, as your usage comes in, you can fire off requests for VMs or bare metals at other cloud providers and then get them up and running.Swyx [00:26:43]: This is if you go above 100%, right?Ivan [00:26:45]: Yeah, this is.Swyx [00:26:46]: Like your overflow.Ivan [00:26:46]: If your overflow, like spillage or whatever you do.Swyx [00:26:48]: You probably lose money on it, but it doesn't matter, right?Ivan [00:26:50]: It, not Well, you might, you might not That is a more cost-effective way to do it but it's a slower way to do it. Because basically what you have to do is you have to like queue your requests, spin up these just-in-time compute, get it all ready, provision it, and then get your workload there. And so if the time isn't important that much, that's fine, and you can do that. But if your customer, and especially for, let's say, the RL training runs, the reason why a lot of people come to us is because GPUs are more expensive than CPUs, right? So you want your GPU running at, what, 100% the entire time. And so when you're running runs on CPUs, when the when the CPU cycle is like down and spinning up the next one, you want that to be instantaneous so that your GPU doesn't go down, right? And if you then have to like go out and provision machines, you're essentially telling the GPU that it has to wait, and that's incurring our cost. So there's things that you have to try to solve for there.RL Workloads, Declarative Images, and Kubernetes ReplacementSwyx [00:27:43]: Yeah, let's talk about the different workload, right? You said that, what was it? A few months ago, you had zero RL workload and now it's 50%.Ivan [00:27:52]: It will be this one, 50%, yeah.Swyx [00:27:54]: Let's talk about how different it is, right? Like I imagine, for example, a lot less dynamic code generation of like arbitrary code. Like here, it's probably all the same code. You're just doing parallel runs or something, I don't know.Ivan [00:28:05]: Yeah. So you'll have multiple Depends on the like for each run, you'll have a snapshot. And they, for the most part, they actually do use our declarative image builder, which is like, “Oh, we, the agent wants these dependencies, these env vars.”Swyx [00:28:17]: These ones, yeah.Ivan [00:28:18]: Yeah, the declarative image builder, it.Swyx [00:28:20]: Which is a very modal like thing that they.Ivan [00:28:22]: Yeah. And so we build it on the fly and then we propagate that snapshot, and you can spin up as many sandboxes as you want against that snapshot. And then if you have to do changes, the model can, or like it could be also be automated. It's like, “Oh, now for the next run, we need to install these things or remove these things or whatever to get, a task done,” and then it goes off and runs that. So yes, that is something that it seems that they prefer. The number one reason I found, or should I say, let's take a step back. What we are competing against in that environment is essentially managed Kubernetes. So EKS, GKE, whatever. That is what the vast majority run on. And anyone that has tried Daytona versus GKE, EKS is like, “I'm never going back.” That has always been. There's a few reasons. One is the ergonomics. So if you have, if you're using Kubernetes to spin that up, you have to essentially manage the interface interactions with that. Daytona, although as a compute provider, it's more akin to a Twilio and Stripe from a consumption perspective than it is an AWS. Like you have an API, an SDK, it's quite like easy and seamless to get these things up and running, that's one. The other is the speed to which we spin up, which we mentioned earlier, which is much faster, and the scale to which we can go to. We haven't got into features, but an interesting feature is that it's very hard to OOM, or out of memory, our sandboxes, because we can dynamically on the fly.Swyx [00:29:48]: Resize.Ivan [00:29:49]: Resize, which is like impossible on almost any other thing. There are some technologies that enable you to do that, but it's like a very hard thing. And so we actually saw this when, the Terminal Revenge team is, brought us actually. So thank you, Alex and the team, that brought us into this whole space.Swyx [00:30:05]: It's just very rare that, a framework would just say, “Guys, just use Daytona.”Ivan [00:30:11]: Yeah, I think it says it somewhere. Yeah.Swyx [00:30:13]: Yeah. I was like, “What is this?”Ivan [00:30:15]: There's all, there's multiple there, but they also mention a few other places. and so Daytona specifically-We have, the, just jumping on themes here We, I don't know where it says Data Center.Swyx [00:30:27]: I, there.Ivan [00:30:27]: Doesn't matter.Swyx [00:30:28]: There's a very strong recommendation, which is, very unusual. Which is, it's.Ivan [00:30:33]: We do not pay them for this, just.Swyx [00:30:34]: I know, yeah. They just like you.Ivan [00:30:35]: Yeah, they like us. yeah, and also a thing, so, Data Center has multiple isolation sets underneath. The customer doesn't have to know what they are. But basically we have Docker, which is a container, that's hardened with Sysbox. So it's Docker's, isolation that is a security equivalent to a VM, but it's still a container. And that is the default, and they, especially in these training workloads, really like that as an interface to be able to use just a basic Docker container, and we enable Docker and Docker. Which for these RL runs, if you need to do a Docker compose or Kubernetes, you can spin up a K3S inside of these things, which unlocks a huge amount of workloads that you can do that you cannot do on other providers. So just on that part is much more interesting. And so we went that, through that. We showed them that we could do that, and they enjoyed that quite a bit. They being the general venture people.Swyx [00:31:28]: Those people, yeah.Ivan [00:31:29]: And Harbor people.Swyx [00:31:29]: Harbor people, do are they, are they a company yet?Ivan [00:31:33]: As far, I do not know.Customer Pull, Slack Connect, and the Computer Use BetSwyx [00:31:35]: Okay. All right. Yeah. It's like super obvious that like, there's a lot of excitement and success around these things, okay, so yeah, tell us more, right? Like, this is an exploding workload, Harbor adopted you, which helped speed things along. But what are you learning as this new workload comes online?Ivan [00:31:53]: There's a couple things that we learned, which we chat about in the beginning. We, and this has led our story, as we mentioned, we like talked to a lot of customers along the way, and we add more features and more tool sets as we talk to customers. And it's interesting that And I think it's that the ecosystem is so small and/or the models get smarter, where when we see one user come with a request, we know it goes on a roadmap if like three to five customers come with the same request in that week. It's like very bizarre. It happens so many times, which is.Swyx [00:32:27]: Because they're all friends.Ivan [00:32:28]: Sorry?Swyx [00:32:28]: They all, they're all friends. They're all in the same group chat.Ivan [00:32:30]: Yeah, probably, yeah. ‘Cause and they're like, “Oh, can you do this?” And I'm like, “Okay, this is interesting. We'll put it on a feature request.” And then the next one's like, “Oh, can you do this?” “Okay.” It's all the same, right? It's always the same. And so what we try to do, and I personally try to do, I try to be on as many call, quote-unquote “sales calls” I can. I'm in every Slack channel. We literally have about 1,000 Slack Connect channels, something like that. It's an interesting, there's so many interesting things you find out when you have all the Slack channels. You can also see where people, transfer between companies. You see leave Slack channel, enter Slack channel. It's an interesting thing. Also, just I digress, I feel that Slack Connect is literally LinkedIn what it should be. You have a list.Swyx [00:33:08]: LinkedIn charges you to, use your own connections, but Slack doesn't, right? Slack is like, do it for free. It's more lock-in. It's great.Ivan [00:33:15]: Yeah. It's amazing. Yeah. It's one of the reasons.Swyx [00:33:17]: You're gonna pay Slack for life.Ivan [00:33:18]: Exactly. You're there for life. So that's interesting. And so one of the things, the newer things we were talking about earlier is we made a big bet and put a lot of investment on computer use. that is not seen publicly the light of day. We haven't GA'd that yet, but we have.Swyx [00:33:32]: Is there a thing I can pull up?Ivan [00:33:33]: There is computer use there. It's right up a bit.Swyx [00:33:36]: Oh, yeah. Okay.Ivan [00:33:38]: What we have, what we talked about and what we've seen publicly is there's this theme now about, the human emulator where And Elon from XAI has talked about this publicly, and if you think about the models today, they're actually quite sophisticated and they can do a lot of work, but they still don't have access to all the tools. Like, I'm a strong believer that the most efficient way for an agent to work is essentially headless or through, terminal or whatnot. But if we, if we look at knowledge work in general, there's about 100 million knowledge workers in the US, about a billion in the world, and knowledge workers, and the salaries of them aggregate to 10 trillion in the US 50 trillion worldwide.Swyx [00:34:24]: Wow.Ivan [00:34:25]: Something like that. And if we look at, the five most important sectors of that, so like healthcare and government and financial services and whatnot, that's about 56% of that. So let's say it's about half of that. So in the US it's about 25 trillion, and most of them, most of that work is actually still locked into legacy apps inside of Windows, which is not going anywhere for a very long time. Like, people just won't invest in that. How much of it? our assumption is the following: if, in the RPA market, which is similar market, well, not the same 25% of, these white collar, workers', work is automated. If an agent is more sophisticated, can go through more runs, figure stuff out, let's say it's, 40%, right? And so if you take 40% of that, you get to essentially, $10 trillion a year.Swyx [00:35:17]: That's a TAM.Ivan [00:35:18]: That is a that is a TAM. So that's the TAM of the models, right? That's not our, essentially ours. But you get to that size, and to be able to do that, you essentially have to give agents these computers with the legacy. So computer use, either Mac or Windows or Linux. Linux we also obviously have and others have. But Windows specifically is something very new, and the only option right now is an EC2 with, Windows or on Azure. Both of them take anywhere from three to five minutes to spin up. We've created an actual sandbox, so it's a second instead of milliseconds, but you have, point in time snapshots, you have, forking, you have all the things that you have from a sandbox, but essentially enables you to hopefully unlock all this value. And so that's been our big push and bet, but we've sort of, kept our ear to the ground. What is sort of the next things in the market?RPA Returns: Why Agents Still Need ComputersSwyx [00:36:06]: Yeah, knowledge work, and building, and sort of RPA, the next wave of RPA. I got very excited about RPA kind of during COVID times. The UI path was IPO-ing. And it was, a very hot Isn't it, Eastern European?Ivan [00:36:20]: It is, Romanian.Swyx [00:36:21]: Romanian?Yeah, it might be the only Romanian, big unicorn okay, yeah. This I don't I don't, I don't have like a I think there's, I think there's a stage being set for the resurgence of RPA, ‘cause everyone understands that, yeah, no one wants to deal with these shitty apps and no one's gonna rewrite them. Like, you just have to do, a remote operation and programmatic operation of them.Ivan [00:36:45]: If you wanna unlock it, my own setup was basically the following. So I was doing a board deck recently, last month, whatever, and I'm like, “Okay, let's just, let's just do automated.” So, all our data's in, ClickHouse and PostHog and QuickBooks, where everyone else's is, and I'm basically, connected that all to, my Cloud code, like go off and go Cloud code whatever. Go off and, here's the integrations, go do that. It pulled out the first report, which was great. It connected to Brex and all these things, pulled it, which was great, and then I say, “Okay, now pull out this, and this,” and I kept getting, really well McKinsey-style design reports, but the data said partial data. all the missing data, partial data. Like, it can't access all the things, and I got so frustrated, and so I got, I got, my Mac Mini virtual sandbox with OpenClaw. I gave it its own account in our company, and then I went to all these services and created a read-only account, so literally like an intern in your company. And so I would say, “Now go and do this report,” and it would get the same, or like, “I can't via the MCP or the API or whatever. I can't get all the information.” I'm like, “Go log in.” And it will log into the website, then go in, export the data. It'll export the data and do the thing end to end. So even for things that have today APIs, not all of it is exposed, and I to get value, I get immense value right now, but it has to be a computer usage, unfortunately, and so I spend a bunch of tokens just on that, but I get the job done. And so if even a startup like ours, and using all the hottest tools, still needs a computer agent what hope does, Goldman have to have a headless, right?Swyx [00:38:22]: Yeah, what a - Why isn't Microsoft doing this?Ivan [00:38:27]: I'm pretty sure, Satya had a post yesterday.Swyx [00:38:29]: Oh, okay. I see.Ivan [00:38:29]: Which was like, “Every agent needs a computer.”Swyx [00:38:31]: I see, I see.Ivan [00:38:32]: So they have launched something recently.Swyx [00:38:34]: Yeah, they have Microsoft Power Automate, I'm sure, I'm sure, they're gonna have their version.macOS Sandboxes, Apple Constraints, and the Windows OpportunityIvan [00:38:39]: Version of that, yeah.Swyx [00:38:39]: You're gonna try to do yours, and it - I always know there's always demand for Mac, but I know it's, tricky to host, macOS sandboxes.Ivan [00:38:49]: We will have macOS sandboxes fairly soon. The problem with macOS, OS sandboxes is, I'm deep in this, I don't know how much interesting is.Swyx [00:38:55]: No, it's.Ivan [00:38:56]: MacOS has this problem.Swyx [00:38:57]: It's a licensing thing, right?Ivan [00:38:58]: Licensing thing. So one, you're allowed to run only two parallel VMs per machine, so that's one. Two, you can only license to a different user every 24 hours. So if you come in and theoretically, if I wanna charge you per second and I charge you one second, I have to have it idle for the rest of the day. I can't have anyone else doing that. So the pricing will be different in the sense that I will have to - we would have to charge for 24 hours, and that's not even, that's not even the most difficult thing. But the, thing above that is, from a security perspective, they enable you to do memory snapshot, pause, resume, but only on the same physical drive, physical machine. And so what you can do in, Windows world or Linux world is that I can move in the background, your snapshot from one to the other and manage load, right? Here, if you wanna do that, you essentially have to have your.Swyx [00:39:49]: Yeah, snapshots. Yeah.Ivan [00:39:50]: Your.Swyx [00:39:51]: It's like.Ivan [00:39:51]: Physical machine.Swyx [00:39:52]: You can't break it up.Ivan [00:39:53]: You can't, you can't move things around that, and all of that is, that part is, from a security standpoint, if it is written. Like, I understand the security aspect of that, but it disables you from doing these agentic, like really scalable agentic workloads.Swyx [00:40:08]: You need to do a vibe-coded, clean room implementation on macOS that you can then - That's like Clean OS or something. I don't know.Ivan [00:40:17]: So. We have.Swyx [00:40:18]: ‘cause like Linux was originally like a clean room rewrite of Unix.Ivan [00:40:21]: Okay. Yeah.Swyx [00:40:21]: Or something like that, right? Like same thing to macOS. Someone needs to do it.Ivan [00:40:25]: Someone will do that, and someone will have some long-running agents for a few days to figure this stuff out. But yeah. So definitely we - we're really close to offering something ‘cause people do want it, but the pricing will be different, and the feature set will be sort of stringent.Swyx [00:40:38]: Yeah, nobody's gonna use this. like, the labs, the labs will because they want to automate macOS.Ivan [00:40:42]: They have to do RL. They have to do RL again. But even if you The - So the point is with the RL part, if you, if you do RL on macOS, then the next iteration of the model comes out, it will be able to use these tools significantly. Then you actually need to run those, that somewhere. So you're gonna have to have that, later on. And from, if anyone at Apple is listening, I very much feel that they are shooting themselves in the foot of the scale of the revenue of compute or licensing they could get if they would just enable a concurrency model similar to what you can get on a Windows and a, and Linux.Swyx [00:41:17]: Yeah. Yeah. And I'm sure they've heard this before. They just don't care. Yeah, it's And maybe they will change their mind with the new CEO.Ivan [00:41:24]: Yeah. We'll see.Swyx [00:41:25]: We'll see.Ivan [00:41:25]: High hopes.Swyx [00:41:26]: High hopes.Ivan [00:41:26]: High hopes.Swyx [00:41:27]: Okay. But I, it's very clear the market opportunity is huge in Windows, and you can go for a long time on just Windows, but your customers are gonna want both. and I think, it is interesting to me that, this is the sort of God application of agents, right? Like, I don't It was - How big was OpenClaw for you guys? Like, was it, was there, a significant bump.OpenClaw, Agent Labs, and the B2B2C Sandbox MarketIvan [00:41:54]: Not for us because we.Swyx [00:41:54]: Because you already.Ivan [00:41:55]: We're kind of positioned differently. Whereas although it's completely PLG and we have individual developers that use it, most of the users that use Daytona are sort of a B2B2C. Sort of it's either B2B or B2B2C. So, in the researcher world, it's B2B, so you're selling to, labs and neo labs and things like that. But on the long-running agents, it's mostly, from a scale revenue perspective, it's mostly B2B2C, where you have a app layer agent that uses you at a big scale.Swyx [00:42:26]: Like a Manus. Yeah.Ivan [00:42:28]: Like a Manus Lovable type of thing.Swyx [00:42:31]: Yeah. I think that's the question of, well how, um-Uh, yeah, B2B to C is basically to me what I've been calling an agent lab, which is kind of like you're not in a model lab, but you're making a very good wrapper that is a platform that other people can sign up so they don't have to code those things. Yeah, it sound, it sounds like a much better market than the direct OpenClaw market.Ivan [00:42:56]: I've like - We I've done multiple things. So the CodeAnywhere's part of our career path R in the calendar, was very much an end user developer product. And so that is great. It You can get a lot of developer love, and I feel that we do as a company have a bunch of developer love. But it's a different type, where it's people building these things. Again, it's more akin to a Twilio because you don't really run - As a person, you wouldn't run Twilio. I don't know how many people remember. It was like ask your developer billboard and whatnot. And people really love Twilio, but they only used it inside of like, “Oh, I'm building this app or service for thing.” And so we're very much directly to that. And you also know that I used to work for a competitor for Twilio, so it's kind of ingrained, in my DNA.Swyx [00:43:35]: People don't know InfoBip is that big.Ivan [00:43:38]: Yeah, it's.Swyx [00:43:39]: Because.Ivan [00:43:40]: It's a billion euro.Swyx [00:43:40]: They're all American. They're like, “Whatever's in Europe doesn't matter to me.” But like it's the, it's the same size or bigger? Same size?Ivan [00:43:46]: It's about half the size.Swyx [00:43:47]: Half the size?Ivan [00:43:48]: Yeah, about half the size.Swyx [00:43:48]: It's like, yeah.Ivan [00:43:48]: Still huge. Multiple billions a year. Yes.Swyx [00:43:51]: That's crazy.Ivan [00:43:51]: Exactly, and so that - These are like really interesting and large revenue-generating, very sticky businesses. Whereas when you're selling to the - When your focus is the end developer, it is a very hard sell because they're very price sensitive, very price conscious, very around that. And there's very It's very hard to scale. Your cap is the number of people that are willing to spin up - First of all, wanna spin that up, and then spin up multiple of these. Whereas if you're in the enterprise one, like we know everyone's talking about like how many tokens they're spending, I'm spending. Like a lot of companies today are like, “If this is our company, spend as much as you can.” Like basically that is where we're going. And so if you think about that paradigm, where you're selling to companies that say, “Spend as much as you can to generate, productivity,” versus, “Oh, I'm a single person. I have this much budget, and I'm doing this thing because it's fun or it's helping me out or whatever.” Like it is a different, it's a different go-to-market, I think, strategy.MCP, CLIs, and Sandboxes as the Agent RuntimeSwyx [00:44:50]: Yeah, there's a lot of discussion. I'm just kind of going through like the mental list of things that are in your favor, which is, for example, MCP versus CLI. Like obviously you want CLI. It's been very good for you. I feel like it's maybe a drop in the bucket or maybe it's huge. I'm just checking whether it's like these are big trends.Ivan [00:45:10]: Those things you - work well in our favor, to your point just because every.Swyx [00:45:13]: They're kind of drop in the bucket, right?Ivan [00:45:15]: I think it's like sort of all the things come together. And so there's so many things that impact that. To your point, like OpenClaw wasn't huge for us, but like having the agent SDK, from Anthropic, so or Cloud Claude Code was very interesting. The reason why it was interesting is that a lot of, let's call them app I don't know what to call them, app layer agent companies, essentially they are like, “Oh, I can create this new app, this new agent. All I need, I just use Claude Code, and I throw it into a sandbox, and then I have my interface to the human to that.” And so that enabled so many more companies to actually offer this, and then they would pull on sandbox. So that was, that was interesting. And to your point, like MCP, versus the CLI, the MCP is an interface against an API, whereas the CLI is like you can actually go do things. Like this is it. The difference between integrations and actually running scripts or data or analysis against a thing. So being able to use a CLI very well enables the agent to do more things, and it's because that people will invoke a sandbox, they'll run it in the CLI, and but it'll do anal-analysis on that data and then give you an actual result versus just, pulling data from an API source.Swyx [00:46:29]: Yeah, it's a layer of indirection basically, it's the same thing as agentic search versus RAG, which where you're.Ivan [00:46:34]: Exactly, yeah.Swyx [00:46:34]: Just like you just win whenever people put more agents into their workflow. And so like it doesn't really matter, but I'm just kinda teasing out like what else have people heard about that like it's sort of, “Oh yeah, this is another sandbox use case. Oh yeah, that's another one.” Am I, am I missing any big ones?Ivan [00:46:51]: The thing, the thing that people, which is the computer use stuff, which I think is probably the most interesting one, is, and to your point, we've talked to so many people over the last year. It's like, “Oh, like why do you need a sandbox? Why do you need this? Why this?” And to your point, it's like, “Oh, I need sandbox for this. I need sandbox for that. I need sandbox-” It's like, “Oh, I need it for every single thing.” And so basically what I, what I - and it sounds like a broken record, it's like you use a laptop every single day, right? And you are n of one. It's just you. But now imagine how And by the way, the laptop, the computer PC market, the PC market is about equal to the cloud market in total. So it's about 150, 180 billion a year. Something like that. It's about roughly the three cloud hyperscalers is about equal to like Apple, HP, Lenovo, whatever, It's a little bit less, but it's sort of like that. And now imagine And that's just like, so how big is the addressable market? What, how many people are there in the world now? What's the last data?Swyx [00:47:45]: Let's call it eight billion.Ivan [00:47:46]: Eight billion. And so let's say you can have two computer, like you have one personal and one business, whatever. Like so it's double that, right? and so that's 16 billion, right? How many agents are gonna be running in two years, in 10 years, in 100 years? Like And for every single task, they will need one of these. And so how big is that? That market is essentially quote unquote “infinite”. You will get to the point, and Dylan Patel was at the conference talking about, from SemiAnalysis, that talks usually about GPUs, was also talking about how CPUs will now be a bottleneck because it will be the constraint. You won't be able to grow, or we won't be able to have enough of these because there won't be enough CPUs to basically do.Swyx [00:48:23]: Yeah. Well, I actually had a really good podcast with Doug Oliphant, who, which was his president at SemiAnalysis, where they've basically been like, yeah, it's been a GPU shortage first, but then it's cascaded down to memory and now to CPUs.Ivan [00:48:35]: CPU, yeah.Swyx [00:48:35]: It-What's next? So networking. So, networking actually has been in shortage for a while if you're looking at, just GPU networking. But, yeah, it's really crazy the amount of computer use that's going on, yeah, cool. I, other questions are, just the one very big part is the open sourceness which you didn't have to do, your competitors don't do, like it's not, a lot of people are worried about keeping their projects open source because some competitor can just slot fork it. I don't know if there's any reflections on just being an open source company.Open Source, Trust, and Enterprise ProcurementIvan [00:49:15]: Yeah. There's a bunch. So we the original product that we did was open source.Swyx [00:49:19]: Yeah. CodeAnywhere.Ivan [00:49:20]: So doing that was actually very good for us. There's basically a saying of, What's the saying? Like, companies that are, that are doing really well, measure themselves against, free cashflow, that are kinda okay, it's EBITDA, then, it's, it goes all the way down.Swyx [00:49:36]: The worst is like GitHub stars.Ivan [00:49:37]: GitHub stars. GitHub stars are the worst, yeah. So you go all the way down to GitHub stars. And so our original one was GitHub stars. That's what we talked about, we're at the point we're talking about revenue, so we're we've gone up the stack on that. And so we started.Swyx [00:49:47]: No, profit.Ivan [00:49:48]: Yeah. We haven't, we're, we'll get there. We'll get there. But basically at that point we did stars and GitHub and it was useful, and the original variation that we did, it we split the core into its own repo and it was Apache 2.0, so very, permissive. And then we basically would bundl

【欢迎订阅】 每天早上5:30，准时更新。 【阅读原文】 标题：China Bans Meta 's Acquisition of Manus on National Security GroundsDecision reflects Beijing's broader attempts to protect China's AI know -how正文：China has banned Meta Platforms' acquisition of artificial-intelligence startup Manus on national security grounds and ordered that the $2.5 billion deal be unwound. China's National Development and Reform Commission, which has the authority to review foreign investments, said Monday that it has banned the acquisition and ordered it to be rescinded. “The transaction complied fully with applicable law,” a Meta representative said in an email statement. “We anticipate an appropriate resolution to the inquiry.”知识点：unwind v. /ˌʌnˈwaɪnd/to cancel or reverse a financial agreement, deal or arrangement. 撤销（交易）；解除（协议）e.g. Both sides agreed to unwind the partnership contract peacefully. 双方同意和平解除合作合约。获取外刊的完整原文以及精讲笔记，请关注微信公众号「早安英文」，回复“外刊”即可。更多有意思的英语干货等着你！ 【节目介绍】 《早安英文-每日外刊精读》，带你精读最新外刊，了解国际最热事件：分析语法结构，拆解长难句，最接地气的翻译，还有重点词汇讲解。 所有选题均来自于《经济学人》《纽约时报》《华尔街日报》《华盛顿邮报》《大西洋月刊》《科学杂志》《国家地理》等国际一线外刊。 【适合谁听】 1、关注时事热点新闻，想要学习最新最潮流英文表达的英文学习者 2、任何想通过地道英文提高听、说、读、写能力的英文学习者 3、想快速掌握表达，有出国学习和旅游计划的英语爱好者 4、参加各类英语考试的应试者（如大学英语四六级、托福雅思、考研等） 【你将获得】 1、超过1000篇外刊精读课程，拓展丰富语言表达和文化背景 2、逐词、逐句精确讲解，系统掌握英语词汇、听力、阅读和语法 3、每期内附学习笔记，包含全文注释、长难句解析、疑难语法点等，帮助扫除阅读障碍。

Jianggan Li, Founder of Momentum Works, joins Jeremy Au to unpack the Trump Xi Beijing summit, the first US presidential visit to China since 2017. They decode the optics of Zhongnanhai Garden and the Temple of Heaven, Xi Jinping's Thucydides Trap reference, the 200 plane Boeing deal, and why the absence of major deliverables is itself a strategic win. The conversation dives deep into the AI chip war, why NVIDIA's market share in China collapsed from 95% to under 10%, how the US export ban accelerated Chinese semiconductor self-reliance, and DeepSeek's reported 50 billion RMB funding round with the founder personally contributing 20 billion. They examine why Jensen Huang was added to Trump's delegation last minute, Elon Musk's unique position with Tesla in China, how Chinese state subsidies flow through local governments, and why founders like the Manus team made costly domicile mistakes. For Southeast Asia founders, VCs, and operators in Singapore, Indonesia, Vietnam, Philippines, Thailand, and Malaysia, this episode reveals why both superpowers settled into managed competition rather than decisive split, and what it means for global supply chains, AI models, and capital flows in 2026. Watch, listen or read the full insight at https://www.bravesea.com/blog/trump-xi-summit Get transcripts, startup resources & community discussions at https://www.bravesea.com WhatsApp: https://whatsapp.com/channel/0029VakR55X6BIElUEvkN02e TikTok: https://www.tiktok.com/@jeremyau Instagram: https://www.instagram.com/jeremyauz Twitter X : https://x.com/jeremyau LinkedIn: https://www.linkedin.com/company/bravesea English: Spotify | YouTube | Apple Podcasts Bahasa Indonesia: Spotify | YouTube | Apple Podcasts Chinese: Spotify | YouTube | Apple Podcasts 00:00 Introduction 01:23 Why the Trump Xi summit was a strategic win 03:25 Key players and how China renamed Rubio 06:26 Xi's Thucydides Trap and the Athens Sparta lesson 09:11 Chinese self-media versus official narratives 12:10 Zhongnanhai Garden and Temple of Heaven optics 15:15 El Niño, food security and global risk 16:36 Boeing deal, Elon Musk and Tesla in China 19:04 Jensen Huang added last minute to the delegation 21:16 Why Chinese founders still domicile in Singapore 23:08 DeepSeek's 50 billion RMB funding anomaly 24:00 NVIDIA's China collapse and the backfired chip ban 26:32 DeepSeek and ByteDance: founder driven AI 29:34 How Chinese state subsidies actually work 32:17 DeepSeek's cost efficiency strategy 33:04 Future outlook: Xi's US visit and Taiwan

Som i en hollywoodfilm brager Muammar Gaddafi og hans sidste loyale støtter ud i ørkenen, på flugt fra oprørerne, efter byen Sirte falder: Gaddafi-regimets sidste bastion. Men fra himlen vælter det snart ned med NATO-bomber. Og fra jorden regner det med kugler, ud over bilkonvojen. Det her er historien om en af verdenshistoriens mest forhadte mennesker. Og vi starter serien med hans vilde og voldsomme død. Fortæller: Nicholas Durup Thomsen. Manus og tilrettelæggelse: Nicholas Durup Thomsen & Anton Færch. Lyddesign: Anton Færch. Soundtrack: Anton Færch. Redaktør: Emil Rothcstein-Christensen. DR Redaktør: Anders Stegger. Produceret for P3 af MonoMono.

Under våren 2026 skakas det norska samhället av avslöjanden kring täta kopplingar mellan den norska makteliten och den dömde sexualförbrytaren Jeffrey Epstein. Toppolitiker, diplomater och till och med kungahuset är inblandade. Det har beskrivits som en kollaps för den norska självbilden. Men varför har just den norska eliten orsakat så många Epsteinskandaler? Programledare: Sabina Marmullakaj. Med Karin Eriksson, Nordenreporter på DN. Manus och producent: Elinor Ahlborn.

What actually keeps customers coming back? In this episode of Limited Supply, Nik sits down with retention expert Joseph Siegel to break down the systems behind high-retention ecommerce brands. From his time leading growth and retention at Feastables to building retention programs for some of the fastest-growing supplement brands in the world, Joseph shares how modern retention goes far beyond email marketing. They dive into onboarding flows, product inserts, gifting strategies, subscriber psychology, and why the best brands obsess over customer experience at every touchpoint. They also explore how AI is changing ecommerce operations from CRO systems and generative email workflows to building smarter customer insights with tools like Claude, Manus, Fireflies, and OpenAI voice models. If you run a subscription brand, consumable product, or ecommerce company focused on long-term growth, this episode is packed with actionable retention strategies. --- What's Instant? It's the secret weapon to triple your email revenue with AI-powered flows and campaigns. Instead of sending the same cart reminders to everyone, Instant gives every shopper a personalized email experience: Copy, products, and offers that adapt to your shopper's behavior and purchase history in real time. Emails sent at the exact moment each shopper is most likely to buy. 11+ abandonment flows and smart multi-step campaigns live in minutes. Built for DTC marketers. Made for revenue growth. See why brands are replacing their ESP with Instant: ⁠⁠⁠instant.one/sharma⁠⁠⁠. --- Want more DTC advice? Check out the⁠⁠⁠ Limited Supply YouTube page⁠⁠⁠ for more insider tips. And if you're looking for an instant stream of on-demand DTC gold, check out the⁠⁠⁠⁠ Limited Supply Slack Channel⁠⁠⁠⁠ for Nik's most unfiltered, uncensored thoughts. Check out the Nik's ⁠⁠⁠⁠DTC newsletter⁠⁠⁠⁠ Follow Nik on Twitter:⁠⁠⁠⁠ https://www.twitter.com/mrsharma⁠⁠

Use code TURFNERDS for 5% off orders $600 and up at Magna-Matic! Use discount code for TURFNERDS10 for 10% off at Strauss, valid starting April 29 through May 31 Use code NERDS to save 10% on Spencer Products! Chad Manus works full-time in transportation and logistics, has six kids, and still manages to service 40 lawn care clients out of Headland, Alabama on afternoons and Saturday mornings only. In this Turf Nerds on Turf's Up Radio episode, Chad breaks down how he grew from 10 clients in year one to 40 in year three, why his second season nearly broke him, and the Facebook ad strategy he used to build killer route density without wasting a dollar. If you've ever wondered whether you can build a real lawn care business without quitting your day job, this one's for you. Use code TURFNERDS for 5% off orders $600 and up at Magna-Matic! Use discount code for TURFNERDS10 for 10% off at Strauss, valid starting April 29 through May 31 Use code NERDS to save 10% on Spencer Products! Tap Here for Turf Nerds Merch!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Look! We Have A Website!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Don't forget to check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Green Frog Web Design⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and tell them the Turf Nerds sent you. Or Greg will scalp your lawn! Use promo code TURFNERDS for 50% off Equip Expo 2026 registration! Shoot us an email! Evan@TurfNerdsPod.com ⁠⁠Instagram⁠⁠ ⁠⁠Facebook⁠⁠ ⁠⁠TikTok⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe on YouTube: ⁠⁠⁠https://www.youtube.com/@TurfNerdsPodcast?sub_confirmation=1⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠#LawnCare #LawnMaintenance #Mowing #MowingGrass #LawnCareBusiness #Toro #ToroMultiforce #CubCadet #BibleStudy #Bible #Christian #Business #Entrepreneurship #Comedy #2024 #Marketing #Advertising #TipsAndTricks #Tips #Success #Yakta #YaktaMowers #YaktaOutdoor #Spring #SpringRush #FYP #Mower #NewMower #UsedMower #RouteDensity #EquipExpo #EquipExpo2024 #Echo #Stihl #RedMax #Shindaiwa #StringTrimmer #WeedWhip #GreenFrogWebDesign #WebDesign #EzraMcCarthy #Aerator #Aeration #ZAerate #Bobcat #BobcatMowers #Husqvarna #HusqvarnaGroup #HYGREENTOOL #GOMOW #ThunderLightingSupply #ChristmasLights #Christmas #Trump #DonaldTrump #PresidentTrump #ElectionDay #EZDumper #DumpInsert #StempkyNursery #Mulch #MulchInstallation #TurfNerds #Newsmax #NewsmaxTV #CarlHigbie #CharlieKirk

AI agents only work when you build them with a clear framework. This episode gives founders, CMOs and business owners the exact process, tested over six months, for shipping agents that actually do the job.Oliver walks through the Three Ps Framework: Purpose, Product, Prompt. Define the purpose of the agent. Shape it into a product you could explain to a client. Write the prompt that briefs the platform. Skip any of the three and the agent breaks.He then shows how to set up a Claude project as the brain of every build, so every tool you reach for stays anchored to the same source of truth. Claude Code becomes the consultant briefing every other platform you use.From there, Oliver breaks down which platform fits which job. OpenClaw for automation and scale, the operational backbone for admin and deep tasks. Manus for creative output, content and scheduling. Lovable for shipping platforms and apps you can charge for from day one. He also covers how to stack all three into one workflow, and which combinations actually work.Oliver closes with how to start small, ship fast and scale the build once the agent is doing its job. The founders winning with AI agents are not the ones running the biggest stacks. They are the ones with the clearest process.If you have been circling AI agents for months without shipping anything, this episode is the build process that gets you moving.Key topics covered: The Three Ps Framework for building AI agents How to set up a Claude project as the brain of every build How to brief Claude Code like a consultant When to use OpenClaw, Manus or Lovable How to stack all three into one workflow How to ship a platform you can monetise from day one How to start small and scale the build once it works Key takeaway: Founders who ship working AI agents anchor every build to a Claude project, brief Claude Code like a consultant and pick the platform that fits the job.Sponsored by Incard — Sponsored by Incard. Sign up now. All your finances. One platform.More Value:Follow on YouTube for deep-dives & video episodes: www.youtube.com/@TheUnlockOliverBruceNeed a 1-2-1 with Oliver or want to be on the show, visit: www.oliverbruce.co.ukRead more information on key points in Oliver's newsletter: The Brucey Bonus newsletterFollow The Unlock & Oliver's socials:LinkedIn | TikTok | YouTube | Instagram | Apple Podcast | Spotify podcast

Join use at the STR AI Summit — June 23-24 at the Freedom Factory in Beverly, MA. 100 seats only strsecrets.com/aisummitMike Sjogren spent over $5,000 in API credits in two months learning AI the hard way. And he wants to make sure you don't have to.In this Portfolio Clinic training, Mike breaks down the top 10 AI mistakes that cost him real money — from not understanding context windows to memory file bloat to giving an agent 15 tasks at once and wondering why nothing got done. He then walks through exactly how STR operators should be using AI right now across three buckets: getting more properties, getting more bookings, and getting more time back.He also shows how he rebuilt his Florida direct booking website in under a day for under $200 using Manus, how his AI agent scrapes top boutique hotel social media content overnight and delivers a morning brief, and why the goal is never to build your own software — it's to use AI as a bolt-on to everything you already have.DM Mike on Instagram @mike.sjogren and comment PROMPT to get the free PDF of all the prompts he used to build his direct booking website.STR AI Summit — June 23-24 at the Freedom Factory in Beverly, MA. 100 seats only.strsecrets.com/aisummitFree 6-step course for scaling STR operators: https://level.strsecrets.com/pc-bookSTR Secrets FB group: https://www.facebook.com/groups/STRentalsecretsTimestamps:0:00 - Why Mike Is Doing This Training (And How Much It Cost Him)2:15 - Mistake #1: Not Understanding Context Windows ($6 Per Message)5:30 - Mistake #2: Memory File Bloat — Why AI Gets Dumber Over Time7:45 - Mistake #3: Using Your Most Expensive Model for Everything10:00 - Mistake #4: Broken Cron Jobs — How to Schedule Tasks That Actually Run13:00 - Mistake #5: Treating AI Like an Employee Who Can Handle 15 Things at Once16:30 - Mistake #6: Not QC-ing the Output18:00 - Mistake #7: Trying to Build Your Own PMS or Pricing Tool20:30 - The 3 STR Buckets: More Properties, More Bookings, More Time23:00 - How to Use AI to Automate Your Entire Prospecting Pipeline27:00 - How to Use AI to Get More Bookings Right Now30:00 - How to Rebuild Your Direct Booking Website With AI for Under $20036:00 - How Mike's Overnight Agent Scrapes Top Hotel Content Every Night39:00 - The 10 Rules for Using AI Without Burning Your Budget42:00 - How to Motivate Your Team to Use AI Without Fear46:00 - Where to Start If You're Brand New to AI48:00 - STR AI Summit: June 23-24 at the Freedom Factory

Join use at the STR AI Summit — June 23-24 at the Freedom Factory in Beverly, MA. 100 seats only strsecrets.com/aisummitMike Sjogren spent over $5,000 in API credits in two months learning AI the hard way. And he wants to make sure you don't have to.In this Portfolio Clinic training, Mike breaks down the top 10 AI mistakes that cost him real money — from not understanding context windows to memory file bloat to giving an agent 15 tasks at once and wondering why nothing got done. He then walks through exactly how STR operators should be using AI right now across three buckets: getting more properties, getting more bookings, and getting more time back.He also shows how he rebuilt his Florida direct booking website in under a day for under $200 using Manus, how his AI agent scrapes top boutique hotel social media content overnight and delivers a morning brief, and why the goal is never to build your own software — it's to use AI as a bolt-on to everything you already have.DM Mike on Instagram @mike.sjogren and comment PROMPT to get the free PDF of all the prompts he used to build his direct booking website.STR AI Summit — June 23-24 at the Freedom Factory in Beverly, MA. 100 seats only.strsecrets.com/aisummitFree 6-step course for scaling STR operators: https://level.strsecrets.com/pc-bookSTR Secrets FB group: https://www.facebook.com/groups/STRentalsecretsTimestamps:0:00 - Why Mike Is Doing This Training (And How Much It Cost Him)2:15 - Mistake #1: Not Understanding Context Windows ($6 Per Message)5:30 - Mistake #2: Memory File Bloat — Why AI Gets Dumber Over Time7:45 - Mistake #3: Using Your Most Expensive Model for Everything10:00 - Mistake #4: Broken Cron Jobs — How to Schedule Tasks That Actually Run13:00 - Mistake #5: Treating AI Like an Employee Who Can Handle 15 Things at Once16:30 - Mistake #6: Not QC-ing the Output18:00 - Mistake #7: Trying to Build Your Own PMS or Pricing Tool20:30 - The 3 STR Buckets: More Properties, More Bookings, More Time23:00 - How to Use AI to Automate Your Entire Prospecting Pipeline27:00 - How to Use AI to Get More Bookings Right Now30:00 - How to Rebuild Your Direct Booking Website With AI for Under $20036:00 - How Mike's Overnight Agent Scrapes Top Hotel Content Every Night39:00 - The 10 Rules for Using AI Without Burning Your Budget42:00 - How to Motivate Your Team to Use AI Without Fear46:00 - Where to Start If You're Brand New to AI48:00 - STR AI Summit: June 23-24 at the Freedom Factory

El humorista y comunicador andaluz Manu Sánchez, una de las voces más reconocibles del entretenimiento en Andalucía, trasnocha hoy con Mara Torres en 'El Faro' para hacer un repaso a su trayectoria, que va desde llenar teatros con sus monólogos y espectáculos hasta participar en todo tipo de formatos televisivos y radiofónicos que le han valido el cariño del público, especialmente el de 'Canal Sur'. Durante años, Manu Sánchez ha combinado humor, compromiso social y amor por su tierra, Andalucía, convirtiéndose en una figura clave del panorama cultural del sur.

En su sección de los lunes, Antón Meana nos ha hablado de primeras veces en el deporte. También hemos conversado con nuestro compañero de la SER Nico Castellanos, que no solo estuvo sobre el terreno durante el terremoto de Lorca del que hoy, 11 de mayo, se cumplen 15 años, sino que ha estado al filo de la noticia en algunos de los principales escenarios de conflicto, crisis humanitarias y desastres naturales del mundo: el Sáhara, el tsunami de Japón, Sudán, Lampedusa, Gaza o Ucrania. Además, nuestro Gatopardo esta noche ha sido el cómico y presentador Manu Sánchez.

En este episodio me siento a charlar con Manu Sáez y Ángel Jané (Horum art), dos fotógrafos de calle que viven la fotografía con una naturalidad brutal. Hablamos de sus canales de YouTube, de cómo se conocieron, de sus caminatas por Barcelona, de street photography, de cámaras Fuji, de viajes fotográficos a Marruecos y de esa parte tan bonita de salir a la calle sin saber qué foto te vas a encontrar.➡️CANAL YOUTUBE ÁNGEL JANÉ: https://www.youtube.com/@HorumArt➡️CANAL YOUTUBE MANU SÁEZ: https://www.youtube.com/@Manu_Saez_CampillosUna charla sin guion, con mucho cacharreo, humor, cerveza imaginaria, Fuji X100VI, fotografía de calle, bloqueos creativos, comunidad fotográfica y pasión pura por crear.Si te gusta la fotografía street, los vídeos espontáneos, las cámaras bonitas y las conversaciones entre fotógrafos que disfrutan de verdad, este podcast te va a encantar**COMPRA EN FOTOK desde este enlace y pon el cupón GABELLIFTK en tu carrito de la compra para llevarte un regalo.WEB FOTOK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://fotok.es/?aff=y206⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠___________________WEBS: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.rubengabelli.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://fotografodecomida.es⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YOUTUBE: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://cutt.ly/ft3QEHF ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠PATREON: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/RubenGabelli ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠INSTAGRAM: @rubengabelli

本期嘉宾：彭林、十天、森森、蓝白、恺伦本期节目的主要内容有：· 00:01:08 -- 苹果内置摄像头 AirPods 或 9 月发布· 00:09:18 -- 苹果因 AI Siri 延迟赔偿 2.5 亿美元，每台 iPhone 最高可获赔 95 美元· 00:14:38 -- 三星宣布在中国大陆停售所有家电产品· 00:26:16 -- 一加、realme 合并· 00:34:53 -- Valve 新一代 Steam 手柄宣布发售· 00:52:43 -- OpenAI 发布 GPT-5.5 Instant、扩容广告平台和实时语音助手· 01:09:15 -- 豆包付费订阅价格曝光，官方回应：始终提供免费服务· 01:24:46 -- 阿里发布「数字员工」QoderWake· 01:31:13 -- 阿里巴巴发布视频生成模型 HappyHorse 1.0· 01:37:11 -- 宇树 G1 人形机器人在韩国佛门「受戒」：法名「迦悲」· 01:46:23 -- 时代的眼泪：开播 24 年的星空卫视 5 月 8 日起暂停卫星传输服务· 01:57:32 -- 中方禁止外资收购 Manus 项目· 02:19:39 -- 闲聊环节我们的二手线下店位置在深圳·坂田北·吉华路·展誉公馆，离地铁站很近目前已经开业了，试营业期间活动也走起来了，具体可以听播客，感谢大家的支持~还有众多观众朋友的热心提问~每周五晚 8 点，爱否直播间，我们一起开心聊天

Are you overwhelmed running deals, managing investors, and juggling life? You're not alone — and you're probably doing it wrong. In this episode of The Vinney & Beau Show, Vinney Chopra and Beau Eckstein get raw and real about what it actually takes to close big commercial real estate and hospitality deals when everything is pulling at you at once.     From Vinney raising nearly $10M across three hotel deals back-to-back, to Beau breaking down why a $5M SBA loan is sometimes easier than a $250K one — this episode is packed with mindset shifts, business systems, and tax strategies that every high-net-worth investor and syndicator needs to hear.    

十年前的三月，那是人类最后一次战胜AI。如今，AI领域发生着剧烈变化，从 GPT最新图像模型展现出惊人的真实理解能力，到AI公司Manus收购案引发的监管风波，再到AI短剧、AI游戏对传统行业的碾压式替代，AI革命已进入不可逆阶段。AI不仅在内容生产上全面取代人力，甚至企业开始用AI“蒸馏员工”，科技巨头批量裁员。与此同时，中美在AI领域形成两极博弈，算力、算法、监管规则重新划分边界。在AI这场海啸下的我们，应该何去何从？您请听庄明浩和划水怪一一道来。更多精彩内容，欢迎收听本期节目~主播 / 相征嘉宾 / 庄明浩音频后期 / 陆凯BBBBUDDHA音频上传 / 恬恬-本节目由深夜谈谈 Midnight Network出品 -Timeline:00:02:45 Image 2断档式领先00:11:10 年化收入1亿美金的公司之一00:23:00 人家商业公司就是为了挣钱00:36:10 滴滴非要去上市00:49:19 一次扔爆炸瓶，一次枪击01:18:46 处处受限制01:22:58 中美科技博弈01:33:51 AI音乐的发展01:37:57 阿尔法狗战胜李世石已经十年了01:46:03 AI能操控游戏么？01:47:35 Fun. - Carry On藏式金刚断烦恼，紫檀咒珠守心安。二十八宿催红鸾，甲子莲蓬伴流年。大内上新四款手串，愿你遇事不慌，少些内耗，遇见真心，白首不离。微信搜索小程序“大内夜市”，把祝福戴在腕间，日子自有光亮。每年夏天，我们都相约在一个森林山谷共同接受阳光、音乐、快乐的洗礼，今年也不例外！7月23日-7月27日，五天四晚，“大内海贼团”正式起航！由船长·相征、航海士·Miya、狂厨·王涛、大剑士·杨凯、疗愈士·郭小寒、观测士·米地、回声·宋晓辉这七位主播领衔带队，快快加入七武海的伟大队伍吧！微信搜索小程序“大内夜市”，即可报名～（报名咨询请微信搜索：DNYS-midnightalks）-你还可以在这里找到我们：小红书：@深夜谈谈、@相征terry、 @miyaB站：@大内密谈midnightalks视频号&抖音：@深夜谈谈微博：@大内密谈微信公众号：大内密谈商务合作邮箱：biz@midnightalks.com加听众群：加深夜谈谈子微信（微信号:SYTT-midnightalks2）并回复【听众群】即可进群。

Steadfastness of Faith: The #1 Reason Real Estate Investors Quit Before the Breakthrough   What separates investors who build lasting wealth from those who restart over and over again? One word: steadfastness.   In this Abundance Thursdays episode, Vinney "Smile" Chopra and co-host Gualter Amarelo dive deep into Principle #27 from The Wealthy Gardener — and why unwavering faith in your underwriting, your operator, and your God-given vision is the most powerful wealth-building tool you'll ever use.   In this episode, you'll discover:  

Our 243rd episode with a summary and discussion of last week's big AI news!Recorded on 04/29/2026Hosted by Andrey Kurenkov and Jeremie HarrisFeel free to email us your questions and feedback at andreyvkurenkov@gmail.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:OpenAI released GPT-5.5 with strong coding-oriented improvements, a system card discussing chain-of-thought monitorability and misalignment testing, higher pricing than GPT-5.4, and notable quirks like a system-prompt warning about “goblins.”xAI launched Grok Voice Think Fast 1.0, claiming large benchmark leads for real-time voice agents and reporting major Starlink customer-support automation and sales conversion impact.DeepSeek open-sourced DeepSeek V4 (Pro and Flash) featuring MoE scaling and 1M-token context via hybrid/compressed attention changes, while Tencent released Hunyuan 3 preview with weaker benchmark performance; a new long-horizon agent benchmark (Clawmark) shows low task success rates.Major business, legal, and policy updates include Google's planned up-to-$40B investment and 5GW compute commitment to Anthropic, Meta's AWS Gravitron deal and China blocking Meta's Manus acquisition, a revamped OpenAI–Microsoft agreement, ongoing Musk–OpenAI trial developments, and new safety/security research on sabotage, document degradation under delegation, and bit-flip attacks.Timestamps:(00:00:10) Intro / Banter(00:02:00) News Preview(00:02:26) Response to listener comments(00:02:55) SponsorsTools & Apps(00:05:55) OpenAI Unveils Its New, More Powerful GPT-5.5 Model - The New York Times(00:23:33) xAI Launches grok-voice-think-fast-1.0: Topping τ-voice Bench at 67.3%, Outperforming Gemini, GPT Realtime, and More - MarkTechPost(00:29:00) Claude can now plug directly into Photoshop, Blender, and Ableton | The VergeProjects & Open Source(00:29:38) China's DeepSeek releases preview of long-awaited V4 model as AI race intensifies(00:47:05) Tencent Unveils Hy3 preview; Model Enhances Agent Capabilities and Real-World Usability - Tencent 腾讯(00:50:14) ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker AgentsApplications & Business(00:53:03) Google Plans to Invest Up to $40 Billion in Anthropic(00:56:26) Meta will use hundreds of thousands of AWS Graviton chips(00:59:51) China blocks Meta's $2 billion takeover of AI startup Manus(01:01:45) OpenAI shakes up partnership with Microsoft, capping revenue share payments(01:07:13) Elon Musk Testifies of AI Risk at Trial, Says OpenAI Tried to ‘Steal' a Charity - WSJ(01:11:50) Judge rejects DOJ bid to delay Anthropic appeal in Pentagon dispute(01:14:42) Google's Gemini can now run on a single air-gapped server — and vanish when you pull the plug(01:19:07) DeepMind's David Silver just raised $1.1B to build an AI that learns without human data | TechCrunchPolicy & Safety(01:22:47) Evaluating whether AI models would sabotage AI safety research(01:28:59) LLMs Corrupt Your Documents When You Delegate(01:32:50) Temporal Sparse Autoencoders: Leveraging the Sequential Nature of Language for Interpretability(01:39:53) Memorandum on Adversarial Distillation of American AI Models(01:41:41) Teen boys are dating their AI chatbots—and experts warn it could kill their careers | Fortune(01:43:57) Announcing the Anthropic Economic Index Survey(01:45:21) Scoop: CISA lacks access to Anthropic's MythosSynthetic Media & Art(01:48:03) Taylor Swift Files to Trademark Voice and Likeness to Protect Against AI MisuseResearch & Advancements(01:49:15) Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit FlipsSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

"Not a creative"?

Subscribe now to skip the ads and get all of our episodes.  King Charles paid his respects at AP HQ, but was put off by Danny's pet ferrets. In this week's news: Iran talks collapse as Trump weighs a blockade and strikes (1:56); the UAE leaves OPEC (7:45); Mali rebels and jihadists seize Kidal (16:49); Derek interviews Alex Thurston about Mali's escalating rebel offensive and the implications for the junta government (18:08); Israel kills civilians and expands evacuation zones in Lebanon (33:43) as the U.S. and Israel demand a Hezbollah disarmament plan from Lebanon (35:25); Israel adds an orange line to its Gaza map (37:08); Afghanistan and Pakistan exchange border fire (38:59); China blocks the sale of AI startup Manus to Meta (40:46); Sudan's Blue Nile faces a humanitarian crisis (44:23); King Charles visits the United States and addresses Congress (46:27); Trump and Putin discuss a Ukraine ceasefire (48:53), plus Ukraine accuses Israel of procuring stolen grain (48:53); and the United States charges Sinaloa Governor Ruben Rocha (52:18). Don't forget to download our latest miniseries Marx Prestige. All episodes out now! And paid subscribers will get access to the full interview with Alex Thurston. Learn more about your ad choices. Visit megaphone.fm/adchoices

King Charles paid his respects at AP HQ, but was put off by Danny's pet ferrets. In this week's news: Iran talks collapse as Trump weighs a blockade and strikes (1:56); the UAE leaves OPEC (7:45); Mali rebels and jihadists seize Kidal (16:49); Derek interviews Alex Thurston about Mali's escalating rebel offensive and the implications for the junta government (18:08); Israel kills civilians and expands evacuation zones in Lebanon (33:43) as the US and Israel demand a Hezbollah disarmament plan from Lebanon (35:25); Israel adds an orange line to its Gaza map (37:08); Afghanistan and Pakistan exchange border fire (38:59); China blocks the sale of AI startup Manus to Meta (40:46); Sudan's Blue Nile faces a humanitarian crisis (44:23); King Charles visits the United States and addresses Congress (46:27); Trump and Putin discuss a Ukraine ceasefire (48:53), plus Ukraine accuses Israel of procuring stolen grain (48:53); and the United States charges Sinaloa Governor Ruben Rocha (52:18).Don't forget to download our latest miniseries Marx Prestige. All episodes out now!Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

AGENDA: 00:00 $45B Floods into Anthropic from Google & Amazon 05:10 OpenAI Misses Growth Targets — Is This a Real Problem? 08:40 The Rise of AI Agents: Why Humans No Longer Pick Models 12:05 "Compute ≠ Revenue": The First Crack in the AI Business Model 20:30 China Blocks $2B Manus Deal — AI Cold War Escalates 34:10 Why Google May Be the Biggest Winner in AI Infrastructure 41:50 The Death of SaaS? Agents Replace Apps Like Jira & Canva 46:20 Thoma Bravo Hands Medallia to Creditors — $5B Wiped Out 52:10 The Collapse of Private Equity Exit Routes in VC  

試喝一個月，最愛這份【紅牛愛基】穩定感。低 GI 讓飯後不再想「登出」躺平；雙蛋白鎖住飽足感，讓你拿回零食抽屜的決定權。口感像豆漿般濃醇香，完全沒化學味！

Get ready for a high-impact conversation on the intersection of landscaping, technology, and innovation! In this episode of Roots of Success, Kevin Keim sits down with ACE Peer Group standouts Sterling West of Newport Avenue Landscaping and Sam Zale of Zale's Lawn and Landscape. Discover how these forward-thinking business owners are using AI, not just as a buzzword, but as a hands-on tool to streamline operations, overhaul tech stacks, and dramatically improve customer experience. From custom-built workflows to real-time insights that flag potential pitfalls, you'll hear concrete examples of how and why these trailblazers dove headfirst into AI. Tune in if you're looking to make technology work for you!  THE BIG IDEA:   AI unlocks operator efficiency  KEY MOMENTS:  [03:46] Starting with customer experience automation [07:04] Building Zale Central program [12:05] Automating scheduling and payments [14:02] Implementing project management insights [17:12] Building with Lovable and AI integration [20:41] Streamlining processes with SOPs [24:26] Building a tech stack with Manus [27:00] Using AI to optimize processes [32:45] Using AI to improve operations [34:59] Using AI to boost efficiency [38:04] Discussing project quality assurance  QUESTIONS WE ANSWER  What inspired the guests to initially explore the use of AI tools in their landscaping businesses?  How did implementing AI impact the customer experience for the companies featured?  What specific operational challenges led to the creation of custom software solutions within these organizations?  In what ways did the adoption of AI reduce or consolidate the number of platforms and tools previously used by these companies?  Can you describe some of the key processes or workflows that have been automated using AI in the businesses discussed?  What financial implications, such as cost savings, resulted from shifting to more AI-driven systems?  How did employees respond to new AI-enabled tools and what changes did it bring to their daily responsibilities?  What practical advice was given for companies interested in starting small with AI implementation?  How does leveraging AI agents support quality assurance and error reduction for landscaping companies?  What are some predictions about how AI might further transform client interactions and project management in the landscaping industry? 

Limited BONUS: First 1,000 builders get $1,000. Claim yours while supplies lasts.: https://startup-ideas-pod.link/hyperagent I sit down with Howie Liu, co-founder and CEO of Airtable, to talk about the agent economy and the launch of HyperAgent. We walk through Sequoia's charts on AI agent deployment, the economics of token-based work versus human labor, and why frontier agents have crossed a threshold that changes how companies get built. Howie then does a live show-and-tell of HyperAgent, including a custom "Greg Isenberg contrarian AI" skill he spins up in real time. This one is for anyone building a solopreneur business, operating a fleet of agents, or trying to figure out where to place their bet in the agent ecosystem Timestamps 00:00 – Intro 02:22 – Sequoia's AI agent deployment chart reaction 04:41 – Copilot vs Autopilot territory and the $1T+ opportunity 08:13 – Agent economics vs human labor costs 11:12 – Fastest enterprise adoption curve in history 14:48 – The agent command center and fleet of 20 agents 18:03 – What is HyperAgent? 19:43 – Live demo: hyperlocal real estate market reports 22:38 – HyperAgent as the founder, not just the developer 23:21 – Street View, Zillow redesigns, and visual tool power 24:15 – Command center view across a fleet of agents 25:48 – Skills as the key primitive for frontier agents 26:30 – Building the Greg Isenberg contrarian AI skill live 32:31 – HyperAgent vs Perplexity Computer, Manus, OpenClaw, Codex 34:52 – Reviewing writing skill 36:55 – The arbitrage of persistence 41:31 – Confidence milestones: first dollar, $10K/month 35:27 – Reviewing contrarian tweet drafts live 45:05 – Giving the agent feedback and building rubrics 50:15 – Connectors, OAuth, and building custom API skills 53:03 – How to get started with HyperAgent 01:01:54 – Credit giveaway for listeners 01:03:31 – Closing Thoughts Key Points Frontier agents have crossed a threshold in the last 4–5 months where they function as true autonomous coworkers, not just chat assistants. Reframe agent cost by value delivered: a $150 token spend for a board memo beats hours of human time, so anchor on opportunity cost. The real arbitrage is persistence: 99% of people quit after one shot, while daily practice for 30/60/90 days produces top 1% operators. Skills are the most important primitive in frontier agents, turning generally intelligent models into domain experts through playbooks. HyperAgent's differentiation is a low floor plus a high ceiling, with rubrics, LLM-as-judge evals, and fleet-wide observability for scaling. Aim for $100B companies with under 5 employees, built on fleets of always-on agents mapped to human job roles. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND HOWIE ON SOCIAL X/Twitter: https://x.com/howietl Hyperagent: https://www.hyperagent.com Airtable: https://www.airtable.com-

Episode 833: Neal and Toby dive into China's block of Meta's acquisition of AI startup Manus, citing national security concerns. Then, the Supreme Court hears arguments on whether ‘geofence' warrants violate the US Constitution's right to privacy, even when committing criminal acts. Next, the MAHA Moms march to the Supreme Court to protest the use of a pesticide used on oat and corn as they claim it causes cancer. Meanwhile, Toby looks into the trend of brides buying wedding dresses much closer to their wedding day because they're quickly losing weight thanks to GLP-1 drugs.  Learn more at https://www.windmillair.com/MBD Get tix for Morning Brew's live show! https://www.caveat.nyc/events/morning-brew-presents-business-island-4-30-2026  Subscribe to Morning Brew Daily for more of the news you need to start your day. Share the show with a friend, and leave us a review on your favorite podcast app. Listen to Morning Brew Daily Here:⁠ ⁠⁠https://www.swap.fm/l/mbd-note⁠⁠⁠  Watch Morning Brew Daily Here:⁠ ⁠⁠https://www.youtube.com/@MorningBrewDailyShow⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

This Week In Startups is made possible by:IM8 Health - IM8health.com/twistSentry - Sentry.io/twistDeel - Deel.com/twistPlaud - https://Plaud.ai/twistWhat's the technology story of the year? No, it's not Anthropic's Mythos model, nor any other AI model. Upcoming IPOs? Wrong again. Jason thinks it's China's government's decision to block Meta's acquisition of Manus. The multi-billion-dollar deal was heralded as evidence that AI companies founded in China could sidestep onerous government meddling by moving their operations to Singapore. That loophole now appears closed.Jason and Lon then dug into the newly-reforged OpenAI-Microsoft partnership. The two companies have had a mutually beneficial, if fractious, operating relationship to date; that they had to rework their agreement is not a shock.Then, your hosts watched and digested a video from China purportedly showing a self-driving car hitting a child at speed. What would happen in the United States if such a tragedy struck? And is that fait accompli?Closing the show, Jason and Lon reacted to the latest Russell Brand implosion, discussed Lon's new favorite show ‘Criminal Record,' and shared recommended foot pedals (for AI dictation) and headphones for the road warriors tuning in.Key Links: OpenAI and MicrosoftOpenAI's announcement of its new Microsoft dealMicrosoft's announcement of its new OpenAI dealOpenAI announces its deal with AWSNews that Microsoft was considering legal action against OpenAIMicrosoft-OpenAI negotiations late 2025 edition, and terms announced in early 2026Amazon announces that OpenAI models are coming to AWSTimestamps:0:00 Show starts1:24 OpenAI and Microsoft have a new deal3:22 Why would Microsoft cede exclusive access to OpenAI models?5:36 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at https://Plaud.ai/twist and use code TWIST for 10% off!8:09 Why Jason thinks Microsoft and Apple should work together on AI9:45 China will block the Meta-Manus deal12:12 Deel - Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit https://deel.com/twist to learn more.12:23 Golden Shares and what they provide14:57 How do you unravel a multi-billion-dollar deal?22:08 Sentry - New users can get $240 in free credits when they go to https://sentry.io/twist and use the code TWIST24:42 The Huawei ADC crash29:49 What happens when something similar happens in the United States?31:55 IM8 Health: Start feeling like your best self every day. Go to https://IM8health.com/twist and use the code TWiST to get a free welcome kit, five free travel sachets, and 10% off your order.36:15 Russell Brand's public humiliation41:22 Don't trust palm reading!43:59 Lon's Off Duty streaming pick: Criminal Record46:25 Jason's Pick: Which foot pedal for AI dictation is right for you?48:43 Jason's Pick: In the market for new headphones?Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisCheck out all our partner offers: https://partners.launch.co/Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.com

China blocked Meta's $2bn acquisition of Manus, an artificial-intelligence startup, ordering both firms to cancel the transaction. Hosted on Acast. See acast.com/privacy for more information.

Get the most out of AI with our free AI ROI Scorecard: https://clickhubspot.com/epkj Ep. 421 What if your team burned through your entire AI budget in just six months? Kipp and Kieran dive into the wild world of “token maxxing”—the new Silicon Valley trend of spending as much as possible on AI tokens without clear outcomes. Learn more on why AI token usage is skyrocketing, the difference between “token maxxing” and “outcome maxxing,” and powerful frameworks every marketing leader can use to turn AI spend into real business growth. Mentions Nvidia https://www.nvidia.com/en-us/ All In Podcast https://www.youtube.com/watch?v=gwW8GKwHB3I Claude https://claude.ai/ Perplexity https://www.perplexity.ai/ Manus https://manus.im/ Gemini https://gemini.google.com/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by Hubspot Media // Produced by Darren Clarke.

The number of countries cutting energy taxes in response to the Iran war has doubled over the past month, and China blocked Meta's $2bn purchase of the AI group Manus. Plus, big private equity backers have raised concerns that some firms may be waving through controversial deals. Mentioned in this podcast:Energy tax cuts spread across 39 economies as prices jumpChina blocks Meta's $2bn purchase of AI group ManusPrivate equity backers raise new conflict concerns over sweetheart dealsNote: The FT does not use generative AI to voice its podcasts Today's FT News Briefing was hosted and edited by Marc Filippino, and produced by Saffeya Ahmed, Fiona Symon, and Sonja Hutson. Our show was mixed by Sam Giovinco. Additional help from Gavin Kallmann, Michael Lello and David da Silva. Our executive producer is Topher Forhecz. Cheryl Brumley is the FT's Global Head of Audio. The show's theme music is by Metaphor Music.Read a transcript of this episode on FT.com Hosted on Acast. See acast.com/privacy for more information.

(April 28, 2026) Amy King and Neil Saavedra join Bill for Handel on the News. Torrence man charged with attempt to assassinate President Trump. Iran offers to reopen Strait of Hormuz if US lifts blockade. China blocks Meta’s acquisition of Chinese-founded AI startup Manus.See omnystudio.com/listener for privacy information.

Plus: China bans Meta's acquisition of AI startup Manus. And a court in Taiwan hands down prison sentences for stealing TSMC trade secrets. Danny Lewis hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

China blocked Meta's $2B Manus acquisition and ordered both sides to unwind the deal, closing the "Singapore washing" loophole for Chinese AI startups. OpenAI is developing smartphone chips with Qualcomm and MediaTek, Google controls ~25% of global AI compute, and SaaS pricing shifts to usage-based. China blocks Meta's $2B Manus acquisition, after reviewing whether it violated investment rules, and tells both to cancel it; Manus moved to Singapore in 2025 (FT) Kuo: OpenAI is working with MediaTek and Qualcomm to develop smartphone chips, with Luxshare handling the system co-design; mass production is expected in 2028 (Ming-Chi Kuo) Epoch AI: Google controls ~25% of global AI compute, with ~3.8M TPUs and 1.3M GPUs; Google Cloud CEO Thomas Kurian says demand and revenue justify the spend (FT) Analysis: as of late 2025, 79 of 500 tracked software companies including HubSpot, Adobe, and Salesforce adopted usage-based AI fees, more than doubling on 2024 (The Information) Anthropic details Project Deal, a marketplace experiment where Claude models bought, sold, and negotiated personal belongings on behalf of Anthropic employees (Anthropic) Learn more about your ad choices. Visit megaphone.fm/adchoices

Plus: OpenAI and Microsoft reach a new deal, giving the startup more freedom. And China bans Meta's acquisition of AI startup Manus. Alex Ossola hosts. Sign up for WSJ's free What's News newsletter. An artificial-intelligence tool assisted in the making of this episode by creating summaries that were based on Wall Street Journal reporting and reviewed and adapted by an editor. Learn more about your ad choices. Visit megaphone.fm/adchoices