Podcasts about gpt

If you're constantly re-explaining your voice, your offers, or your standards to ChatGPT, this episode is your reset. I'm walking you step-by-step through how to build your own custom GPT so it thinks like you, edits like you, and follows your exact rules. No more starting from scratch. Just a smarter system that supports your content, protects your voice, and saves you serious time. RESOURCES MENTIONED NOTE: Some links below contain affiliate/referral links. It is a way for this site to earn advertising fees by advertising or linking to certain products and/or services. DISCOUNT: Code for 30+ free days of Podcast Audio Hosting through Libsyn: bossgirl RESOURCE: Need a Podcast Editor? Hire mine & tell him I referred you…The Podcast Man WORK WITH ME: Back Pocket VIP Coaching YOUTUBE CHANNEL: Subscribe >> The House of Sugar Creek MY BOOK: Snag a copy! Pillars & Purpose: How to Build a Business That Works for You RESOURCE: Contract Templates for your Business YOUTUBE CHANNEL: Subscribe to the BGC YouTube Channel and listen to my episodes via YouTube! MY 90-DAY UNDATED PLANNER: Buy it here! RESOURCE: Receive 20% off your first month or your first year with Dubsado RESOURCE: Receive 50% off your first full year with FloDesk (+ a 14-day free trial) LEAVE A MESSAGE: Click Here SEARCH BAR CONFESSIONS: Starts at 10:57 BUSINESS NUGGET: Starts at 13:59 RESOURCE: Try Manychat for 2 weeks for free RESOURCE: Check out Hilma products – $10 off for ya! RESOURCE: The Clarity Catch-Up Mini Workbook (FREEBIE) RESOURCE: The Clarity Code (reflection deck) RESOURCE: The Clarity Shot EPISODES YOU MIGHT ALSO ENJOY... EPISODE 558 – 153 FOLLOWERS IN A YEAR, 121 IN A DAY, WHAT CHANGED? EPISODE 549 – STOP WAITING ON THE ALGORITHM (IT'S NOT 2013 ANYMORE) EPISODE 509 – THE ONE ABOUT JOY VS HAPPINESS EPISODE 449 – MY SOCIAL EXPERIMENT EPISODE 409 – THE DARK SIDE OF ENTREPRENEURSHIP & CREATIVITY EPISODE 359 – THE IMPORTANCE OF CELEBRATING YOU EPISODE 309 –  WHY IT'S IMPERATIVE TO SET BOUNDARIES IN BUSINESS EPISODE 209 – THE KEY TO CONFIDENCE FOR CREATIVES EPISODE 159 – BLOG NO-NO'S (DON'T BE THAT BLOGGER) FIND TAYLOR ONLINE... Blog – The House of Sugar Creek Instagram – @taylorlbradford Facebook – bossgirlcreative Pinterest – thehouseofsugarcreek TikTok – @taylorlbradford YouTube – The House of Sugar Creek YouTube – Boss Girl Creative

In this episode, my guest is Pat Lapalapa, Sales Leader at Ray White AT Realty in Auckland, New Zealand. Pat speaks about how AI is helping leaders build stronger, more effective real estate teams. Pat shares how AI is being used to collapse time, improve coaching, and turn agent performance data into clear, actionable insights. The conversation explores practical leadership use cases, including custom GPT playbooks for auctions and appraisals, AI-powered performance storytelling, and internal knowledge systems that act as a second brain for teams. Pat emphasizes that AI should amplify human connection, not replace it, and explains why systems and consistency matter more than hustle in an AI-driven world. Guest: Pat Lapalapa Instagram: https://www.instagram.com/pat_lapalapa_group?igsh=YmlldThocXd6a2x1 Facebook: https://www.facebook.com/southaucklandspecialist   Website: https://www.raywhiteatrealty.co.nz/    Host: Rajeev Sajja Website: http://www.realestateaiflash.com    Facebook: https://www.facebook.com/rsajja  Instagram: http://www.instagram.com/rajeev_sajja  LinkedIn: http://www.linkedIn.com/in/rsajja    Resources:  Join our Instagram Real Estate AI Insiders Channel - https://ig.me/j/AbZCJG37DqBPPtxi/ Get 14 days Wispro Flow Pro Free Trial - https://ref.wisprflow.ai/rajeev-sajja  Subscribe to our weekly AI Newsletter: https://realestateai-flash.beehiiv.com/subscribe

DarkHorseEntrepreneur.com Why 82% of Parents Are Using ChatGPT Wrong (And How the Smart Ones Save 20 Hours Weekly) Episode Summary In this episode, Tracy Brinkmann dives deep into how parent entrepreneurs can leverage AI tools like ChatGPT and Claude to boost productivity and streamline their online entrepreneurship journey. Discover proven AI strategies designed specifically for busy parents juggling side hustles and family life. Learn how smart marketing strategies and digital marketing tips can help you make money online efficiently.   Tracy breaks down four core AI principles that transform this technology from a basic search tool into a powerful automation engine that works while your kids sleep. Whether you're new to AI or struggling with generic AI responses, this episode will change the way you approach AI for your digital products, marketing efforts, and overall business growth.   Stay tuned for actionable entrepreneur tips on strategic AI prompting, email strategy automation, and digital courses creation that help build passive income streams. This episode is essential listening for anyone focused on balancing side hustles with parenting, online business development, and effective email marketing tips.   Key Timestamps & Insights 00:00 - The 10 PM Reality Check 00:50 - Episode Overview 01:15 - The Uncomfortable Truth 02:25 - Principle #1: Context Is Everything 04:10 - Principle #2: Use AI's Memory Features Properly 06:05 - Principle #3: Master Chain-of-Thought Prompting 07:20 - Principle #4: Choose Tools Strategically, Not Emotionally 09:35 - The Bigger Picture 11:00 - Whiskered Wisdom Strategies Shared The Four Core AI Principles: Context-Rich Prompting Include who you are, what you're selling, target audience, constraints, and desired outcomes Transform questions into detailed briefings Give AI everything it needs to help you specifically Strategic Memory Usage Spend 15 minutes teaching AI about your business, style, and goals Save key processes, templates, and constraints Build compound knowledge instead of starting fresh each time Chain-of-Thought Implementation Break complex projects into logical sequential steps Refine each step before moving to the next Create compound results through systematic progression Strategic Tool Selection Identify your biggest bottleneck first Master one tool completely before adding others Match tools to specific workflow needs, not emotional appeal The Briefing Framework: Who you are (role/business type) What you're selling/offering Target audience specifics Budget/time constraints Desired outcome definition Success metrics Resources Mentioned ChatGPT-4 - For customer communications and general business tasks Anthropic's Claude - For content creation and detailed writing Perplexity AI - For market research and competitive analysis AI Escape Plan Newsletter - Weekly practical strategies at DarkHorseInsider.com Yale University Research - Referenced study on AI productivity gains Action Steps to Take Immediate Actions (Tonight): Pick one regular side hustle task (social media posts, competitor research, email drafting) Write a detailed brief including your role, audience, constraints, and desired outcome Test your old vague approach vs. the new briefing method Compare the quality and relevance of results This Week: Choose your biggest time bottleneck (research, content, or communication) Select the appropriate AI tool for that specific bottleneck Spend 15 minutes teaching that tool about your business context Set up memory features with your processes and preferences This Month: Implement chain-of-thought prompting for one complex project Build templates for your most common AI requests Track time saved and quality improvements Gradually automate additional workflow components Key Quotes "Your side hustle is competing against parents who've figured out how to make AI work 10 times harder than you have." "AI isn't a search engine – it's a machine you program with words." "The people making real money with AI aren't using more tools – they're using the right tools better." "The parents who learn to work with AI effectively won't just build better businesses – they'll reclaim time that seemed impossible to find." "The question isn't whether AI will change how work gets done. That's already happening. The question is whether you'll be among the people driving that change or getting left behind by it."   AI side hustles, entrepreneur AI tools, make money online with AI, AI productivity, ChatGPT for side hustles, AI automation, parent entrepreneur productivity, AI prompting strategies, ChatGPT, GPT-4, Large Language Model, OpenAI, Anthropic, Claude AI, AI tools, side hustle automation

Get our AI news cheat sheet: 20+ prompts for the latest models and tools https://clickhubspot.com/kps Episode 98: Is 2026 shaping up to be the year AI agents become indispensable—and outpace GPT-5? Hosts Matt Wolfe (https://x.com/mreflow)) and Joe Fier (linkedin.com/in/joefier) break down the explosion of new AI models, including Claude Sonnet 4.6, Gemini 3.1 Pro, and Grok 4.2, and explore how these tools are not only smarter but also significantly cheaper than previous state-of-the-art language models. This episode dives deep into the rise of agentic AI, the OpenClaw origin story, and how companies like Meta and ElevenLabs are racing to create integrated, emotionally-aware AI agents. Matt and Joe discuss the rapid democratization of AI, the impact of these advances on creativity and business operations, and the ongoing debate about slowing down AI before it accelerates beyond human control. Plus: practical demos, business tips, and a look at the hardware/software divide in global robotics. Check out The Next Wave YouTube Channel if you want to see Matt and Nathan on screen: https://lnk.to/thenextwavepd — Show Notes: (00:00) Next Wave Podcast: AI Insights (06:09) Anthropic Blocks, OpenAI Welcomes (10:35) ClaudeBot: AI Team Assistant (20:50) Meta Integrates Manus AI Ads (22:04) AI vs Manual Ad Management (29:55) New AI Models Released (31:54) AI Models Improve, Consumers Unchanged (41:09) Chatbots: Everyday and Advanced Uses (43:57) Mixture of Experts Explained (47:23) AI-Powered Product Photo Creator (56:58) Debating Internet Advancement (01:00:36) To Scale: Human Evolution (01:03:42) AI Debate: Polarized or Balanced? (01:13:16) AI Creativity Still Needs Humans (01:16:40) AI's Future in Entertainment (01:24:15) Experience Enhances AI Creativity (01:27:08) Robots Struggle with Nuance (01:30:27) US-China Collaboration for Smart Robots — Mentions: Joe Fier: https://www.instagram.com/joefier/ Seedance 2.0: https://www.seedance.com/ OpenClaw: https://openclaw.ai/ Manus: https://manus.im/ Nano Banana: https://nanobanana.com/ ElevenLabs: https://elevenlabs.io/ Perplexity: https://www.perplexity.ai/ Get the guide to build your own Custom GPT: https://clickhubspot.com/tnw — Check Out Matt's Stuff: • Future Tools - https://futuretools.beehiiv.com/ • Blog - https://www.mattwolfe.com/ • YouTube- https://www.youtube.com/@mreflow — Check Out Nathan's Stuff: Newsletter: https://news.lore.com/ Blog - https://lore.com/ The Next Wave is a HubSpot Original Podcast // Brought to you by Hubspot Media // Production by Darren Clarke // Editing by Ezra Bakker Trupiano

As Bob continues his LawNext on Location series – all recorded live in the San Francisco area at locations of each guest's choosing – he sits down with Pablo Arredondo at his home in Tiburon, a quaint Marin County town with a history stretching from Mexican land grants to naval outposts to a southern railway terminus. From Pablo's home office, the view looks out over Richardson Bay towards Sausalito and, if you look carefully, the Golden Gate Bridge can be seen in the distance. It is a setting that is entirely fitting for a conversation with someone who helped shape one of the more remarkable journeys in the annals of legal technology. Pablo was cofounder of Casetext, the once-scrappy startup that spent a decade iterating, pivoting and persisting before striking gold with CoCounsel, the first GPT-4-powered AI legal assistant, unveiled on the nationally televised Morning Joe show on March 1, 2023. Just four months later, Thomson Reuters acquired Casetext for $650 million in cash. Now, 2.5 years later, Pablo recently left TR, where he is, as he puts it, building a Lego Death Star with his daughter and finally paying attention to his well-being after 16 years of nonstop pursuit. In this wide-ranging conversation, Pablo reflects on the long road to CoCounsel – from a failed crowdsourcing experiment to CARA's brief analysis tool to the pivotal moment when Casetext signed a $20,000 innovation license with OpenAI and got early access to GPT-4, 10 weeks before ChatGPT's public launch. He describes the surreal experience of those first 48 hours after CoCounsel's debut, when he and cofounder Jake Heller identified 74 distinct legal use cases the tool could handle – any one of which, he says, "would have been a company in the old world." Pablo and Bob also dig into the bigger questions surrounding legal AI, including whether the field is advancing as fast as he expected; what the foundation models from Anthropic, OpenAI and Google mean for legal-specific AI companies such as Harvey; and why he believes reasoning models and agentic AI represent the next genuinely profound leap beyond GPT-4. Pablo also candidly reflects on the TR acquisition and his work while at TR, and he offers hints on what may lie ahead for him – at least once that Death Star model is done.  It is a conversation that is part memoir, part technology seminar and part meditation on what it means to have built something that changed a profession – and his life – all recorded with a sweeping, albeit cloudy, view of the majesty of San Francisco Bay.    Thank You To Our Sponsors This episode of LawNext is generously made possible by our sponsors. We appreciate their support and hope you will check them out.   Paradigm, home to the practice management platforms PracticePanther, Bill4Time, MerusCase and LollyLaw; the e-payments platform Headnote; and the legal accounting software TrustBooks. Briefpoint, eliminating routine discovery response and request drafting tasks so you can focus on drafting what matters (or just make it home for dinner). Legalweek, March 9-12, North Javits Center, New York City.   If you enjoy listening to LawNext, please leave us a review wherever you listen to podcasts.  

John Grange, Co-Founder of Move Venture Capital and CTO of OpsCompass, joins us from Omaha, Nebraska to unpack what AI is really changing — and what it's quietly breaking.From the collapse of digital trust in a world of deepfakes to the hype around AI agents and “GPT wrappers,” John brings the perspective of a technical founder turned investor. We dig into why value creation matters more than ever, why compliance doesn't equal security, and how AI is lowering the cost of building — and attacking — software systems.We also explore the harder questions:Are we headed toward an era where nobody believes what they see?Does AI amplify existing cybersecurity weaknesses?Is regulation the solution — or a competitive liability?And in a world where technology is commoditized, what's the real moat left for startups?This episode connects venture capital, cloud security, AI infrastructure, social media's psychological impact, and the future of trust into one central theme: AI is accelerating everything — including our mistakes.If you care about startups, cybersecurity, infrastructure, or the societal consequences of AI, this conversation goes well beyond the buzzwords.Want to learn more about securing your fleets, platforms, or mission critical systems? Contact us at FleetDefender.com.

Luke and John are going to be doing a show together, and Luke has some new material to workshop! (Yes--it does!) Our ancestors must have been dealing with different animals than the ones we currently have... NEXT: We are having Second Winter, right on schedule. If history is a teacher, we have at least 4 more thaws-and-refreezes before Real Spring. But, if history is a teacher, Luke still won't learn. LATER: WE HAVE SO MUCH TO TALK ABOUT. But let's talk about Artificial Intelligence again. Marcus Pittman suggestes that God was the Original Prompter, and making things with AI is a valid way to imitate God and make art. But, boy, that wasn't a popular take! FINALLY: John reads some AI-generated "jokes" from his comedy-writing GPT. (Yikes.) Contact the Comedian's Family by emailing nextdoor@johnbranyan.com

Michael Pouliot shares why vertical integration, disciplined buy boxes, and patience are key as multifamily heads into a major refinance cycle.In this episode of RealDealChat, Michael Pouliot—fourth-generation real estate entrepreneur and founder of Carbon—breaks down what's really happening in multifamily as the 2025–2027 maturity wall approaches.We discuss raising capital ahead of distress, why the downturn took longer than expected, and how today's opportunities are often coming from exhausted sponsors or lender takebacks. Michael explains why bringing property management in-house created millions in value, how repairing HVACs instead of replacing them changed asset economics, and why ownership mindset matters at every level of the organization.We also dive into:How a disciplined buy box saves thousands of underwriting hoursWhy “rates will be lower next year” is the most common investor lieHow Carbon uses AI and custom GPT agents inside property managementWhy location quality ultimately outperforms chasing high cap ratesWhat Michael learned from Wall Street's “two strike” cultureIf you're investing in multifamily—or preparing for the next phase of this cycle—this conversation will sharpen your framework.

Luke and John are going to be doing a show together, and Luke has some new material to workshop! (Yes--it does!) Our ancestors must have been dealing with different animals than the ones we currently have... NEXT: We are having Second Winter, right on schedule. If history is a teacher, we have at least 4 more thaws-and-refreezes before Real Spring. But, if history is a teacher, Luke still won't learn. LATER: WE HAVE SO MUCH TO TALK ABOUT. But let's talk about Artificial Intelligence again. Marcus Pittman suggestes that God was the Original Prompter, and making things with AI is a valid way to imitate God and make art. But, boy, that wasn't a popular take! FINALLY: John reads some AI-generated "jokes" from his comedy-writing GPT. (Yikes.) Contact the Comedian's Family by emailing nextdoor@johnbranyan.com

In this episode, Steve Fretzin and Sarah Persich discuss: Investing time instead of just spending it Fixing systems before layering on automation Building a connected tech stack that talks to itself Using AI strategically while managing risk   Key Takeaways: High-performing firms focus on building systems that multiply their time rather than endlessly grinding through tasks. Automation, documented workflows, and thoughtful process design “buy back” hours every week. The goal is long-term leverage, not short-term busyness. Most lawyers do not have an automation problem first; they have a clarity problem around roles, processes, and workflows. Undefined responsibilities and undocumented systems cause time leaks long before software can solve anything. Strong foundations make automation effective instead of chaotic. A solid CRM, practice management system, and an integration layer like Zapier allow firms to eliminate repetitive manual work. Open APIs and thoughtful integrations turn scattered tools into a coordinated system. When payments, contracts, intake, and follow-ups connect seamlessly, administrative drag disappears. AI becomes powerful when prompts are specific, voice is clearly defined, and systems are documented with tools like Loom and structured SOPs. Custom prompts or GPT setups help maintain brand consistency and save substantial time on drafting and research. At the same time, firms must weigh confidentiality, compliance, and ethical considerations before deploying AI at scale.   "I still stayed in my comfort zone for a little while, and I finally allowed myself to accept being uncomfortable… the big mistake was not going out on my own sooner, and staying in that safety zone and accepting the uncomfortability. And it's been really, really great ever since." —  Sarah Persich   Check out my new show, Be That Lawyer Coaches Corner, and get the strategies I use with my clients to win more business and love your career again.   Ready to go from good to GOAT in your legal marketing game? Don't miss PIMCON—where the brightest minds in professional services gather to share what really works. Lock in your spot now: https://www.pimcon.org/   Thank you to our Sponsor! Rankings.io: https://rankings.io/ Lawyer.com: https://www.lawyer.com/   Ready to grow your law practice without selling or chasing? Book your free 30-minute strategy session now—let's make this your breakout year: https://fretzin.com/   About Sarah Persich: Sarah Persich is a law firm automation strategist and operations expert known as “The Automation Lady.” With nearly a decade of experience inside a small law firm, she began her career as a legal assistant. She grew into the integrator role, serving as the operational second-in-command responsible for systems, technology, and process design. Her hands-on experience managing IT, workflows, and firm infrastructure gave her a front-row seat to the inefficiencies that quietly drain time and profitability from growing practices. Over time, she transitioned from internal operations leadership into marketing and automation strategy, helping firms move beyond reactive task management and toward intentional system design. Today, Sarah works with law firms to implement CRMs, streamline practice management systems, build automations, and document scalable processes. She helps attorneys distinguish between high-value strategic work and repetitive administrative tasks, enabling them to reclaim time, improve client experience, and build firms that operate with clarity instead of chaos.   Connect with Sarah Persich:  Website: https://www.automationlady.com/ LinkedIn: https://www.linkedin.com/in/sarahpersich/   Connect with Steve Fretzin: LinkedIn: Steve Fretzin Twitter: @stevefretzin Instagram: @fretzinsteve Facebook: Fretzin, Inc. Website: Fretzin.com Email: Steve@Fretzin.com Book: Legal Business Development Isn't Rocket Science and more! YouTube: Steve Fretzin Call Steve directly at 847-602-6911   Audio production by Turnkey Podcast Productions. You're the expert. Your podcast will prove it.

Luke and John are going to be doing a show together, and Luke has some new material to workshop! (Yes--it does!) Our ancestors must have been dealing with different animals than the ones we currently have... NEXT: We are having Second Winter, right on schedule. If history is a teacher, we have at least 4 more thaws-and-refreezes before Real Spring. But, if history is a teacher, Luke still won't learn. LATER: WE HAVE SO MUCH TO TALK ABOUT. But let's talk about Artificial Intelligence again. Marcus Pittman suggestes that God was the Original Prompter, and making things with AI is a valid way to imitate God and make art. But, boy, that wasn't a popular take! FINALLY: John reads some AI-generated "jokes" from his comedy-writing GPT. (Yikes.) Contact the Comedian's Family by emailing nextdoor@johnbranyan.com

Atenção (disclaimer): Os dados aqui apresentados representam minha opinião pessoal.Não são de forma alguma indicações de compra ou venda de ativos no mercado financeiro.https://www.infomoney.com.br/economia/volume-de-exportacao-de-carne-do-brasil-cresce-164-em-janeiro-diz-abrafrigo/https://www.infomoney.com.br/economia/previa-do-pib-ibc-br-dezembro-ano-2025/Shell faz sua proposta para Raízen, com cheque maior que Cosan e sem cisãohttps://pipelinevalor.globo.com/negocios/noticia/shell-faz-sua-proposta-para-raizen-com-cheque-maior-que-cosan-e-sem-cisao.ghtmlAcionistas da Simpar (SIMH3) reunidos em assembleia aprovam grupamento de ações https://financenews.com.br/2026/02/acionistas-da-simpar-simh3-reunidos-em-assembleia-aprovam-grupamento-de-acoes/JHSF (JHSF3) compra palácio histórico em Milão para lançar novo hotel Fasano; veja os detalheshttps://www.moneytimes.com.br/jhsf-jhsf3-compra-palacio-historico-em-milao-para-lancar-novo-hotel-fasano-veja-os-detalhes-igdl/Kepler Weber (KEPL3) prorroga novamente prazo para negociação com a GPT; entendahttps://www.moneytimes.com.br/kepler-weber-kepl3-prorroga-novamente-prazo-para-negociacao-com-a-gpt-entenda-lmrs/Previ e BNDEs vetam proposta de minoritário na Tupyhttps://braziljournal.com/previ-e-bndes-vetam-proposta-de-minoritario-na-tupy/Natura vende Avon Rússiahttps://financenews.com.br/2026/02/natura-vende-avon-russia/Vale atrai sócios para projeto de níquel no Canadáhttps://pipelinevalor.globo.com/negocios/noticia/vale-atrai-socios-para-projeto-de-niquel-no-canada.ghtmlAzul garante US$ 300 mi em investimentos da American, United e credoreshttps://www.infomoney.com.br/mercados/azul-garante-us-300-mi-em-investimentos-da-american-united-e-credores/Azul (AZUL53) conclui oferta de R$ 4,98 bilhões e homologa aumento de capitalhttps://www.moneytimes.com.br/azul-azul53-conclui-oferta-de-r-498-bilhoes-e-homologa-aumento-de-capital-lmrs/Fim do Chapter 11: Azul (AZUL53) anuncia saída de recuperação judicial nos EUAhttps://www.infomoney.com.br/mercados/fim-do-chapter-11-azul-azul4-anuncia-saida-de-recuperacao-judicial-nos-eua/Vazamento de reunião do caso Master causa indignação entre ministros do STFhttps://podcasts.apple.com/br/podcast/vazamento-de-reuni%C3%A3o-do-caso-master-causa-indigna%C3%A7%C3%A3o/id203963267?i=1000749654221&l=en-GBAfter Colbert says CBS blocked interview, FCC commissioner weighs in on 'equal time'https://podcasts.apple.com/br/podcast/after-colbert-says-cbs-blocked-interview-fcc-commissioner/id78304589?i=1000750233503&l=en-GBCan A.I. Already Do Your Job?https://podcasts.apple.com/br/podcast/can-a-i-already-do-your-job/id1200361736?i=1000750300296&l=en-GBWhere's the Beef? Inside the Fragile Cattle Markethttps://podcasts.apple.com/br/podcast/wheres-the-beef-inside-the-fragile-cattle-market/id1578096201?i=1000750221288&l=en-GBThe Startup Run by AI Agentshttps://podcasts.apple.com/br/podcast/the-startup-run-by-ai-agents/id1602541473?i=1000748281972&l=en-GBEpisode 1: Quality Assurancehttps://podcasts.apple.com/br/podcast/episode-1-quality-assurance/id1753117762?i=1000661647891&l=en-GB‘O que paira é um clima de muita desconfiança': os efeitos da operação de Moraeshttps://podcasts.apple.com/br/podcast/o-que-paira-%C3%A9-um-clima-de-muita-desconfian%C3%A7a-os/id203963267?i=1000750354829&l=en-GBDecisão de Moraes 'caiu muito mal dentro do Supremo'https://podcasts.apple.com/br/podcast/decis%C3%A3o-de-moraes-caiu-muito-mal-dentro-do-supremo/id203963267?i=1000750476949&l=en-GBU.S. cuts forces in Syria as its new government fights terror threathttps://podcasts.apple.com/br/podcast/u-s-cuts-forces-in-syria-as-its-new-government-fights/id78304589?i=1000750392553&l=en-GBA investigação sobre o vazamento de dados na Receita Federalhttps://podcasts.apple.com/br/podcast/a-investiga%C3%A7%C3%A3o-sobre-o-vazamento-de-dados-na/id1477406521?i=1000750592536&l=en-GB

Aujourd'hui, on plonge dans le code avec OpenAI qui vient de frapper un grand coup en lançant GPT-5.3-Codex-Spark.C'est une version allégée mais ultra-rapide de son modèle de génération de code.La vitesse pureD'abord, la promesse est simple : la vitesse pure.Ce nouveau modèle "Spark" est capable de générer du code 15 fois plus vite que le modèle standard GPT-5.3-Codex.On parle d'une réduction drastique de la latence, avec une réponse aux requêtes presque instantanée. Pour les développeurs, cela signifie la fin du mode "batch" où l'on envoyait une instruction avant de partir prendre un café en attendant le résultat.Ici, on entre dans l'ère de la collaboration en temps réel. Le modèle permet des micro-éditions ciblées et des ajustements d'interface en direct, et ce sans casser le flux de travail.Partenariat stratégique avec CerebrasEnsuite, il faut regarder sous le capot pour comprendre ce bond de performance.Cette prouesse est le fruit d'un partenariat stratégique avec le fabricant de puces Cerebras. Le modèle Spark tourne sur le "Wafer Scale Engine 3", un processeur géant de la taille d'une galette qui regroupe toutes les ressources de calcul sur une seule pièce de silicium.Concrètement, OpenAI a réduit l'échange de données entre le client et le serveur de 80 %. C'est cette architecture matérielle unique qui permet une interactivité fluide, autorisant même le développeur à interrompre ou à rediriger l'IA en plein milieu de sa tâche.Mais attention, et c'est mon troisième point, cette vitesse a un prix : celui de la précision et de la sécurité.Plus vite, mais plus faillibleOpenAI est très honnête sur ce point : sur les bancs d'essai mesurant les capacités d'ingénierie logicielle autonome, Spark est moins performant que son grand frère.Plus inquiétant encore pour les entreprises, il n'atteint pas les seuils de haute capacité en cybersécurité définis par OpenAI.En clair, Spark fait les choses beaucoup plus vite, mais il est plus susceptible de commettre des erreurs ou de générer des failles.On est donc sur un outil de prototypage rapide et d'itération légère, plutôt que sur un agent capable de gérer seul des infrastructures critiques.Le ZD Tech est sur toutes les plateformes de podcast ! Abonnez-vous !Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

AI agents differ from chatbots by pursuing autonomous goals through the ReACT loop rather than responding to turn-based prompts. While coding agents are currently the most reliable due to verifiable feedback loops, the market is expanding into desktop and browser automation via tools like Claude co-work and open claw. Links Notes and resources at ocdevel.com/mlg/mla-28 Try a walking desk - stay healthy & sharp while you learn & code Generate a podcast - use my voice to listen to any AI generated content you want Fundamental Definitions Agent vs. Chatbot: Chatbots are turn-based and human-driven. Agents receive objectives and dynamically direct their own processes. The ReACT Loop: Every modern agent uses the cycle: Thought -> Action -> Observation. This interleaved reasoning and tool usage allows agents to update plans and handle exceptions. Performance: Models using agentic loops with self-correction outperform stronger zero-shot models. GPT-3.5 with an agent loop scored 95.1% on HumanEval, while zero-shot GPT-4 scored 67.0%. The Agentic Spectrum Chat: No tools or autonomy. Chat + Tools: Human-driven web search or code execution. Workflows: LLMs used in predefined code paths. The human designs the flow, the AI adds intelligence at specific nodes. Agents: LLMs dynamically choose their own path and tools based on observations. Tool Categories and Market Players Developer Frameworks: Use LangGraph for complex, stateful graphs or CrewAI for role-based multi-agent delegation. OpenAI Agents SDK provides minimalist primitives (Handoffs, Sessions), while the Claude Agent SDK focuses on local computer interaction. Workflow Automation: n8n and Zapier provide low-code interfaces. These are stable for repeatable business tasks but limited by fixed paths and a lack of persistent memory between runs. Coding Agents: Claude Code, Cursor, and GitHub Copilot are the most advanced agents. They succeed because code provides an unambiguous feedback loop (pass/fail) for the ReACT cycle. Desktop and Browser Agents: Claude Cowork( (released Jan 2026) operates in isolated VMs to produce documents. ChatGPT Atlas is a Chromium-based browser with integrated agent capabilities for web tasks. Autonomous Agents: open claw is an open-source, local system with broad permissions across messaging, file systems, and hardware. While powerful, it carries high security risks, including 512 identified vulnerabilities and potential data exfiltration. Infrastructure and Standards MCP (Model Context Protocol): A universal standard for connecting agents to tools. It has 10,000+ servers and is used by Anthropic, OpenAI, and Google. Future Outlook: By 2028, multi-agent coordination will be the default architecture. Gartner predicts 38% of organizations will utilize AI agents as formal team members, and the developer role will transition primarily to objective specification and output evaluation.

Is your job safe if it happens on a screen?In the past few weeks, AI hasn't just improved, it has crossed a line. From writing production-ready code to building full applications autonomously, the shift is no longer theoretical. It's operational.The reality? AI is moving from assistant to operator, faster than most leaders are prepared for.In this episode, we break down what's really happening behind the headlines, why this moment feels eerily similar to early 2020, and what business leaders must do now to avoid being caught off guard.If you lead people, manage budgets, or make strategic decisions, this conversation is not optional.In this session, you'll discover:Why a viral article comparing AI to early COVID signals a bigger structural shiftHow Claude 4.6 and GPT 5.3 are moving from “helpful tool” to “finished output”The real reason AI labs targeted software engineers firstWhy “anything that can be done on a computer” is now vulnerableHow AI built a full multi-agent production pipeline in 48 hoursWhat Gemini 3.1 Pro's benchmark leap actually meansWhy Accenture now ties promotions to AI usageHow AI insurance is removing enterprise adoption barriersWhat the India AI Summit revealed about global governance tensionsWhy OpenAI's $100B raise is both brilliant and dangerously high-stakesHow robotics is quietly moving from factory floors into daily lifeWhy hybrid human-AI workflows are temporary by designThe coming economic disruption — and where opportunity hides inside itAbout Leveraging AI The Ultimate AI Course for Business People: https://multiplai.ai/ai-course/ YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/ Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/events If you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Tengo una peculiar forma de ser ambiciosa, una forma diferente que te permite vivir con mucha más calma y mucha más paz. Y eso es justo lo que te contaré aquí. Para entrar en nuestra lista de correo: https://espabilismo.com Si quieres montar un negocio de propiedades digitales como el nuestro, puedes pillar esta formación con GPT de regalo para crear tus propiedades por solo 20 pavos: https://espabilismo.com/propiedad

Tengo una peculiar forma de ser ambiciosa, una forma diferente que te permite vivir con mucha más calma y mucha más paz. Y eso es justo lo que te contaré aquí. Para entrar en nuestra lista de correo: https://espabilismo.com Si quieres montar un negocio de propiedades digitales como el nuestro, puedes pillar esta formación con GPT de regalo para crear tus propiedades por solo 20 pavos: https://espabilismo.com/propiedad

Listen to Full Audio at https://podcasts.apple.com/us/podcast/the-reasoning-throne-decoding-gemini-3-1-pros-77-arc/id1684415169?i=1000750806927

Sam Altman says superintelligence is two years away. Google just dropped Gemini 3.1 with benchmark scores that look like a full generation leap. The AI upgrade wars are here. But are we ready? Anthropic released Sonnet 4.6, OpenAI is rumored to be adding a spicy "Citron Mode" to GPT-5.3, and Sam and Dario Amodei refused to hold hands on stage like two kids at a school dance. Plus Hollywood is threatening to sue over Seedance 2.0, Google's new Lyria 3 AI music model is fine (we tested it with a McNugget rap), the OpenClaw founder got hired by OpenAI, and Kevin made Mr. Tibs delete himself to create a better version. He's fine with it. Probably. SUPERINTELLIGENCE IN TWO YEARS AND THEY CAN'T EVEN HOLD HANDS. WE'RE FINE. #ai #ainews #openai Come to our Discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/   // Show Links // Dario Amodei & Sam Altman Can't Hold Hands https://x.com/Yuchenj_UW/status/2024366483917459659?s=20 Sam Altman on SuperIntelligence https://x.com/clashreport/status/2024401234447520220?s=20 Google Gemini Pro 3.1 https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-1-pro/  New Photoshoot Update to Google Pompeii https://x.com/GoogleLabs/status/2024529795548102667?s=20 Claude Sonnet 4.6  https://www.anthropic.com/news/claude-sonnet-4-6 SVG Results from 4.5 to 4.6 https://x.com/scaling01/status/2023840565641556439?s=20 OpenAI's 'Citron Mode' Soon = Spicy Mode? https://x.com/btibor91/status/2024456593669231032?s=20 Netflix, Disney & Paramount All Threaten Seedance 2.0 https://variety.com/2026/tv/news/netflix-bytedance-immediate-litigation-seedance-ai-1236666084/ Seedance 2.0 Output Restrictions https://x.com/jamesjyu/status/2024305814950101034?s=20 Seedance 2.0 Dor Brothers $200m Movie https://x.com/thedorbrothers/status/2023460644905742577?s=20 Seedance 2.0 FERAL trailer https://www.youtube.com/watch?v=FmhiZ5OQBW0 Operation You Know What (Charles Curran Seedance 2.0) https://x.com/charliebcurran/status/2023611358160597060?s=20 Seedance Dark Cats:  https://x.com/pleometric/status/2023231194050052508?s=20 Trust Everything You See on Tiktok: https://www.tiktok.com/@trusteverythingyousee Google's Lyria 3 https://deepmind.google/models/lyria/ https://x.com/GoogleAI/status/2024154215182926027?s=20 OpenClaw Founder Joins OpenAI https://x.com/sama/status/2023150230905159801?s=20 HermitClaw: One Sandboxed Area, Learning  https://x.com/brendanh0gan/status/2023230513230614563?s=20 Contra: Agents Buy From Creatives (New Start-up) https://x.com/contraben/status/2024182864506761617?s=20 Unitree Robots Training For Chinese New Year Look Scary https://x.com/rohanpaul_ai/status/2024025865328488690?s=20 Chinese New Year Celebration Comparison: https://x.com/kimmonismus/status/2023388775511191699?s=20 AI Boston Dynamics Video? https://x.com/Rainmaker1973/status/2023791639601230195?s=20 Scary Robot Deployment https://x.com/ClaytonMorris/status/2024501307659407371/video/1 Riley Brown's OpenClaw to Blender https://x.com/rileybrown/status/2024334527217455270?s=20 Amazing Non-Seedance 2 AI Video Space Pirate Vibes https://x.com/ryanlightbourn/status/2023581484766875948?s=20  

Diane Sadowski-Joseph, Co-Founder of Clarinet, joined us on The Modern People Leader. We talked about why most AI adoption stalls at “talking the talk,” how to choose the right AI use cases using the “trifecta” and the Five Frictions framework, and how “click cutters” can unlock compounding gains by removing cognitive and workflow friction.----  Here's everything Diane referenced: https://modernpeopleleader.kit.com/fivefrictionsSponsor Links:

CoreStory is building code intelligence platforms that address the fundamental limitation of today's coding agents: their inability to navigate complex enterprise codebases. While foundation models excel at greenfield development, they fail at real-world engineering tasks in systems spanning millions of lines of code. CoreStory's context layer delivers a 44% improvement on SWE-bench, the industry's standard benchmark for measuring coding agent effectiveness on actual GitHub issues. In this episode of BUILDERS, I sat down with Anand Kulkarni, CEO of CoreStory, to explore how his team is enabling the shift to AI-native engineering and seeding the category of spec-driven development across Microsoft, GitHub, and Amazon. Topics Discussed: Building with GPT-3 API 18 months before ChatGPT went public Why even GPT-5 and Opus 4.5 struggle with enterprise codebases on SWE-bench The narrative shift required when selling AI pre- and post-ChatGPT CoreStory's 44% improvement in coding agent performance through context intelligence How "spec-driven development" got adopted by Microsoft, GitHub, and Amazon without formal analyst relations The parallel between JIRA monetizing Agile and CoreStory enabling AI-native engineering Three-channel distribution: direct enterprise, coding agent partnerships via MCP, and hyperscaler/GSI routes Why specs become the source of truth while code becomes disposable in the AI era GTM Lessons For B2B Founders: Match your narrative precision to technical depth: CoreStory deploys three distinct positioning strategies based on audience sophistication. For AI practitioners tracking benchmarks, they lead with "44% SWE-bench improvement"—a metric that immediately signals meaningful progress on the hardest problem in the space. For engineering leaders aware of AI tooling but not deep in the research, they focus on velocity gains and ROI metrics. For executives, they describe reverse-engineering codebases into machine-readable specs. The key insight: technical audiences dismiss vague value props, while non-technical audiences get lost in benchmark details. Map your positioning to how your audience measures success in their world. Seed category language through earned adoption, not manufactured consensus: Anand initially called their approach "requirements-driven development" before simplifying to "spec-driven development." Rather than pitching analysts, they used the term consistently in customer conversations, gave talks at GitHub Universe, and shipped demos showing the workflow. When customers naturally adopted the language and community leaders began using similar terminology independently, Microsoft and GitHub followed with their own implementations (like GitHub's SpecKit). The lesson: category language sticks when practitioners choose to use it because it clarifies their work, not because a vendor pushed it. Focus on customer adoption as proof of concept before seeking broader market validation. Position against emergent practices, not just incumbent products: CoreStory doesn't position against legacy code analysis tools—they position as the enabler of AI-native engineering, the discipline that will displace Agile. Anand's insight from watching JIRA's success: "People don't love JIRA. What they love is Agile as a way to move away from waterfall." CoreStory is betting that 10x velocity gains from AI-native practices will drive the same categorical shift. When you're early in a technology wave, attach to the practice change (how teams will work differently) rather than feature comparisons with existing tools. Movements create markets. Design channel strategy around customer problem awareness: CoreStory's three channels map to different stages of buyer sophistication. Direct enterprise comes from teams already deep in AI engineering who've hit the context limitation wall. Coding agent partnerships (via MCP integration with tools like Cognition and Factory) serve builders wanting better AI tooling who haven't diagnosed the context problem yet. Hyperscalers and GSIs distribute into modernization and maintenance projects where AI enablement is emerging as a requirement. Each channel serves a distinct buyer journey stage. Don't force one go-to-market motion—design multiple paths based on where different customer segments are in understanding the problem you solve. Navigate pre-legitimacy markets by hiding the breakthrough: Before ChatGPT, selling anything AI-driven faced immediate skepticism about whether it was "real" or just smoke and mirrors. Anand couldn't lead with AI without triggering disbelief. CoreStory focused on delivered outcomes—"here's what you'll be able to do"—with AI as the mechanism, not the message. Post-ChatGPT, the challenge flipped: everyone expects AI, but now the differentiation question becomes harder. If you're building on emerging technology before market consensus forms, deemphasize the technology until buyers have context to evaluate it. Once the market validates the technology category, shift to demonstrating your specific technical advantage within it. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

260220(2) [꼬리에 꼬리를 무는 뉴스] (1) 美서 챗GPT 불매운동 '큇GPT' 확산…왜? / (2) “인스타·유튜브는 '마약상'”… 청소년 SNS 중독 재판 시작 / (3) 성과급 ‘1인당 1억 3000만원'이 던지는 질문 - 허남설

This episode is a special crossover from The Next Wave podcast, hosted by Matt Wolfe and featuring a deep-dive conversation with marketing and business expert Joe Fier. The duo breaks down the five most interesting developments in AI from the past week, with a focus on SeedDance 2.0—an advanced video model from ByteDance that's dominating headlines for its realistic visuals and flawless lip syncing. They discuss how SeedDance is changing the game compared to heavyweights like Veo and Sora, and why its approach to copyright and training data might give it a global edge.Along the way, Matt Wolfe and Joe Fier demo tools live, including GPT-5.3 Codex Spark and Google's Gemini DeepThink, showing how these models can create websites, apps, and even solve scientific problems at lightning speed. The episode also explores the ethical and business ramifications of AI's rapid evolution—from ads in ChatGPT to the potential impact on jobs and creativity—making it a must-listen for anyone eager to stay ahead in the AI landscape.Topics DiscussedSeedance 2.0's Arrival & ImpactDemos & Real-World ExamplesThe Future of AI Video in Marketing & AdvertisingAI and IP/Copyright ChallengesUltra-Fast Coding ModelsHuman Creativity vs. AIAI Advertising & MonetizationRapid AI Advancement & Staying AheadResources MentionedThe Next Wave Podcast: https://www.thenextwave.showMatt Wolfe: https://www.youtube.com/@mreflow Seedance 2.0: https://www.seedance.com/ByteDance: https://www.bytedance.com/CapCut: https://www.capcut.com/Veo: https://deepmind.google/models/veo/Runway: https://runwayml.com/ChatGPT Codex: https://chatgpt.com/codexMatt Schumer's Viral Article: https://www.mattshumer.com/blog/ai-changes-everythingSuper Bowl Claude Commercial:

Tickets for AIEi Miami and AIE Europe are live, with first wave speakers announced!From pioneering software-defined networking to backing many of the most aggressive AI model companies of this cycle, Martin Casado and Sarah Wang sit at the center of the capital, compute, and talent arms race reshaping the tech industry. As partners at a16z investing across infrastructure and growth, they've watched venture and growth blur, model labs turn dollars into capability at unprecedented speed, and startups raise nine-figure rounds before monetization.Martin and Sarah join us to unpack the new financing playbook for AI: why today's rounds are really compute contracts in disguise, how the “raise → train → ship → raise bigger” flywheel works, and whether foundation model companies can outspend the entire app ecosystem built on top of them. They also share what's underhyped (boring enterprise software), what's overheated (talent wars and compensation spirals), and the two radically different futures they see for AI's market structure.We discuss:* Martin's “two futures” fork: infinite fragmentation and new software categories vs. a small oligopoly of general models that consume everything above them* The capital flywheel: how model labs translate funding directly into capability gains, then into revenue growth measured in weeks, not years* Why venture and growth have merged: $100M–$1B hybrid rounds, strategic investors, compute negotiations, and complex deal structures* The AGI vs. product tension: allocating scarce GPUs between long-term research and near-term revenue flywheels* Whether frontier labs can out-raise and outspend the entire app ecosystem built on top of their APIs* Why today's talent wars ($10M+ comp packages, $B acqui-hires) are breaking early-stage founder math* Cursor as a case study: building up from the app layer while training down into your own models* Why “boring” enterprise software may be the most underinvested opportunity in the AI mania* Hardware and robotics: why the ChatGPT moment hasn't yet arrived for robots and what would need to change* World Labs and generative 3D: bringing the marginal cost of 3D scene creation down by orders of magnitude* Why public AI discourse is often wildly disconnected from boardroom reality and how founders should navigate the noiseShow Notes:* “Where Value Will Accrue in AI: Martin Casado & Sarah Wang” - a16z show* “Jack Altman & Martin Casado on the Future of Venture Capital”* World Labs—Martin Casado• LinkedIn: https://www.linkedin.com/in/martincasado/• X: https://x.com/martin_casadoSarah Wang• LinkedIn: https://www.linkedin.com/in/sarah-wang-59b96a7• X: https://x.com/sarahdingwanga16z• https://a16z.com/Timestamps00:00:00 – Intro: Live from a16z00:01:20 – The New AI Funding Model: Venture + Growth Collide00:03:19 – Circular Funding, Demand & “No Dark GPUs”00:05:24 – Infrastructure vs Apps: The Lines Blur00:06:24 – The Capital Flywheel: Raise → Train → Ship → Raise Bigger00:09:39 – Can Frontier Labs Outspend the Entire App Ecosystem?00:11:24 – Character AI & The AGI vs Product Dilemma00:14:39 – Talent Wars, $10M Engineers & Founder Anxiety00:17:33 – What's Underinvested? The Case for “Boring” Software00:19:29 – Robotics, Hardware & Why It's Hard to Win00:22:42 – Custom ASICs & The $1B Training Run Economics00:24:23 – American Dynamism, Geography & AI Power Centers00:26:48 – How AI Is Changing the Investor Workflow (Claude Cowork)00:29:12 – Two Futures of AI: Infinite Expansion or Oligopoly?00:32:48 – If You Can Raise More Than Your Ecosystem, You Win00:34:27 – Are All Tasks AGI-Complete? Coding as the Test Case00:38:55 – Cursor & The Power of the App Layer00:44:05 – World Labs, Spatial Intelligence & 3D Foundation Models00:47:20 – Thinking Machines, Founder Drama & Media Narratives00:52:30 – Where Long-Term Power Accrues in the AI StackTranscriptLatent.Space - Inside AI's $10B+ Capital Flywheel — Martin Casado & Sarah Wang of a16z[00:00:00] Welcome to Latent Space (Live from a16z) + Meet the Guests[00:00:00] Alessio: Hey everyone. Welcome to the Latent Space podcast, live from a 16 z. Uh, this is Alessio founder Kernel Lance, and I'm joined by Twix, editor of Latent Space.[00:00:08] swyx: Hey, hey, hey. Uh, and we're so glad to be on with you guys. Also a top AI podcast, uh, Martin Cado and Sarah Wang. Welcome, very[00:00:16] Martin Casado: happy to be here and welcome.[00:00:17] swyx: Yes, uh, we love this office. We love what you've done with the place. Uh, the new logo is everywhere now. It's, it's still getting, takes a while to get used to, but it reminds me of like sort of a callback to a more ambitious age, which I think is kind of[00:00:31] Martin Casado: definitely makes a statement.[00:00:33] swyx: Yeah.[00:00:34] Martin Casado: Not quite sure what that statement is, but it makes a statement.[00:00:37] swyx: Uh, Martin, I go back with you to Netlify.[00:00:40] Martin Casado: Yep.[00:00:40] swyx: Uh, and, uh, you know, you create a software defined networking and all, all that stuff people can read up on your background. Yep. Sarah, I'm newer to you. Uh, you, you sort of started working together on AI infrastructure stuff.[00:00:51] Sarah Wang: That's right. Yeah. Seven, seven years ago now.[00:00:53] Martin Casado: Best growth investor in the entire industry.[00:00:55] swyx: Oh, say[00:00:56] Martin Casado: more hands down there is, there is. [00:01:00] I mean, when it comes to AI companies, Sarah, I think has done the most kind of aggressive, um, investment thesis around AI models, right? So, worked for Nom Ja, Mira Ia, FEI Fey, and so just these frontier, kind of like large AI models.[00:01:15] I think, you know, Sarah's been the, the broadest investor. Is that fair?[00:01:20] Venture vs. Growth in the Frontier Model Era[00:01:20] Sarah Wang: No, I, well, I was gonna say, I think it's been a really interesting tag, tag team actually just ‘cause the, a lot of these big C deals, not only are they raising a lot of money, um, it's still a tech founder bet, which obviously is inherently early stage.[00:01:33] But the resources,[00:01:36] Martin Casado: so many, I[00:01:36] Sarah Wang: was gonna say the resources one, they just grow really quickly. But then two, the resources that they need day one are kind of growth scale. So I, the hybrid tag team that we have is. Quite effective, I think,[00:01:46] Martin Casado: what is growth these days? You know, you don't wake up if it's less than a billion or like, it's, it's actually, it's actually very like, like no, it's a very interesting time in investing because like, you know, take like the character around, right?[00:01:59] These tend to [00:02:00] be like pre monetization, but the dollars are large enough that you need to have a larger fund and the analysis. You know, because you've got lots of users. ‘cause this stuff has such high demand requires, you know, more of a number sophistication. And so most of these deals, whether it's US or other firms on these large model companies, are like this hybrid between venture growth.[00:02:18] Sarah Wang: Yeah. Total. And I think, you know, stuff like BD for example, you wouldn't usually need BD when you were seed stage trying to get market biz Devrel. Biz Devrel, exactly. Okay. But like now, sorry, I'm,[00:02:27] swyx: I'm not familiar. What, what, what does biz Devrel mean for a venture fund? Because I know what biz Devrel means for a company.[00:02:31] Sarah Wang: Yeah.[00:02:32] Compute Deals, Strategics, and the ‘Circular Funding' Question[00:02:32] Sarah Wang: You know, so a, a good example is, I mean, we talk about buying compute, but there's a huge negotiation involved there in terms of, okay, do you get equity for the compute? What, what sort of partner are you looking at? Is there a go-to market arm to that? Um, and these are just things on this scale, hundreds of millions, you know, maybe.[00:02:50] Six months into the inception of a company, you just wouldn't have to negotiate these deals before.[00:02:54] Martin Casado: Yeah. These large rounds are very complex now. Like in the past, if you did a series A [00:03:00] or a series B, like whatever, you're writing a 20 to a $60 million check and you call it a day. Now you normally have financial investors and strategic investors, and then the strategic portion always still goes with like these kind of large compute contracts, which can take months to do.[00:03:13] And so it's, it's very different ties. I've been doing this for 10 years. It's the, I've never seen anything like this.[00:03:19] swyx: Yeah. Do you have worries about the circular funding from so disease strategics?[00:03:24] Martin Casado: I mean, listen, as long as the demand is there, like the demand is there. Like the problem with the internet is the demand wasn't there.[00:03:29] swyx: Exactly. All right. This, this is like the, the whole pyramid scheme bubble thing, where like, as long as you mark to market on like the notional value of like, these deals, fine, but like once it starts to chip away, it really Well[00:03:41] Martin Casado: no, like as, as, as, as long as there's demand. I mean, you know, this, this is like a lot of these sound bites have already become kind of cliches, but they're worth saying it.[00:03:47] Right? Like during the internet days, like we were. Um, raising money to put fiber in the ground that wasn't used. And that's a problem, right? Because now you actually have a supply overhang.[00:03:58] swyx: Mm-hmm.[00:03:59] Martin Casado: And even in the, [00:04:00] the time of the, the internet, like the supply and, and bandwidth overhang, even as massive as it was in, as massive as the crash was only lasted about four years.[00:04:09] But we don't have a supply overhang. Like there's no dark GPUs, right? I mean, and so, you know, circular or not, I mean, you know, if, if someone invests in a company that, um. You know, they'll actually use the GPUs. And on the other side of it is the, is the ask for customer. So I I, I think it's a different time.[00:04:25] Sarah Wang: I think the other piece, maybe just to add onto this, and I'm gonna quote Martine in front of him, but this is probably also a unique time in that. For the first time, you can actually trace dollars to outcomes. Yeah, right. Provided that scaling laws are, are holding, um, and capabilities are actually moving forward.[00:04:40] Because if you can put translate dollars into capabilities, uh, a capability improvement, there's demand there to martine's point. But if that somehow breaks, you know, obviously that's an important assumption in this whole thing to make it work. But you know, instead of investing dollars into sales and marketing, you're, you're investing into r and d to get to the capability, um, you know, increase.[00:04:59] And [00:05:00] that's sort of been the demand driver because. Once there's an unlock there, people are willing to pay for it.[00:05:05] Alessio: Yeah.[00:05:06] Blurring Lines: Models as Infra + Apps, and the New Fundraising Flywheel[00:05:06] Alessio: Is there any difference in how you built the portfolio now that some of your growth companies are, like the infrastructure of the early stage companies, like, you know, OpenAI is now the same size as some of the cloud providers were early on.[00:05:16] Like what does that look like? Like how much information can you feed off each other between the, the two?[00:05:24] Martin Casado: There's so many lines that are being crossed right now, or blurred. Right. So we already talked about venture and growth. Another one that's being blurred is between infrastructure and apps, right? So like what is a model company?[00:05:35] Mm-hmm. Like, it's clearly infrastructure, right? Because it's like, you know, it's doing kind of core r and d. It's a horizontal platform, but it's also an app because it's um, uh, touches the users directly. And then of course. You know, the, the, the growth of these is just so high. And so I actually think you're just starting to see a, a, a new financing strategy emerge and, you know, we've had to adapt as a result of that.[00:05:59] And [00:06:00] so there's been a lot of changes. Um, you're right that these companies become platform companies very quickly. You've got ecosystem build out. So none of this is necessarily new, but the timescales of which it's happened is pretty phenomenal. And the way we'd normally cut lines before is blurred a little bit, but.[00:06:16] But that, that, that said, I mean, a lot of it also just does feel like things that we've seen in the past, like cloud build out the internet build out as well.[00:06:24] Sarah Wang: Yeah. Um, yeah, I think it's interesting, uh, I don't know if you guys would agree with this, but it feels like the emerging strategy is, and this builds off of your other question, um.[00:06:33] You raise money for compute, you pour that or you, you pour the money into compute, you get some sort of breakthrough. You funnel the breakthrough into your vertically integrated application. That could be chat GBT, that could be cloud code, you know, whatever it is. You massively gain share and get users.[00:06:49] Maybe you're even subsidizing at that point. Um, depending on your strategy. You raise money at the peak momentum and then you repeat, rinse and repeat. Um, and so. And that wasn't [00:07:00] true even two years ago, I think. Mm-hmm. And so it's sort of to your, just tying it to fundraising strategy, right? There's a, and hiring strategy.[00:07:07] All of these are tied, I think the lines are blurring even more today where everyone is, and they, but of course these companies all have API businesses and so they're these, these frenemy lines that are getting blurred in that a lot of, I mean, they have billions of dollars of API revenue, right? And so there are customers there.[00:07:23] But they're competing on the app layer.[00:07:24] Martin Casado: Yeah. So this is a really, really important point. So I, I would say for sure, venture and growth, that line is blurry app and infrastructure. That line is blurry. Um, but I don't think that that changes our practice so much. But like where the very open questions are like, does this layer in the same way.[00:07:43] Compute traditionally has like during the cloud is like, you know, like whatever, somebody wins one layer, but then another whole set of companies wins another layer. But that might not, might not be the case here. It may be the case that you actually can't verticalize on the token string. Like you can't build an app like it, it necessarily goes down just because there are no [00:08:00] abstractions.[00:08:00] So those are kinda the bigger existential questions we ask. Another thing that is very different this time than in the history of computer sciences is. In the past, if you raised money, then you basically had to wait for engineering to catch up. Which famously doesn't scale like the mythical mammoth. It take a very long time.[00:08:18] But like that's not the case here. Like a model company can raise money and drop a model in a, in a year, and it's better, right? And, and it does it with a team of 20 people or 10 people. So this type of like money entering a company and then producing something that has demand and growth right away and using that to raise more money is a very different capital flywheel than we've ever seen before.[00:08:39] And I think everybody's trying to understand what the consequences are. So I think it's less about like. Big companies and growth and this, and more about these more systemic questions that we actually don't have answers to.[00:08:49] Alessio: Yeah, like at Kernel Labs, one of our ideas is like if you had unlimited money to spend productively to turn tokens into products, like the whole early stage [00:09:00] market is very different because today you're investing X amount of capital to win a deal because of price structure and whatnot, and you're kind of pot committing.[00:09:07] Yeah. To a certain strategy for a certain amount of time. Yeah. But if you could like iteratively spin out companies and products and just throw, I, I wanna spend a million dollar of inference today and get a product out tomorrow.[00:09:18] swyx: Yeah.[00:09:19] Alessio: Like, we should get to the point where like the friction of like token to product is so low that you can do this and then you can change the Right, the early stage venture model to be much more iterative.[00:09:30] And then every round is like either 100 k of inference or like a hundred million from a 16 Z. There's no, there's no like $8 million C round anymore. Right.[00:09:38] When Frontier Labs Outspend the Entire App Ecosystem[00:09:38] Martin Casado: But, but, but, but there's a, there's a, the, an industry structural question that we don't know the answer to, which involves the frontier models, which is, let's take.[00:09:48] Anthropic it. Let's say Anthropic has a state-of-the-art model that has some large percentage of market share. And let's say that, uh, uh, uh, you know, uh, a company's building smaller models [00:10:00] that, you know, use the bigger model in the background, open 4.5, but they add value on top of that. Now, if Anthropic can raise three times more.[00:10:10] Every subsequent round, they probably can raise more money than the entire app ecosystem that's built on top of it. And if that's the case, they can expand beyond everything built on top of it. It's like imagine like a star that's just kind of expanding, so there could be a systemic. There could be a, a systemic situation where the soda models can raise so much money that they can out pay anybody that bills on top of ‘em, which would be something I don't think we've ever seen before just because we were so bottlenecked in engineering, and this is a very open question.[00:10:41] swyx: Yeah. It's, it is almost like bitter lesson applied to the startup industry.[00:10:45] Martin Casado: Yeah, a hundred percent. It literally becomes an issue of like raise capital, turn that directly into growth. Use that to raise three times more. Exactly. And if you can keep doing that, you literally can outspend any company that's built the, not any company.[00:10:57] You can outspend the aggregate of companies on top of [00:11:00] you and therefore you'll necessarily take their share, which is crazy.[00:11:02] swyx: Would you say that kind of happens in character? Is that the, the sort of postmortem on. What happened?[00:11:10] Sarah Wang: Um,[00:11:10] Martin Casado: no.[00:11:12] Sarah Wang: Yeah, because I think so,[00:11:13] swyx: I mean the actual postmortem is, he wanted to go back to Google.[00:11:15] Exactly. But like[00:11:18] Martin Casado: that's another difference that[00:11:19] Sarah Wang: you said[00:11:21] Martin Casado: it. We should talk, we should actually talk about that.[00:11:22] swyx: Yeah,[00:11:22] Sarah Wang: that's[00:11:23] swyx: Go for it. Take it. Take,[00:11:23] Sarah Wang: yeah.[00:11:24] Character.AI, Founder Goals (AGI vs Product), and GPU Allocation Tradeoffs[00:11:24] Sarah Wang: I was gonna say, I think, um. The, the, the character thing raises actually a different issue, which actually the Frontier Labs will face as well. So we'll see how they handle it.[00:11:34] But, um, so we invest in character in January, 2023, which feels like eons ago, I mean, three years ago. Feels like lifetimes ago. But, um, and then they, uh, did the IP licensing deal with Google in August, 2020. Uh, four. And so, um, you know, at the time, no, you know, he's talked publicly about this, right? He wanted to Google wouldn't let him put out products in the world.[00:11:56] That's obviously changed drastically. But, um, he went to go do [00:12:00] that. Um, but he had a product attached. The goal was, I mean, it's Nome Shair, he wanted to get to a GI. That was always his personal goal. But, you know, I think through collecting data, right, and this sort of very human use case, that the character product.[00:12:13] Originally was and still is, um, was one of the vehicles to do that. Um, I think the real reason that, you know. I if you think about the, the stress that any company feels before, um, you ultimately going one way or the other is sort of this a GI versus product. Um, and I think a lot of the big, I think, you know, opening eyes, feeling that, um, anthropic if they haven't started, you know, felt it, certainly given the success of their products, they may start to feel that soon.[00:12:39] And the real. I think there's real trade-offs, right? It's like how many, when you think about GPUs, that's a limited resource. Where do you allocate the GPUs? Is it toward the product? Is it toward new re research? Right? Is it, or long-term research, is it toward, um, n you know, near to midterm research? And so, um, in a case where you're resource constrained, um, [00:13:00] of course there's this fundraising game you can play, right?[00:13:01] But the fund, the market was very different back in 2023 too. Um. I think the best researchers in the world have this dilemma of, okay, I wanna go all in on a GI, but it's the product usage revenue flywheel that keeps the revenue in the house to power all the GPUs to get to a GI. And so it does make, um, you know, I think it sets up an interesting dilemma for any startup that has trouble raising up until that level, right?[00:13:27] And certainly if you don't have that progress, you can't continue this fly, you know, fundraising flywheel.[00:13:32] Martin Casado: I would say that because, ‘cause we're keeping track of all of the things that are different, right? Like, you know, venture growth and uh, app infra and one of the ones is definitely the personalities of the founders.[00:13:45] It's just very different this time I've been. Been doing this for a decade and I've been doing startups for 20 years. And so, um, I mean a lot of people start this to do a GI and we've never had like a unified North star that I recall in the same [00:14:00] way. Like people built companies to start companies in the past.[00:14:02] Like that was what it was. Like I would create an internet company, I would create infrastructure company, like it's kind of more engineering builders and this is kind of a different. You know, mentality. And some companies have harnessed that incredibly well because their direction is so obviously on the path to what somebody would consider a GI, but others have not.[00:14:20] And so like there is always this tension with personnel. And so I think we're seeing more kind of founder movement.[00:14:27] Sarah Wang: Yeah.[00:14:27] Martin Casado: You know, as a fraction of founders than we've ever seen. I mean, maybe since like, I don't know the time of like Shockly and the trade DUR aid or something like that. Way back in the beginning of the industry, I, it's a very, very.[00:14:38] Unusual time of personnel.[00:14:39] Sarah Wang: Totally.[00:14:40] Talent Wars, Mega-Comp, and the Rise of Acquihire M&A[00:14:40] Sarah Wang: And it, I think it's exacerbated by the fact that talent wars, I mean, every industry has talent wars, but not at this magnitude, right? No. Yeah. Very rarely can you see someone get poached for $5 billion. That's hard to compete with. And then secondly, if you're a founder in ai, you could fart and it would be on the front page of, you know, the information these days.[00:14:59] And so there's [00:15:00] sort of this fishbowl effect that I think adds to the deep anxiety that, that these AI founders are feeling.[00:15:06] Martin Casado: Hmm.[00:15:06] swyx: Uh, yes. I mean, just on, uh, briefly comment on the founder, uh, the sort of. Talent wars thing. I feel like 2025 was just like a blip. Like I, I don't know if we'll see that again.[00:15:17] ‘cause meta built the team. Like, I don't know if, I think, I think they're kind of done and like, who's gonna pay more than meta? I, I don't know.[00:15:23] Martin Casado: I, I agree. So it feels so, it feel, it feels this way to me too. It's like, it is like, basically Zuckerberg kind of came out swinging and then now he's kind of back to building.[00:15:30] Yeah,[00:15:31] swyx: yeah. You know, you gotta like pay up to like assemble team to rush the job, whatever. But then now, now you like you, you made your choices and now they got a ship.[00:15:38] Martin Casado: I mean, the, the o other side of that is like, you know, like we're, we're actually in the job hiring market. We've got 600 people here. I hire all the time.[00:15:44] I've got three open recs if anybody's interested, that's listening to this for investor. Yeah, on, on the team, like on the investing side of the team, like, and, um, a lot of the people we talk to have acting, you know, active, um, offers for 10 million a year or something like that. And like, you know, and we pay really, [00:16:00] really well.[00:16:00] And just to see what's out on the market is really, is really remarkable. And so I would just say it's actually, so you're right, like the really flashy one, like I will get someone for, you know, a billion dollars, but like the inflated, um, uh, trickles down. Yeah, it is still very active today. I mean,[00:16:18] Sarah Wang: yeah, you could be an L five and get an offer in the tens of millions.[00:16:22] Okay. Yeah. Easily. Yeah. It's so I think you're right that it felt like a blip. I hope you're right. Um, but I think it's been, the steady state is now, I think got pulled up. Yeah. Yeah. I'll pull up for[00:16:31] Martin Casado: sure. Yeah.[00:16:32] Alessio: Yeah. And I think that's breaking the early stage founder math too. I think before a lot of people would be like, well, maybe I should just go be a founder instead of like getting paid.[00:16:39] Yeah. 800 KA million at Google. But if I'm getting paid. Five, 6 million. That's different but[00:16:45] Martin Casado: on. But on the other hand, there's more strategic money than we've ever seen historically, right? Mm-hmm. And so, yep. The economics, the, the, the, the calculus on the economics is very different in a number of ways. And, uh, it's crazy.[00:16:58] It's cra it's causing like a, [00:17:00] a, a, a ton of change in confusion in the market. Some very positive, sub negative, like, so for example, the other side of the, um. The co-founder, like, um, acquisition, you know, mark Zuckerberg poaching someone for a lot of money is like, we were actually seeing historic amount of m and a for basically acquihires, right?[00:17:20] That you like, you know, really good outcomes from a venture perspective that are effective acquihires, right? So I would say it's probably net positive from the investment standpoint, even though it seems from the headlines to be very disruptive in a negative way.[00:17:33] Alessio: Yeah.[00:17:33] What's Underfunded: Boring Software, Robotics Skepticism, and Custom Silicon Economics[00:17:33] Alessio: Um, let's talk maybe about what's not being invested in, like maybe some interesting ideas that you would see more people build or it, it seems in a way, you know, as ycs getting more popular, it's like access getting more popular.[00:17:47] There's a startup school path that a lot of founders take and they know what's hot in the VC circles and they know what gets funded. Uh, and there's maybe not as much risk appetite for. Things outside of that. Um, I'm curious if you feel [00:18:00] like that's true and what are maybe, uh, some of the areas, uh, that you think are under discussed?[00:18:06] Martin Casado: I mean, I actually think that we've taken our eye off the ball in a lot of like, just traditional, you know, software companies. Um, so like, I mean. You know, I think right now there's almost a barbell, like you're like the hot thing on X, you're deep tech.[00:18:21] swyx: Mm-hmm.[00:18:22] Martin Casado: Right. But I, you know, I feel like there's just kind of a long, you know, list of like good.[00:18:28] Good companies that will be around for a long time in very large markets. Say you're building a database, you know, say you're building, um, you know, kind of monitoring or logging or tooling or whatever. There's some good companies out there right now, but like, they have a really hard time getting, um, the attention of investors.[00:18:43] And it's almost become a meme, right? Which is like, if you're not basically growing from zero to a hundred in a year, you're not interesting, which is just, is the silliest thing to say. I mean, think of yourself as like an introvert person, like, like your personal money, right? Mm-hmm. So. Your personal money, will you put it in the stock market at 7% or you put it in this company growing five x in a very large [00:19:00] market?[00:19:00] Of course you can put it in the company five x. So it's just like we say these stupid things, like if you're not going from zero to a hundred, but like those, like who knows what the margins of those are mean. Clearly these are good investments. True for anybody, right? True. Like our LPs want whatever.[00:19:12] Three x net over, you know, the life cycle of a fund, right? So a, a company in a big market growing five X is a great investment. We'd, everybody would be happy with these returns, but we've got this kind of mania on these, these strong growths. And so I would say that that's probably the most underinvested sector.[00:19:28] Right now.[00:19:29] swyx: Boring software, boring enterprise software.[00:19:31] Martin Casado: Traditional. Really good company.[00:19:33] swyx: No, no AI here.[00:19:34] Martin Casado: No. Like boring. Well, well, the AI of course is pulling them into use cases. Yeah, but that's not what they're, they're not on the token path, right? Yeah. Let's just say that like they're software, but they're not on the token path.[00:19:41] Like these are like they're great investments from any definition except for like random VC on Twitter saying VC on x, saying like, it's not growing fast enough. What do you[00:19:52] Sarah Wang: think? Yeah, maybe I'll answer a slightly different. Question, but adjacent to what you asked, um, which is maybe an area that we're not, uh, investing [00:20:00] right now that I think is a question and we're spending a lot of time in regardless of whether we pull the trigger or not.[00:20:05] Um, and it would probably be on the hardware side, actually. Robotics, right? And the robotics side. Robotics. Right. Which is, it's, I don't wanna say that it's not getting funding ‘cause it's clearly, uh, it's, it's sort of non-consensus to almost not invest in robotics at this point. But, um, we spent a lot of time in that space and I think for us, we just haven't seen the chat GPT moment.[00:20:22] Happen on the hardware side. Um, and the funding going into it feels like it's already. Taking that for granted.[00:20:30] Martin Casado: Yeah. Yeah. But we also went through the drone, you know, um, there's a zip line right, right out there. What's that? Oh yeah, there's a zip line. Yeah. What the drone, what the av And like one of the takeaways is when it comes to hardware, um, most companies will end up verticalizing.[00:20:46] Like if you're. If you're investing in a robot company for an A for agriculture, you're investing in an ag company. ‘cause that's the competition and that's surprising. And that's supply chain. And if you're doing it for mining, that's mining. And so the ad team does a lot of that type of stuff ‘cause they actually set up to [00:21:00] diligence that type of work.[00:21:01] But for like horizontal technology investing, there's very little when it comes to robots just because it's so fit for, for purpose. And so we kinda like to look at software. Solutions or horizontal solutions like applied intuition. Clearly from the AV wave deep map, clearly from the AV wave, I would say scale AI was actually a horizontal one for That's fair, you know, for robotics early on.[00:21:23] And so that sort of thing we're very, very interested. But the actual like robot interacting with the world is probably better for different team. Agree.[00:21:30] Alessio: Yeah, I'm curious who these teams are supposed to be that invest in them. I feel like everybody's like, yeah, robotics, it's important and like people should invest in it.[00:21:38] But then when you look at like the numbers, like the capital requirements early on versus like the moment of, okay, this is actually gonna work. Let's keep investing. That seems really hard to predict in a way that is not,[00:21:49] Martin Casado: I think co, CO two, kla, gc, I mean these are all invested in in Harvard companies. He just, you know, and [00:22:00] listen, I mean, it could work this time for sure.[00:22:01] Right? I mean if Elon's doing it, he's like, right. Just, just the fact that Elon's doing it means that there's gonna be a lot of capital and a lot of attempts for a long period of time. So that alone maybe suggests that we should just be investing in robotics just ‘cause you have this North star who's Elon with a humanoid and that's gonna like basically willing into being an industry.[00:22:17] Um, but we've just historically found like. We're a huge believer that this is gonna happen. We just don't feel like we're in a good position to diligence these things. ‘cause again, robotics companies tend to be vertical. You really have to understand the market they're being sold into. Like that's like that competitive equilibrium with a human being is what's important.[00:22:34] It's not like the core tech and like we're kind of more horizontal core tech type investors. And this is Sarah and I. Yeah, the ad team is different. They can actually do these types of things.[00:22:42] swyx: Uh, just to clarify, AD stands for[00:22:44] Martin Casado: American Dynamism.[00:22:45] swyx: Alright. Okay. Yeah, yeah, yeah. Uh, I actually, I do have a related question that, first of all, I wanna acknowledge also just on the, on the chip side.[00:22:51] Yeah. I, I recall a podcast that where you were on, i, I, I think it was the a CC podcast, uh, about two or three years ago where you, where you suddenly said [00:23:00] something, which really stuck in my head about how at some point, at some point kind of scale it makes sense to. Build a custom aic Yes. For per run.[00:23:07] Martin Casado: Yes.[00:23:07] It's crazy. Yeah.[00:23:09] swyx: We're here and I think you, you estimated 500 billion, uh, something.[00:23:12] Martin Casado: No, no, no. A billion, a billion dollar training run of $1 billion training run. It makes sense to actually do a custom meic if you can do it in time. The question now is timelines. Yeah, but not money because just, just, just rough math.[00:23:22] If it's a billion dollar training. Then the inference for that model has to be over a billion, otherwise it won't be solvent. So let's assume it's, if you could save 20%, which you could save much more than that with an ASIC 20%, that's $200 million. You can tape out a chip for $200 million. Right? So now you can literally like justify economically, not timeline wise.[00:23:41] That's a different issue. An ASIC per model, which[00:23:44] swyx: is because that, that's how much we leave on the table every single time. We, we, we do like generic Nvidia.[00:23:48] Martin Casado: Exactly. Exactly. No, it, it is actually much more than that. You could probably get, you know, a factor of two, which would be 500 million.[00:23:54] swyx: Typical MFU would be like 50.[00:23:55] Yeah, yeah. And that's good.[00:23:57] Martin Casado: Exactly. Yeah. Hundred[00:23:57] swyx: percent. Um, so, so, yeah, and I mean, and I [00:24:00] just wanna acknowledge like, here we are in, in, in 2025 and opening eyes confirming like Broadcom and all the other like custom silicon deals, which is incredible. I, I think that, uh, you know, speaking about ad there's, there's a really like interesting tie in that obviously you guys are hit on, which is like these sort, this sort of like America first movement or like sort of re industrialized here.[00:24:17] Yeah. Uh, move TSMC here, if that's possible. Um, how much overlap is there from ad[00:24:23] Martin Casado: Yeah.[00:24:23] swyx: To, I guess, growth and, uh, investing in particularly like, you know, US AI companies that are strongly bounded by their compute.[00:24:32] Martin Casado: Yeah. Yeah. So I mean, I, I would view, I would view AD as more as a market segmentation than like a mission, right?[00:24:37] So the market segmentation is, it has kind of regulatory compliance issues or government, you know, sale or it deals with like hardware. I mean, they're just set up to, to, to, to, to. To diligence those types of companies. So it's a more of a market segmentation thing. I would say the entire firm. You know, which has been since it is been intercepted, you know, has geographical biases, right?[00:24:58] I mean, for the longest time we're like, you [00:25:00] know, bay Area is gonna be like, great, where the majority of the dollars go. Yeah. And, and listen, there, there's actually a lot of compounding effects for having a geographic bias. Right. You know, everybody's in the same place. You've got an ecosystem, you're there, you've got presence, you've got a network.[00:25:12] Um, and, uh, I mean, I would say the Bay area's very much back. You know, like I, I remember during pre COVID, like it was like almost Crypto had kind of. Pulled startups away. Miami from the Bay Area. Miami, yeah. Yeah. New York was, you know, because it's so close to finance, came up like Los Angeles had a moment ‘cause it was so close to consumer, but now it's kind of come back here.[00:25:29] And so I would say, you know, we tend to be very Bay area focused historically, even though of course we've asked all over the world. And then I would say like, if you take the ring out, you know, one more, it's gonna be the US of course, because we know it very well. And then one more is gonna be getting us and its allies and Yeah.[00:25:44] And it goes from there.[00:25:45] Sarah Wang: Yeah,[00:25:45] Martin Casado: sorry.[00:25:46] Sarah Wang: No, no. I agree. I think from a, but I think from the intern that that's sort of like where the companies are headquartered. Maybe your questions on supply chain and customer base. Uh, I, I would say our customers are, are, our companies are fairly international from that perspective.[00:25:59] Like they're selling [00:26:00] globally, right? They have global supply chains in some cases.[00:26:03] Martin Casado: I would say also the stickiness is very different.[00:26:05] Sarah Wang: Yeah.[00:26:05] Martin Casado: Historically between venture and growth, like there's so much company building in venture, so much so like hiring the next PM. Introducing the customer, like all of that stuff.[00:26:15] Like of course we're just gonna be stronger where we have our network and we've been doing business for 20 years. I've been in the Bay Area for 25 years, so clearly I'm just more effective here than I would be somewhere else. Um, where I think, I think for some of the later stage rounds, the companies don't need that much help.[00:26:30] They're already kind of pretty mature historically, so like they can kind of be everywhere. So there's kind of less of that stickiness. This is different in the AI time. I mean, Sarah is now the, uh, chief of staff of like half the AI companies in, uh, in the Bay Area right now. She's like, ops Ninja Biz, Devrel, BizOps.[00:26:48] swyx: Are, are you, are you finding much AI automation in your work? Like what, what is your stack.[00:26:53] Sarah Wang: Oh my, in my personal stack.[00:26:54] swyx: I mean, because like, uh, by the way, it's the, the, the reason for this is it is triggering, uh, yeah. We, like, I'm hiring [00:27:00] ops, ops people. Um, a lot of ponders I know are also hiring ops people and I'm just, you know, it's opportunity Since you're, you're also like basically helping out with ops with a lot of companies.[00:27:09] What are people doing these days? Because it's still very manual as far as I can tell.[00:27:13] Sarah Wang: Hmm. Yeah. I think the things that we help with are pretty network based, um, in that. It's sort of like, Hey, how do do I shortcut this process? Well, let's connect you to the right person. So there's not quite an AI workflow for that.[00:27:26] I will say as a growth investor, Claude Cowork is pretty interesting. Yeah. Like for the first time, you can actually get one shot data analysis. Right. Which, you know, if you're gonna do a customer database, analyze a cohort retention, right? That's just stuff that you had to do by hand before. And our team, the other, it was like midnight and the three of us were playing with Claude Cowork.[00:27:47] We gave it a raw file. Boom. Perfectly accurate. We checked the numbers. It was amazing. That was my like, aha moment. That sounds so boring. But you know, that's, that's the kind of thing that a growth investor is like, [00:28:00] you know, slaving away on late at night. Um, done in a few seconds.[00:28:03] swyx: Yeah. You gotta wonder what the whole, like, philanthropic labs, which is like their new sort of products studio.[00:28:10] Yeah. What would that be worth as an independent, uh, startup? You know, like a[00:28:14] Martin Casado: lot.[00:28:14] Sarah Wang: Yeah, true.[00:28:16] swyx: Yeah. You[00:28:16] Martin Casado: gotta hand it to them. They've been executing incredibly well.[00:28:19] swyx: Yeah. I, I mean, to me, like, you know, philanthropic, like building on cloud code, I think, uh, it makes sense to me the, the real. Um, pedal to the metal, whatever the, the, the phrase is, is when they start coming after consumer with, uh, against OpenAI and like that is like red alert at Open ai.[00:28:35] Oh, I[00:28:35] Martin Casado: think they've been pretty clear. They're enterprise focused.[00:28:37] swyx: They have been, but like they've been free. Here's[00:28:40] Martin Casado: care publicly,[00:28:40] swyx: it's enterprise focused. It's coding. Right. Yeah.[00:28:43] AI Labs vs Startups: Disruption, Undercutting & the Innovator's Dilemma[00:28:43] swyx: And then, and, but here's cloud, cloud, cowork, and, and here's like, well, we, uh, they, apparently they're running Instagram ads for Claudia.[00:28:50] I, on, you know, for, for people on, I get them all the time. Right. And so, like,[00:28:54] Martin Casado: uh,[00:28:54] swyx: it, it's kind of like this, the disruption thing of, uh, you know. Mo Open has been doing, [00:29:00] consumer been doing the, just pursuing general intelligence in every mo modality, and here's a topic that only focus on this thing, but now they're sort of undercutting and doing the whole innovator's dilemma thing on like everything else.[00:29:11] Martin Casado: It's very[00:29:11] swyx: interesting.[00:29:12] Martin Casado: Yeah, I mean there's, there's a very open que so for me there's like, do you know that meme where there's like the guy in the path and there's like a path this way? There's a path this way. Like one which way Western man. Yeah. Yeah.[00:29:23] Two Futures for AI: Infinite Market vs AGI Oligopoly[00:29:23] Martin Casado: And for me, like, like all the entire industry kind of like hinges on like two potential futures.[00:29:29] So in, in one potential future, um, the market is infinitely large. There's perverse economies of scale. ‘cause as soon as you put a model out there, like it kind of sublimates and all the other models catch up and like, it's just like software's being rewritten and fractured all over the place and there's tons of upside and it just grows.[00:29:48] And then there's another path which is like, well. Maybe these models actually generalize really well, and all you have to do is train them with three times more money. That's all you have to [00:30:00] do, and it'll just consume everything beyond it. And if that's the case, like you end up with basically an oligopoly for everything, like, you know mm-hmm.[00:30:06] Because they're perfectly general and like, so this would be like the, the a GI path would be like, these are perfectly general. They can do everything. And this one is like, this is actually normal software. The universe is complicated. You've got, and nobody knows the answer.[00:30:18] The Economics Reality Check: Gross Margins, Training Costs & Borrowing Against the Future[00:30:18] Martin Casado: My belief is if you actually look at the numbers of these companies, so generally if you look at the numbers of these companies, if you look at like the amount they're making and how much they, they spent training the last model, they're gross margin positive.[00:30:30] You're like, oh, that's really working. But if you look at like. The current training that they're doing for the next model, their gross margin negative. So part of me thinks that a lot of ‘em are kind of borrowing against the future and that's gonna have to slow down. It's gonna catch up to them at some point in time, but we don't really know.[00:30:47] Sarah Wang: Yeah.[00:30:47] Martin Casado: Does that make sense? Like, I mean, it could be, it could be the case that the only reason this is working is ‘cause they can raise that next round and they can train that next model. ‘cause these models have such a short. Life. And so at some point in time, like, you know, they won't be able to [00:31:00] raise that next round for the next model and then things will kind of converge and fragment again.[00:31:03] But right now it's not.[00:31:04] Sarah Wang: Totally. I think the other, by the way, just, um, a meta point. I think the other lesson from the last three years is, and we talk about this all the time ‘cause we're on this. Twitter X bubble. Um, cool. But, you know, if you go back to, let's say March, 2024, that period, it felt like a, I think an open source model with an, like a, you know, benchmark leading capability was sort of launching on a daily basis at that point.[00:31:27] And, um, and so that, you know, that's one period. Suddenly it's sort of like open source takes over the world. There's gonna be a plethora. It's not an oligopoly, you know, if you fast, you know, if you, if you rewind time even before that GPT-4 was number one for. Nine months, 10 months. It's a long time. Right.[00:31:44] Um, and of course now we're in this era where it feels like an oligopoly, um, maybe some very steady state shifts and, and you know, it could look like this in the future too, but it just, it's so hard to call. And I think the thing that keeps, you know, us up at [00:32:00] night in, in a good way and bad way, is that the capability progress is actually not slowing down.[00:32:06] And so until that happens, right, like you don't know what's gonna look like.[00:32:09] Martin Casado: But I, I would, I would say for sure it's not converged, like for sure, like the systemic capital flows have not converged, meaning right now it's still borrowing against the future to subsidize growth currently, which you can do that for a period of time.[00:32:23] But, but you know, at the end, at some point the market will rationalize that and just nobody knows what that will look like.[00:32:29] Alessio: Yeah.[00:32:29] Martin Casado: Or, or like the drop in price of compute will, will, will save them. Who knows?[00:32:34] Alessio: Yeah. Yeah. I think the models need to ask them to, to specific tasks. You know? It's like, okay, now Opus 4.5 might be a GI at some specific task, and now you can like depreciate the model over a longer time.[00:32:45] I think now, now, right now there's like no old model.[00:32:47] Martin Casado: No, but let, but lemme just change that mental, that's, that used to be my mental model. Lemme just change it a little bit.[00:32:53] Capital as a Weapon vs Task Saturation: Where Real Enterprise Value Gets Built[00:32:53] Martin Casado: If you can raise three times, if you can raise more than the aggregate of anybody that uses your models, that doesn't even matter.[00:32:59] It doesn't [00:33:00] even matter. See what I'm saying? Like, yeah. Yeah. So, so I have an API Business. My API business is 60% margin, or 70% margin, or 80% margin is a high margin business. So I know what everybody is using. If I can raise more money than the aggregate of everybody that's using it, I will consume them whether I'm a GI or not.[00:33:14] And I will know if they're using it ‘cause they're using it. And like, unlike in the past where engineering stops me from doing that.[00:33:21] Alessio: Mm-hmm.[00:33:21] Martin Casado: It is very straightforward. You just train. So I also thought it was kind of like, you must ask the code a GI, general, general, general. But I think there's also just a possibility that the, that the capital markets will just give them the, the, the ammunition to just go after everybody on top of ‘em.[00:33:36] Sarah Wang: I, I do wonder though, to your point, um, if there's a certain task that. Getting marginally better isn't actually that much better. Like we've asked them to it, to, you know, we can call it a GI or whatever, you know, actually, Ali Goi talks about this, like we're already at a GI for a lot of functions in the enterprise.[00:33:50] Um. That's probably those for those tasks, you probably could build very specific companies that focus on just getting as much value out of that task that isn't [00:34:00] coming from the model itself. There's probably a rich enterprise business to be built there. I mean, could be wrong on that, but there's a lot of interesting examples.[00:34:08] So, right, if you're looking the legal profession or, or whatnot, and maybe that's not a great one ‘cause the models are getting better on that front too, but just something where it's a bit saturated, then the value comes from. Services. It comes from implementation, right? It comes from all these things that actually make it useful to the end customer.[00:34:24] Martin Casado: Sorry, what am I, one more thing I think is, is underused in all of this is like, to what extent every task is a GI complete.[00:34:31] Sarah Wang: Mm-hmm.[00:34:32] Martin Casado: Yeah. I code every day. It's so fun.[00:34:35] Sarah Wang: That's a core question. Yeah.[00:34:36] Martin Casado: And like. When I'm talking to these models, it's not just code. I mean, it's everything, right? Like I, you know, like it's,[00:34:43] swyx: it's healthcare.[00:34:44] It's,[00:34:44] Martin Casado: I mean, it's[00:34:44] swyx: Mele,[00:34:45] Martin Casado: but it's every, it is exactly that. Like, yeah, that's[00:34:47] Sarah Wang: great support. Yeah.[00:34:48] Martin Casado: It's everything. Like I'm asking these models to, yeah, to understand compliance. I'm asking these models to go search the web. I'm asking these models to talk about things I know in the history, like it's having a full conversation with me while I, I engineer, and so it could be [00:35:00] the case that like, mm-hmm.[00:35:01] The most a, you know, a GI complete, like I'm not an a GI guy. Like I think that's, you know, but like the most a GI complete model will is win independent of the task. And we don't know the answer to that one either.[00:35:11] swyx: Yeah.[00:35:12] Martin Casado: But it seems to me that like, listen, codex in my experience is for sure better than Opus 4.5 for coding.[00:35:18] Like it finds the hardest bugs that I work in with. Like, it is, you know. The smartest developers. I don't work on it. It's great. Um, but I think Opus 4.5 is actually very, it's got a great bedside manner and it really, and it, it really matters if you're building something very complex because like, it really, you know, like you're, you're, you're a partner and a brainstorming partner for somebody.[00:35:38] And I think we don't discuss enough how every task kind of has that quality.[00:35:42] swyx: Mm-hmm.[00:35:43] Martin Casado: And what does that mean to like capital investment and like frontier models and Submodels? Yeah.[00:35:47] Why “Coding Models” Keep Collapsing into Generalists (Reasoning vs Taste)[00:35:47] Martin Casado: Like what happened to all the special coding models? Like, none of ‘em worked right. So[00:35:51] Alessio: some of them, they didn't even get released.[00:35:53] Magical[00:35:54] Martin Casado: Devrel. There's a whole, there's a whole host. We saw a bunch of them and like there's this whole theory that like, there could be, and [00:36:00] I think one of the conclusions is, is like there's no such thing as a coding model,[00:36:04] Alessio: you know?[00:36:04] Martin Casado: Like, that's not a thing. Like you're talking to another human being and it's, it's good at coding, but like it's gotta be good at everything.[00:36:10] swyx: Uh, minor disagree only because I, I'm pretty like, have pretty high confidence that basically open eye will always release a GPT five and a GT five codex. Like that's the code's. Yeah. The way I call it is one for raisin, one for Tiz. Um, and, and then like someone internal open, it was like, yeah, that's a good way to frame it.[00:36:32] Martin Casado: That's so funny.[00:36:33] swyx: Uh, but maybe it, maybe it collapses down to reason and that's it. It's not like a hundred dimensions doesn't life. Yeah. It's two dimensions. Yeah, yeah, yeah, yeah. Like and exactly. Beside manner versus coding. Yeah.[00:36:43] Martin Casado: Yeah.[00:36:44] swyx: It's, yeah.[00:36:46] Martin Casado: I, I think for, for any, it's hilarious. For any, for anybody listening to this for, for, for, I mean, for you, like when, when you're like coding or using these models for something like that.[00:36:52] Like actually just like be aware of how much of the interaction has nothing to do with coding and it just turns out to be a large portion of it. And so like, you're, I [00:37:00] think like, like the best Soto ish model. You know, it is going to remain very important no matter what the task is.[00:37:06] swyx: Yeah.[00:37:07] What He's Actually Coding: Gaussian Splats, Spark.js & 3D Scene Rendering Demos[00:37:07] swyx: Uh, speaking of coding, uh, I, I'm gonna be cheeky and ask like, what actually are you coding?[00:37:11] Because obviously you, you could code anything and you are obviously a busy investor and a manager of the good. Giant team. Um, what are you calling?[00:37:18] Martin Casado: I help, um, uh, FEFA at World Labs. Uh, it's one of the investments and um, and they're building a foundation model that creates 3D scenes.[00:37:27] swyx: Yeah, we had it on the pod.[00:37:28] Yeah. Yeah,[00:37:28] Martin Casado: yeah. And so these 3D scenes are Gaussian splats, just by the way that kind of AI works. And so like, you can reconstruct a scene better with, with, with radiance feels than with meshes. ‘cause like they don't really have topology. So, so they, they, they produce each. Beautiful, you know, 3D rendered scenes that are Gaussian splats, but the actual industry support for Gaussian splats isn't great.[00:37:50] It's just never, you know, it's always been meshes and like, things like unreal use meshes. And so I work on a open source library called Spark js, which is a. Uh, [00:38:00] a JavaScript rendering layer ready for Gaussian splats. And it's just because, you know, um, you, you, you need that support and, and right now there's kind of a three js moment that's all meshes and so like, it's become kind of the default in three Js ecosystem.[00:38:13] As part of that to kind of exercise the library, I just build a whole bunch of cool demos. So if you see me on X, you see like all my demos and all the world building, but all of that is just to exercise this, this library that I work on. ‘cause it's actually a very tough algorithmics problem to actually scale a library that much.[00:38:29] And just so you know, this is ancient history now, but 30 years ago I paid for undergrad, you know, working on game engines in college in the late nineties. So I've got actually a back and it's very old background, but I actually have a background in this and so a lot of it's fun. You know, but, but the, the, the, the whole goal is just for this rendering library to, to,[00:38:47] Sarah Wang: are you one of the most active contributors?[00:38:49] The, their GitHub[00:38:50] Martin Casado: spark? Yes.[00:38:51] Sarah Wang: Yeah, yeah.[00:38:51] Martin Casado: There's only two of us there, so, yes. No, so by the way, so the, the pri The pri, yeah. Yeah. So the primary developer is a [00:39:00] guy named Andres Quist, who's an absolute genius. He and I did our, our PhDs together. And so like, um, we studied for constant Quas together. It was almost like hanging out with an old friend, you know?[00:39:09] And so like. So he, he's the core, core guy. I did mostly kind of, you know, the side I run venture fund.[00:39:14] swyx: It's amazing. Like five years ago you would not have done any of this. And it brought you back[00:39:19] Martin Casado: the act, the Activ energy, you're still back. Energy was so high because you had to learn all the framework b******t.[00:39:23] Man, I f*****g used to hate that. And so like, now I don't have to deal with that. I can like focus on the algorithmics so I can focus on the scaling and I,[00:39:29] swyx: yeah. Yeah.[00:39:29] LLMs vs Spatial Intelligence + How to Value World Labs' 3D Foundation Model[00:39:29] swyx: And then, uh, I'll observe one irony and then I'll ask a serious investor question, uh, which is like, the irony is FFE actually doesn't believe that LMS can lead us to spatial intelligence.[00:39:37] And here you are using LMS to like help like achieve spatial intelligence. I just see, I see some like disconnect in there.[00:39:45] Martin Casado: Yeah. Yeah. So I think, I think, you know, I think, I think what she would say is LLMs are great to help with coding.[00:39:51] swyx: Yes.[00:39:51] Martin Casado: But like, that's very different than a model that actually like provides, they, they'll never have the[00:39:56] swyx: spatial inte[00:39:56] Martin Casado: issues.[00:39:56] And listen, our brains clearly listen, our brains, brains clearly have [00:40:00] both our, our brains clearly have a language reasoning section and they clearly have a spatial reasoning section. I mean, it's just, you know, these are two pretty independent problems.[00:40:07] swyx: Okay. And you, you, like, I, I would say that the, the one data point I recently had, uh, against it is the DeepMind, uh, IMO Gold, where, so, uh, typically the, the typical answer is that this is where you start going down the neuros symbolic path, right?[00:40:21] Like one, uh, sort of very sort of abstract reasoning thing and one form, formal thing. Um, and that's what. DeepMind had in 2024 with alpha proof, alpha geometry, and now they just use deep think and just extended thinking tokens. And it's one model and it's, and it's in LM.[00:40:36] Martin Casado: Yeah, yeah, yeah, yeah, yeah.[00:40:37] swyx: And so that, that was my indication of like, maybe you don't need a separate system.[00:40:42] Martin Casado: Yeah. So, so let me step back. I mean, at the end of the day, at the end of the day, these things are like nodes in a graph with weights on them. Right. You know, like it can be modeled like if you, if you distill it down. But let me just talk about the two different substrates. Let's, let me put you in a dark room.[00:40:56] Like totally black room. And then let me just [00:41:00] describe how you exit it. Like to your left, there's a table like duck below this thing, right? I mean like the chances that you're gonna like not run into something are very low. Now let me like turn on the light and you actually see, and you can do distance and you know how far something away is and like where it is or whatever.[00:41:17] Then you can do it, right? Like language is not the right primitives to describe. The universe because it's not exact enough. So that's all Faye, Faye is talking about. When it comes to like spatial reasoning, it's like you actually have to know that this is three feet far, like that far away. It is curved.[00:41:37] You have to understand, you know, the, like the actual movement through space.[00:41:40] swyx: Yeah.[00:41:40] Martin Casado: So I do, I listen, I do think at the end of these models are definitely converging as far as models, but there's, there's, there's different representations of problems you're solving. One is language. Which, you know, that would be like describing to somebody like what to do.[00:41:51] And the other one is actually just showing them and the space reasoning is just showing them.[00:41:55] swyx: Yeah, yeah, yeah. Right. Got it, got it. Uh, the, in the investor question was on, on, well labs [00:42:00] is, well, like, how do I value something like this? What, what, what work does the, do you do? I'm just like, Fefe is awesome.[00:42:07] Justin's awesome. And you know, the other two co-founder, co-founders, but like the, the, the tech, everyone's building cool tech. But like, what's the value of the tech? And this is the fundamental question[00:42:16] Martin Casado: of, well, let, let, just like these, let me just maybe give you a rough sketch on the diffusion models. I actually love to hear Sarah because I'm a venture for, you know, so like, ventures always, always like kind of wild west type[00:42:24] swyx: stuff.[00:42:24] You, you, you, you paid a dream and she has to like, actually[00:42:28] Martin Casado: I'm gonna say I'm gonna mar to reality, so I'm gonna say the venture for you. And she can be like, okay, you a little kid. Yeah. So like, so, so these diffusion models literally. Create something for, for almost nothing. And something that the, the world has found to be very valuable in the past, in our real markets, right?[00:42:45] Like, like a 2D image. I mean, that's been an entire market. People value them. It takes a human being a long time to create it, right? I mean, to create a, you know, a, to turn me into a whatever, like an image would cost a hundred bucks in an hour. The inference cost [00:43:00] us a hundredth of a penny, right? So we've seen this with speech in very successful companies.[00:43:03] We've seen this with 2D image. We've seen this with movies. Right? Now, think about 3D scene. I mean, I mean, when's Grand Theft Auto coming out? It's been six, what? It's been 10 years. I mean, how, how like, but hasn't been 10 years.[00:43:14] Alessio: Yeah.[00:43:15] Martin Casado: How much would it cost to like, to reproduce this room in 3D? Right. If you, if you, if you hired somebody on fiber, like in, in any sort of quality, probably 4,000 to $10,000.[00:43:24] And then if you had a professional, probably $30,000. So if you could generate the exact same thing from a 2D image, and we know that these are used and they're using Unreal and they're using Blend, or they're using movies and they're using video games and they're using all. So if you could do that for.[00:43:36] You know, less than a dollar, that's four or five orders of magnitude cheaper. So you're bringing the marginal cost of something that's useful down by three orders of magnitude, which historically have created very large companies. So that would be like the venture kind of strategic dreaming map.[00:43:49] swyx: Yeah.[00:43:50] And, and for listeners, uh, you can do this yourself on your, on your own phone with like. Uh, the marble.[00:43:55] Martin Casado: Yeah. Marble.[00:43:55] swyx: Uh, or but also there's many Nerf apps where you just go on your iPhone and, and do this.[00:43:59] Martin Casado: Yeah. Yeah. [00:44:00] Yeah. And, and in the case of marble though, it would, what you do is you literally give it in.[00:44:03] So most Nerf apps you like kind of run around and take a whole bunch of pictures and then you kind of reconstruct it.[00:44:08] swyx: Yeah.[00:44:08] Martin Casado: Um, things like marble, just that the whole generative 3D space will just take a 2D image and it'll reconstruct all the like, like[00:44:16] swyx: meaning it has to fill in. Uh,[00:44:18] Martin Casado: stuff at the back of the table, under the table, the back, like, like the images, it doesn't see.[00:44:22] So the generator stuff is very different than reconstruction that it fills in the things that you can't see.[00:44:26] swyx: Yeah. Okay.[00:44:26] Sarah Wang: So,[00:44:27] Martin Casado: all right. So now the,[00:44:28] Sarah Wang: no, no. I mean I love that[00:44:29] Martin Casado: the adult[00:44:29] Sarah Wang: perspective. Um, well, no, I was gonna say these are very much a tag team. So we, we started this pod with that, um, premise. And I think this is a perfect question to even build on that further.[00:44:36] ‘cause it truly is, I mean, we're tag teaming all of these together.[00:44:39] Investing in Model Labs, Media Rumors, and the Cursor Playbook (Margins & Going Down-Stack)[00:44:39] Sarah Wang: Um, but I think every investment fundamentally starts with the same. Maybe the same two premises. One is, at this point in time, we actually believe that there are. And of one founders for their particular craft, and they have to be demonstrated in their prior careers, right?[00:44:56] So, uh, we're not investing in every, you know, now the term is NEO [00:45:00] lab, but every foundation model, uh, any, any company, any founder trying to build a foundation model, we're not, um, contrary to popular opinion, we're

“If anyone's going to disrupt Khan Academy, it should be us,” founder and CEO Sal Khan tells Bloomberg Intelligence Senior Tech Analyst Anurag Rana, discussing how AI can deliver personalized learning at scale if embedded in classrooms with teacher oversight, guardrails for minors and rigorous model evaluation. Khan explains Khanmigo's early GPT-4 roots, why Khan Academy is going multi-model to match use cases like Writing Coach and how district packaging helps cover compute costs while enabling monitoring and accountability. He also lays out a vision of the 2030 classroom where AI reduces teacher planning and grading burdens, supports small-group instruction and enables richer assessment, while warning workforce disruption may arrive faster than society is prepared for.

What if AI didn't replace your creativity—but amplified it?In this episode of Content Amplified, Ben sits down with Mandy Arola, Director of Marketing at Nashville Software School, to unpack a question every marketer is wrestling with: How do you use AI without sacrificing authenticity?Mandy has spent over 15 years in marketing—from the music industry to tech education—and she's learned one simple rule: always start with a real story. AI can help you scale, refine, and repurpose. But connection? That begins with something human.Together, they explore how to build a content engine powered by AI while keeping your brand voice intact, your standards high, and your audience at the center.If you've ever worried that AI might dilute your message, this conversation will reframe how you think about it—and give you a practical path forward.What you'll learn in this episode:Why authentic content always starts with real customer storiesHow to turn one podcast into blogs, social posts, and short-form clips using AIThe practical way to train a custom GPT on your brand voice (without getting technical)How to use AI as a collaborative editor—not a replacement writerWhat to do when AI output misses the markHow to measure connection beyond clicks, shares, and impressionsWhen it's better to delay content than publish something mediocreHow to balance consistency with quality on a content calendarWhy sometimes the smartest marketing move is to stay quietAbout Mandy ArolaMandy Arola is the Director of Marketing at Nashville Software School, where she leads strategy and execution across content marketing, brand messaging, and community engagement.With over 15 years of experience, Mandy began her career in the music industry, spending a decade working alongside marketing teams before transitioning into the technology education space. At Nashville Software School, she has built and executed content strategies both as a team leader and as a solo marketer—proving that strong strategy and thoughtful execution matter more than team size.She specializes in creating story-driven marketing that connects online and resonates offline. Her work bridges AI-powered efficiency with deeply human storytelling.Connect with Mandy:Mandy's LinkedIn ProfileNashville Software SchoolText us what you think about this episode!

In this episode, we unpack a viral AI essay that compares today's AI moment to February 2020 the calm before global disruption.The author argues that AI has entered a new “phase change.” That systems like GPT-5.3 Codex and Claude Opus 4.6 are no longer just assistants, but autonomous agents capable of planning, executing, and iterating complex work independently.But is this reality or hype?As UX designers, we don't need panic.We need perspective.In this episode, I explore:What the viral article actually claimsWhy it's spreading so fastWhat “agentic AI” really meansHow leading voices are reacting — from optimism to skepticismAnd how you can prepare long-term as a designer in an accelerating worldThis isn't about fear.It's about clarity, adaptability, and momentum.Here are some of the voices referenced in this episode. I highly recommend exploring their work and forming your own opinion:Matt ShumerFounder & AI entrepreneur. Author of the viral “February 2020 moment” essay.Nate B. JonesAI commentator discussing the “phase change” toward agent swarms and autonomous systems.YouTubeAllie K. MillerAI advisor and former Amazon AI leader. Talks about “information asymmetry” and hands-on benchmarking with advanced AI systems.LinkedInAnn HandleyMarketing leader and author advocating against AI panic — emphasizing human judgment and relationships.LinkedInGary MarcusAI researcher and cognitive scientist offering a skeptical counterpoint on reliability and hype.SubstackAI for Designers: 5-week Bootcamp

In today's episode of the RattlerGator Report, JB White conducts a live read-through and reaction to a powerful essay by Matt Schumer detailing the rapid acceleration of artificial intelligence. Framing the moment as a “February 2020” style inflection point, JB walks through Schumer's firsthand account of GPT-5.3 Codex and Opus 4.6, highlighting AI systems that now write code, debug themselves, iterate independently, and even help build their own successors. The discussion centers on exponential growth, task-duration benchmarks, AI-assisted model training, and projections that superhuman capability across most cognitive work could arrive within just a few years. JB expands the conversation into geopolitics, energy infrastructure, Elon Musk's role in robotics and satellite systems, and what AI dominance could mean for military, economic, and cultural power. He also ties the technological shift to 2026–2028 political positioning, global alliances, and internal GOP battles, arguing that America's strategic advantage depends on recognizing the scale of change underway. The episode blends technological urgency, political forecasting, and philosophical reflection on generational responsibility in the face of accelerating transformation.  

Hard truth: You need to level up your Ai Skills and this weeks epiosde is going to show you 7 ways you can do that. No tech. No crazy 30 steps. Things you can do in your small business today. Most pet business owners are either ignoring AI or just using it for basic tasks, but I'm here to up-level your thinking and show you how to shift your mindset to achieve your goals faster. In this episode, I'm breaking down seven practical, straightforward ways you can use AI right now to save time, increase trust with your clients, and stop the "content slop" madness for good. In This Episode You'll Discover Boost your local ranking by replying with pet names and service-specific keywords. Use AI to find exactly where your site fails to answer client questions. Build instant trust by answering questions before they are ever asked. Stop hiring "warm bodies" with personality-driven ads that attract top talent. Turn one client email or blog into ten high-quality social posts. Use your "Sent" folder to build a document that ends repetitive emotional labor. Let AI analyze your competitors to find their weaknesses and your competitive edge. Timestamps 08:18 – Use AI to find the "missing answers" on your site that are costing you sales. 11:36 – Create a "What to Expect" guide that closes deals before you even speak. 14:45 – Stop running ads; start writing talent magnets that filter out the fluff. 18:13 – How to turn one high-value insight into 10 strategic, high-quality posts. 23:30 – Turn repetitive emails into a permanent FAQ to reclaim your emotional labor. 26:15 – Use AI to spot your competitors' weaknesses and exploit your strengths. Notable Quotes "Every negative review, you're actually not responding to them, you're responding to everyone who's ever gonna see it for years to come." "I can tell you how successful or unsuccessful you're gonna be based off of where you're spending your time." "It's not AI [that will ruin the world], it's the people that understand how to use AI the right way." Resources and Links Get organized and stop the resume chaos. Click here to try my favorite applicant tracking system: Breezy HR (ATS): bellavasta.com/breezy If you want to know what your competitors are really saying, you need my phone sales script exercise Want the exact prompts for every strategy I shared today? Join our community and let's make your business fly: Jump Consulting Mastermind: (Use code BELLA25 for $25 off!) Have a specific question or need a partner hookup? Shoot me a message directly: bella@bellavasta.com Transcript Welcome back to another episode of Bella in Your Business. Today we're going to talk about seven things that AI can do for your pet business this week that you probably didn't think of. Now guys, I think this is really, really important because I've been seeing people use it, but like use it at a very kindergarten level, not in elementary, middle school, high school, or dare I say collegiate level. Okay. And I'm here to up level your thinking of what is actually possible. And hopefully by the end of this episode, you're going to have a lot of different ideas and I'm going to change your mindset slightly. That's always my goal in everything that I do is to shift your mindset, to think bigger, think more strategic and achieve your goals faster. So most pet businesses are like, they're either ignoring AI, complaining about AI and I'm not even gonna go into that and I give that any life, okay? But I wanna talk to you who you feel like you're using it every day. Maybe you have it on your phone, you have it downloaded, you talk to it all the time, you feel like you're getting a lot from it. Harvard actually just came out with a study that people are actually more busy because of AI, because they're not, especially a chat GPT, which is one of the reasons why I kind of broke up with them. It's always like, well,

During Scripting Fridays on the Agent Power Huddle, Ed introduced an exciting opportunity for agents: REMLO (Real Estate Mortgage Loan Officer). Drawing from his 30+ years in real estate and mortgage lending, Ed shared how agents can become licensed loan officers through Texana Bank, creating an additional income stream while continuing to practice real estate. The program allows agents to originate loans with the support of a dedicated loan partner, earn 50–60 basis points per transaction, and operate nationwide under the bank's federal charter. Ed emphasized the streamlined onboarding process and the strong compliance structure in place. The discussion also covered practical considerations—from managing inspections and underwriting communication to addressing lender pushback and RESPA concerns. Ed reinforced that the program is fully compliant and positioned as a value-add service for clients. The session wrapped with a reminder that opportunities like this are about diversification, service, and long-term growth—plus a look at Ed's custom GPT tool, WhatWouldEdSay.com, for scripting and strategy support.

If you're like most people, you've probably got dozens (maybe hundreds) of chats with generic titles like "marketing ideas" or "content strategy." And when you need to pick up where you left off? Good luck scrolling through that mess.Here's the thing: ChatGPT is incredibly powerful. But, if you're not organizing your conversations intentionally, you're making it way harder on yourself than it needs to be.That's why I basically live inside ChatGPT Projects. In this episode, I'm walking you through exactly what Projects are, how they're different from custom GPTs, and how you can set them up to get way better results from AI.We're also covering some recent changes OpenAI made to memory settings (which I just discovered by accident last week). So grab your notebook for this one!In this episode, you'll learn:What ChatGPT Projects actually are (and why they're different from custom GPTs)The #1 problem most people have with AI—and how projects solve itHow to set up project-specific memory so your contexts stay clean and separatedMy exact workaround for retroactively fixing memory settings in existing projectsWhen to use a project vs. a custom GPT (with real examples from my business)How I use projects for business strategy, speaking prep, and even personal stuff (like my husband's 40th birthday Jeopardy game)Pro tips for managing, naming, and auditing your projects over timeWhy pulling bots into projects is a secret weapon for chaining tasks togetherReal-world examples I share:

OpenAI's hottest app isn't ChatGPT—it's Codex.In the last few weeks alone, the Codex team shipped a desktop app, GPT-5.3 Codex (a new flagship model), and Spark, the fastest coding model I've ever used. Usage has grown fivefold since January, and over a million people now use Codex weekly. Codex was also the app that OpenAI chose to run an ad for in the Super Bowl.Dan Shipper talked to Thibault Sottiaux, head of Codex, and Andrew Ambrosino, a member of technical staff who built the Codex app, for Every's AI & I about what OpenAI is building and how they're using it internally.If you found this episode interesting, please like, subscribe, comment, and share! Want even more?Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It's usually only for paying subscribers, but you can get it here for free.To hear more from Dan Shipper:Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Head to granola.ai/every and get 3 months free with the code EVERY.Timestamps:  00:00:00 - Start00:01:27 - Introduction 00:05:27 - OpenAI's evolving bet on its coding agent 00:09:42 - The choice to invest in a GUI (over a terminal) 00:20:38 - The AI workflows that the Codex team relies on to ship 00:26:45 - Teaching Codex how to read between the lines 00:28:45 - Building affordances for a lightening fast model 00:33:15 - Why speed is a dimension of intelligence 00:36:30 - Code review is the next bottleneck for coding agents 00:41:24 - How the Codex team positions against the competition Links to resources mentioned in the episode:Thibault Sottiaux: Tibo (@thsottiaux)Andrew Ambrosino: Andrew Ambrosino (@ajambrosino)Every's vibe check on everything the Codex team launched: OpenAI's Codex App Gains Ground on Claude Code, GPT-5.3 Codex—The 10x Engineer, Now More Fun at Parties, AI as Fast as Your Train of Thought

Struggling to know whether you can trust AI for garden planning? Wondering if ChatGPT can actually help you grow better vegetables—or if it might quietly steer you wrong? In this episode, we talk through the real benefits and real risks of using AI in your vegetable garden. Dream to Garden – Plan your garden faster with AI tools without giving up your own judgment. Learn the why behind your planting decisions and get step-by-step guidance plus custom GPT support.

As property management faces rapid technological disruption, what happens to the businesses that refuse to adapt… or the ones that go all-in on AI and eliminate the human element entirely?  In this episode of the #DoorGrowShow, Jason and Sarah Hull sit down with Joe Oliveri in Brisbane, Australia to unpack the accelerating AI revolution and what it means for the future of property management. With over 30 years in the industry and 16 years as an international real estate business coach, Joe shares why he believes the next three years will determine which companies survive, and which disappear.  They explore the shift from traditional property manager roles to data-driven client relationship managers, how AI can transform processes like lease renewals, the risks of deepfakes and security threats, and why the winning formula will be a strategic blend of technology and human connection.   You'll Learn (00:00) Introduction to AI in Property Management  (00:40) The Evolution of Property Management  (01:58) The Impact of AI on Property Management  (05:35) Integrating AI with Human Interaction  (10:30) AI's Role in Tenant Management  (14:17) The Need for Verification in AI  (16:30) The Future of AI in Property Management  (21:44) Consequences of Ignoring AI  (25:43) Finding Balance: AI and Human Roles Growth  Quotables "If this industry does not change and truly understand AI, we're going to be irrelevant." "Three years is all we've got to make the changes."  "AI isn't something that they can go back to their office and say, we're going to build this AI. Let the experts do it." Resources DoorGrow and Scale Mastermind DoorGrow Academy DoorGrow on YouTube DoorGrowClub DoorGrowLive Transcript Jason Hull (00:00) that companies will need to be able to make to keep up and really frankly, survive. It's recording.   We can time up. Shifts in layout. Let's count. All right. You think it's going to work there or should we hold that? Well, we'll probably have to do this. All right. Cool. No introduction. Well, no. Just do it. I'm saying not the full intro that you normally do the way you read the entire thing. Just do a quick. You're not going to have all that when we're going to send it. OK. Do an intro, but you're not going to do the normal intro. All right.   Put those somewhere. Hang them on your shirt or do something. Okay. That's very Brisbane. Well you have to fit in. When in Brisbane, do like Brisbane. Right, so we are... It wasn't pretty. Okay. Five, four, three, two... If you can see the camera, it can see you.   Can you see the camera? can. You don't... can. Okay. Alright, you ready? Five, four, three, two, one. Alright, so I'm Jason Hull. This is Sarah Hull with DoorGrow and we are Hangout with Joe Oliveri. And we're in Brisbane. Brizzy. Brizzy, yeah. And you can't see but we're overlooking the beautiful city and the river right now.   And what is this, a wine room? Yeah, this is our wine cellar. Private wine cellar. Private wine cellar. Okay. And so we're going to be chatting today about AI, the future, and how that's going to impact and affect property management. So, Jill, why don't you give people a little bit of background on yourself and who you are and how you got into property management.   Yeah well that's a long story but I'll make it short. So I've been in the industry for about 30 years now so it makes me feel old when I say that. ⁓ But for the last 16 years I've been a real estate business coach and I've been lucky enough to coach people in Australia and the USA so I get a really good oversight of what's going on in the world. ⁓ But you know my focus for the last 16 years has been   where is this industry going and how can we help businesses to get there and what do need to do? So basically, yeah, for the last 30 years, I've been doing property management and yeah, I think it's exciting where it's heading and through that journey, I met you guys, which is wonderful. So yeah, yeah. Yeah, fantastic. We've been able to have you out at one of our conference events and have you speak and yeah, it's been delightful.   ⁓ I know, I mean, in 30 years, you've seen a lot of changes, but it's speeding up. Like we're in the middle of this AI revolution right now. Everything's changing dramatically. And so what are some of the things that you're noticing? And you have a process software called Thrusos, which we use to run our own operational side of our business. ⁓ What are some of the things that you are right now?   thinking are going to happen and you're trying to figure out. Yeah, well, I'm actually concerned about the future for property management in a positive way. If you can kind of like say that. Because what I'm seeing is we are going through rapid change. I remember when I started in the industry 30 years ago, we were just introducing property management software. Everyone was still using spreadsheets and you know.   paper documents and all sorts of things. ⁓ Carbon copy leases, know, that's how far back we go. And there was major pushback on property management software. And the pushback probably took about five years for the industry to completely transition to understanding you had to use software. Well, we don't have the luxury of five years anymore because my belief is it's changing so rapidly.   And it's the consumer expectations that are going to force change that if this industry does not change and truly understand AI, we're going to be irrelevant. So I believe in three years time, we're going to see completely different roles in the way that we do things. in the next, like leading up to that three years,   I believe that in the first year, we're going to see probably about 40 % of businesses starting to struggle and disappear. They're losing managements, clients are going elsewhere because they're expecting AI and seamless processes and interactions and tasking. And then that will speed up. And by the second year, we'll see 80%.   And then we'll only have a small percentages. I know this seems like doomsday, but it's a reality. Only a small percentage of existing businesses that are around today who will be around in three years time. If they do not adopt AI and AI is very broad. So they've got to understand AI, but you know, that's my belief. That's what I'm seeing as well. So yeah, you know, we've got to sit up and take notice.   Yeah. And I think a lot of the things that I've been noticing, some people kind of shift right away and some people are a little bit more reluctant to shift. Yes. And I think the ones that it's almost you need to find the balance. You don't want to go all in and all AI and you don't want to have no AI. You want to kind of find the right balance and that happy medium and really figure out what is the best way to utilize AI.   and have a human component. Because I do not believe it will be able to be all AI. I just, think when it really comes down to it, it is a relationship business. It's a human to human contact business. really when things go wrong, humans want to talk with other humans who understand. They don't want, have you ever been on the phone and you're going, agent, agent, representative, and it's not.   understanding and you're like, just get me to the human. do I, what button do I need to push? What option is it that I the human? And I think that will continue, that will prevail. However, AI is such a powerful tool that I think we just need to figure out what's the most complimentary way that the humans and the AI can interact together to provide an amazing experience so that the tenants are happy and the clients are happy and the property management business is happy.   really be able to figure out what's the best way to do this. And something that you were telling me yesterday, I went, ⁓ she is so smart for doing that. Can you talk a bit about your, ⁓ tell us first about Flusos and what it is and how it works. And then tell me what you were chatting with me about at dinner last night about what you're going in and updating in Flusos because of all of the advancements in AI that are happening.   Yeah, yeah, so you're 100 % right Sarah, you know, there will always be the human element. It's necessary. We're a service business. So people want the customer relationships. They want that person who lets them know, hey, this is all right. You know, we're going well here. But the role of the property manager has changed. There will always be a role for property managers, but not in the way that we see it today.   And that's where we've got to make that transition. But one of the simplest flows to talk about, when I talk about flows, Flusos is workflows on all of the various tasks that we do. To help people understand how AI integrates with the human side of property management is if we look at a tenancy renewal. So when we're doing that renewal, there's so much that AI can do that takes away that   you know, that personal kind of like input ⁓ into the task as in like if a property manager doesn't like a tenant, then you know, like it becomes personal. ⁓ If they do like the tenant and they've built this relationship with the tenant, where the tenant is making them feel like if the rent goes up, that the tenant will lose the home, the property manager gets too involved personally and emotionally.   So to take away that very personal and emotional element and deal in the facts, if we look at, you know, a tenant renewal, AI has the ability, and this is what we're building into Flusos. So AI has the ability to go through and say, these renewals are due. It will then look at the tenant history to say, you know, how's the tenant pay the rent on time? Let's look at the in-resident inspections that we've done and we can see that the tenants   looking after the property, abiding by the terms and conditions. Everything's going great. We can see in the system where the tenant has, you know, kind of like mentioned that they would like to renew, that their children go to the local school and they want to stay there through the primary. We've got all of this data that's built up. So AI will be able to go in and say, yeah, you know, like this tenant has mentioned they want to stay on. We look at their history. It's all good. We're also going to look at the market.   And the market is determining that we can increase the rent to this much or it stays, it remains as it is. And we should offer a lease term of this length because AI will be able to determine what's going on in that marketplace. There could be infrastructure rebuilds going on, which could push people away from moving there. You know, just because we've got infrastructure being built, there is a building period that turns people off.   So AI can look at all of that and then say, okay, this is what we should offer the tenant. Now, the property manager then looks at that and they can say, well, you know, this owner has this property as a ⁓ full-time ⁓ or permanent investment property, but we need to talk to them and say, hey, as an investment property, this is where we recommend that you, you know, take the property, increase the rent, offer renewal because of this.   ⁓ And then the owner can make a decision. Now AI jumps in, does all the lease renewals, sends off the documents, updates the system. And the property manager's next role is talking to the owner and saying, congratulations, the tenants have signed the renewal. AI has then given them updates on your property is now achieving this in comparison to market. This is what the increase means to you in terms of dollars and percentage.   And we become that voice of, you know, like ⁓ reason and congratulations and service. And the owners look to us for that because all the information that's given to them is not based on personal, ⁓ you know, thoughts on what's going on or emotion. So, yeah.   And it makes it seem either that's the thing. No, I guess not. Oh, I think they're building over there. So maybe it'll be good and yet they're supposed to build a new stadium and that'll bring in. It's really figuring out things that we just don't know what the impact will truly be. And I love that it's kind of like, OK, have the human monitor the AI and have the AI do the heavy lifting.   and then you kind of watch it, make sure it's doing the right thing, and then you get to be the human to human connection. Exactly. Let me be the one who calls the owner, but AI has done all the things for me, so it's kind of prepped it, gotten it ready, wrapped it up in a pretty package that now I can present to the owner, and I get to be almost a bearer of good news instead of the bearer of bad news. Exactly, exactly. And know, owners don't want to hear that you should renew the lease because they're a good tenant.   Well, what constitutes a good tenant? They have to pay their rent on time. They have to look after the property. They have to look after the garden. So they've got to abide by the terms and conditions. It doesn't mean they're a good tenant. So owners don't want to hear that. The owners want to hear that they've abided by the terms and conditions. So we see no reason why they shouldn't be offered a renewal. I think one of the interesting challenges that are   that's going to come with AI is that AI can make anything now. I can take a photo of you, I could use AI to make you say stuff and match your voice. And so the danger with AI is that I think we're gonna get to the point where people will only trust human in-person interactions to begin things or to end things or just, you know. And so there's gonna have to be this human element of verification unless there'll probably be some people that work this out.   like some sort of verification system. You can load it up on your phone and verify that this is a real thing that you're talking to on Zoom or something. you know, that with all the AI slop as they're calling it and all of the fake videos and it's now becoming nobody believes anything. And so it's hard to know, is this really true? Is this actually the property manager that I'm talking to that is, you know,   that I have this property and I'm the owner and you know, are they real? And so, am I giving them access? And so I think there's gonna need to be some sort of verification system in order for people to trust because people will trust, I think it'll get to the point where we'll just trust this. Like I can shake your hand, I can touch you, I you're real.   I mean, we might all be fake on the I you don't know we just took a photo and write the whole podcast and do it and yes But they're really in Ulston That's right. Yeah There's been so much that's happened with deep fakes there've been yeah millions of dollars scammed and Now there's it it's getting so aggressive   that it's recommended that if you are a human that recommends or that interacts regularly with another human, like you and your husband, for example, or you and your children, that you have a a safe word, a password, a verbal safe where if you get a phone call from what looks like and sounds like your daughter saying, mom, I'm stuck on the side of the road, please send me money, I need help, what's the word?   What's the word? And then you know if that word isn't said, that is not my daughter even though it looks like it sounds like it. And I think that's going to be something that we need to kind of incorporate as well and for that reason I agree. I think that in-person, personal relationship will be more important than ever. Yes, I agree with that and this is something that's interesting you bring that up because I always had a safe word with my children. It was given. ⁓   It's something that I think property managers take for granted. They call owners and tenants and talk about all sorts of things without any sort of security check. So, you know, like if we're talking to the banks or, you know, anyone, we get a telecode or we've got to like key in what our personal sort of verification. Exactly.   So I think that's another area, and I'm glad you brought that up because it's another area where industry has to step up. We've got to protect the data that we've got. We've got a lot of sensitive data there. So we've got to really look after that. But there will always be that human element in property management because people want to know that they're making the right decision. People want to chat about it. They want to go through and say, based on that data,   would I be wrong in increasing the rent? It's like, no, a property manager is like, that's what the market is determining. So if the market determines a rental increase, then that's what the market is saying. Holding back rent only impacts every other investor in that market. I think it'll be interesting. So I think moving forward in the future, if we start to leverage AI, but we build our processes around things.   you know, initiated in a way that it starts with a human and that sensitive touch points are done as a human and that we come up with our own verification methods, we're going to avoid some of these traps and our processes will have a longer life span. Yes, yes. You know, we won't have to, man, we have to change everything now with the, all these scammers are doing this one thing where they call up and pretend that they're you, you know.   And so, yeah, because you can go on 11 Labs right now. You can upload your little recording of your voice and then you can have your voice and you can have it say anything. so, yeah, so I think that's going to be a challenge. And I think we're going to have to figure out a way to how do you how do you on a Zoom call with a remote owner that's out of state or out of country verify that each of you are an actual   real physical human being. Somebody needs to invent that device that verifies it's like taking a blood sample. It's like they're human and it's it's like, this is the, this is actually Joe I'm talking to across the pond. So yeah. Okay. Yeah, it is important. And I think the other thing for the industry to understand is that, you know, AI isn't something that they can go back to their office and say, we're going to build this AI.   ⁓ Let the experts do it. Let the experts who understand process and know, Sarah is a real expert on process and to have that level of expertise, it takes a lot of knowledge and a lot of like building and rebuilding and understanding and it's tweaked, you know, for different companies. But you know, like they shouldn't be taking this on themselves. Let the experts do it. And when we talk about, you know, our tech.   We need tech stacks and there is a lot of different technology out there that we've got to build it all in together. Property managers can't do that. A lot of business leaders can't do it either. know, have faith in the experts. That's what I'm saying to the industry is have faith in the experts because, you know, they are doing a lot of work behind the scenes on making sure that AI is not a negative.   impact to the industry is only making our industry sustainable and relevant into the future. mean that's going to be one of the temptations and dangers is that anyone can now go create any software. can load up lovable or any of these other tools and they can say make me a CRM or make me a property management software. But yeah the problem is you then have to become some sort of expert that's constantly communicating, fixing bugs, tweaking it, figuring it out.   And if you can't or something breaks or something gets hacked, then you're at risk. Your whole business is now at risk. And yeah, so I think that, but in the future, everybody will be able to create anything. So I think the people that really thrive and survive and keep a job while AI kind of takes over, I believe will be those that are the artists.   So we're going to shift away from it being about being a nerdy programmer. It's going to be those that have this creative thinking that they can think, how can I combine these tools? How can I connect these? How can we innovate this? And that's been one of the most fun things for me in playing with AI is now I get to be an artist with building systems and building things and creating things. Cause I can create things so quickly. Whereas before I would just think about all the things I wanted to do. And I'd be like, that'd be nice if somebody made that. And I'd be like, that's way too much work.   I don't want to do that. but yeah, it's now you can just create anything and you can edit things quickly. You can have things reviewed. And so there's a lot of things that everybody's probably already using some of the AI tools right now, you know, like chat GPT and maybe Claude and perplexity and some of these things, but there's a lot of, you know, more advanced tools that are coming out that are going to make things even faster.   And now AI is building AI and things are just speeding up.   Jason Hull (22:01) is that we're gonna have a lot of tenants out of work. I think there's gonna be a lot of tenants that are like, hey, I just lost my job to AI. And so we've already replaced some roles and some functions of our team and maybe even a whole team member with some AI tools already. And so that's coming very quickly. And I think Elon Musk just said that   in the next three to five years, the best surgeons in the world will be robots. And those are high paying, high functioning jobs that people put a lot of effort into, but he says they'll be better, more accurate. And so, do you want a really seasoned, older surgeon with maybe, he's human steady level hands, or do you want somebody that has laser precision that gets it right every time that's overseen by that person?   I think the best blend is both. I want the AI laser precision with the human with all of the knowledge and experience to watch it and make sure that it's the right thing. if you did it that way, if a doctor just had a monitor, it eliminates the need for many of them. You now need one doctor to...   multiple AI robots. Because you've got beta. think everything that's going to shift, AI is going to change so many things, which is great. It's still not going to be able to, I mean, how comfortable would you feel? Open heart surgery and that's the AI robot and you go, ⁓ do I want that thing cutting me open? ⁓   What's its track record? What if it glitches? What if it breaks down? Is it going to do the right thing? it know? What is it, you know, is it programmed? What if it dies in the middle of the surgery? Does it have a battery? There's a lot of things to think about. And does it care? Right. is it, what if it that eye robot where it's scanning and going, oh, it has an 11 % chance of survival. I'm done. Well, wait a second. Hold on. Do we, you know, do we keep going? So I think everything is going to come down to a blend.   of AI and human and there's got to be both of those components. So can you maybe chat about, let's chat about kind of both ends of the spectrum here. What might happen to some property management companies that refuse to adopt AI? Where they go, I'm just not doing it. I'm not using AI. I'm staying old school. We don't want to learn anything. We don't want to do anything else. might you be a, what would you think the prediction would be on companies that just will not?   Yes. Use it. That's a really good question because we kind of saw that with what happened with these old school companies ⁓ where they refused to have anything but the property management program, you know, where you store your data. ⁓ And they eventually were out of business. I mean, I'd go into these offices and they just have   files everywhere, files covering the desk, they didn't know where anything was. But they refused to, you know, ⁓ use anything else than go to that paper file. And it was a mess. mean, how do you find paper? ⁓ So we saw those businesses gradually get out of business. They didn't have a business to sell, basically. So they might have been mighty in their day, but they were no longer mighty when technology just   over. Now that took a long time to happen in the past. It's going to be more rapid now. So those businesses that refuse to adapt or adopt AI or understand it because a lot of them think we've got AI. It's like you don't have AI. GPD does not help you to manage process better. So if they don't then   We're seeing it already Sarah and Jason. We're seeing that these companies that used to manage 500 or more managements are down to half of that and I'm selling one at the moment where they had 600 and we're just on the final figures today. They're down to 342. That's a lot of money that they've lost because they refuse to adapt new methods and they let the property managers determine   what technology they would use. Because what happens if we allow staff to determine what technology we will use, then the staff just create or justify a reason for their position. We can't do that anymore. We've got to identify the task that a property manager does. And there's much less than what, you know, they did in the past. A property manager is basically just a client relationship manager now.   They're reviewing data and interpreting that data to have conversations with the clients. And that's the way we've got to do it. And the other thing is, investors are changing too. So we're getting a lot of institutional investors. So institutional investors don't want to deal with, you know, mother head and type, you know, like, ⁓ the tenants are lovely and you know, you don't want to lose them and...   you probably can't afford to do the maintenance and things like that. Institutional investors just want the facts so they can make a decision and quite often they don't want to make a decision they want the property manager to do what's needed. And AI will determine the necessary steps so the property manager becomes that person this has been done or they can look online through their portal. in   I'm like, that's a long answer to your question. But you know, like I believe hand on heart and don't want to seem like I'm doing so sorry, I'm hitting the mic. that three years time is three years is all we've got to make the changes and to identify the tasks the property manager does. Because it's not the same anymore. I agree. And I think it's about shifting that shifting. It's about making that shift.   And then conversely, let's talk about the other end of the spectrum because, okay, if you go, you know what, I'm sold, I'm doing everything AI. I'm firing my entire team, I'm letting AI do everything and we've seen some companies try to do this before, but now there's a lot of changes and AI can do a lot of things that before was not possible. So what would you say to the companies that are gonna go all in and they're gonna do all AI? Is that the solution?   No, it's a happy blend of technology and team. So if you don't have the team there, property management is a service industry. So we have to remember that, you know, and our service is helping the clients to feel confident about decisions that they're making or instructions that they're giving. ⁓ So it is definitely a blend of ⁓ technology and team.   but the team's role has changed. please don't think you can go in there and chat GBT is going to, you know, create all the conversations and, and, know, they're going to answer the phone and, and, you know, talk to the client and record it all. No, there needs to be human element. But again, I'll go back to it's the experts that will help you create that because it's very, very difficult to understand how to blend that technology and team. ⁓   without the kind of like the team having their say in it too. A lot of business owners let the team say too much and they make decisions based on team. We've seen that, or they take a vote. A vote, yes. My team, I hear that from our clients, and they go, well my team voted and what? Your team voted? No, no, no, no. that's good. They don't ever vote. Like, yeah, you know, eliminate my job. I'll vote yes for that. Yeah, yeah. No, no.   Yeah, the challenge with team members is that they are not usually money driven the way entrepreneurs are. They're not focused on the money side of the business and they're focused on safety and security. And as AI comes, that's going to take a lot of that away. And so yeah, you don't want to have your team vote. This is, it's not like a   It's not democracy. No, this is business. I believe in democratic principles, it's the business. But yeah, you can't place the burden of decision making on people that are wired to make decisions in a way that's not conducive. Yeah, it's all about them. And, you know, like it's important to understand how the team is thinking so that you can then help them adjust to it or no.   that person's not going to come through with me. So you can make the decisions. no, know, team will always justify why they are needed in a business. Yeah. mean, the day may come with all the AI stuff and humans really, we tend to like each other. We like humans a bit. You know, we'll probably have labels on our business made with real humans. Real humans at our business and a real human answers the phone. No AI. You know, I mean, it might happen. So that could be interesting. So.   One of the things that I also though, am thinking and maybe I'm a bit of a conspiracy theorist or a little crazy, I don't know. But ⁓ when Trump went into Venezuela and extradited or took out that dictator that had taken over the government there and was causing a lot of problems, the people were very happy. But what was really interesting, what was unsaid or I didn't hear people talk about it much is the US government.   Military whatever went in had the ability they turned off all the power to the entire city There were not even backups were working everything went out and went black. Mm-hmm and That's wild to think that we have the ability to just wipe out power and electricity I don't know if it was an EMP thing or Some people say solar flares can do this and maybe the government can do this kind of stuff. Who knows but the fact that technological   data, power, electricity, all that can just shut off in an instant. How would we deal with that in a world where everything has become digital and everything has become AI? Will we have backups? Will we have keys? Will we be able to find things? ⁓ Will we know stuff? there's, think there, I mean, if that happens one time, it will be like change everything forever. Just like the pandemic changed everybody's perception forever about.  

Get our AI Video Guide: https://clickhubspot.com/dth Episode 97: How close are we to a world where AI-generated videos are indistinguishable from reality? Matt Wolfe (https://x.com/mreflow) and Joe Fier (linkedin.com/in/joefier) dive deep into Seedance 2.0—ByteDance's new AI video model that could outpace giants like Sora and Veo. Joe, a marketing and business expert known for his hands-on approach and insights into AI's rapid evolution, helps to break down the five most fascinating developments in the AI space this week. They tackles game-changing AI advances: Seedance 2.0's mind-blowing video generation for ads and motion graphics, the rollout of Google's Veo 3.1 in Google Ads, the GPT-5.3 Codex Spark coding model built on specialized inference chips, Gemini's DeepThink model for scientific research, and the early rollout of ChatGPT ads. Check out The Next Wave YouTube Channel if you want to see Matt and Nathan on screen: https://lnk.to/thenextwavepd — Show Notes: (00:00) Seedance 2.0 arrives – AI video generation blurs reality, ad creation moves fast. (03:03) Google's Veo 3.1 powers video ads, advertisers can now generate clips directly from image uploads. (05:33) Comparison of Runway, Kling, Veo, and Sora—head-to-head prompt showdown. (07:00) Motion graphics and explainers—AI's take on the creative industry. (08:35) US vs. China—Copyright, IP, and training data debates. (12:10) Deepfake and video authenticity—why we now default to skepticism. (13:30) Google's edge in visual AI via YouTube's massive corpus. (14:39) The next frontier: Longer, more consistent video generation. (15:14) Where do humans fit in? Taste, storytelling, and creative direction. (18:30) GPT-5.3 Codex Spark—coding models on Cerebras inference chips, demo generating a website in 18 seconds. (24:34) AI tool comparisons—Codex vs. Cursor vs. Claude Code. (25:12) Speed as the key bottleneck breaker in creative and technical workflows. (28:02) Google's Gemini DeepThink—state-of-the-art research, advanced coding and physics capabilities. (32:52) Gemini demo attempt—3D-printable STL file and solving the three-body problem. (33:20) ChatGPT rolls out ads—impact on monetization and user trust. (40:02) Google's ad history—how “sponsored” is becoming harder to distinguish. (44:02) Democratizing AI access via ad-supported models. (45:03) Matt Schumer's viral article—why AI is moving even faster than most people realize. (51:11) Tools that build tools—AGI's path and the new role for humans. (53:12) Real-world skills and taste—where humanity still wins (for now). (54:01) Final thoughts—wake up, pay attention, and stay on the leading edge. — Mentions: Seedance 2.0: https://www.seedance.com/ ByteDance: https://www.bytedance.com/ CapCut: https://www.capcut.com/ Veo: https://deepmind.google/models/veo/ Runway: https://runwayml.com/ ChatGPT Codex: https://chatgpt.com/codex Matt Schumer's Viral Article: https://www.mattshumer.com/blog/ai-changes-everything Super Bowl Claude Commercial: https://www.anthropic.com/news/super-bowl-ad Get the guide to build your own Custom GPT: https://clickhubspot.com/tnw — Check Out Matt's Stuff: • Future Tools - https://futuretools.beehiiv.com/ • Blog - https://www.mattwolfe.com/ • YouTube- https://www.youtube.com/@mreflow — Check Out Nathan's Stuff: Newsletter: https://news.lore.com/ Blog - https://lore.com/ The Next Wave is a HubSpot Original Podcast // Brought to you by Hubspot Media // Production by Darren Clarke // Editing by Ezra Bakker Trupiano

El programa 2825 de Radiogeek, les habló de varios temas importantes. YouTube sube la apuesta – Ahora oculta comentarios y descripciones a quienes usan bloqueadores de anuncios; Apple confirma evento para el 4 de marzo – El regreso del MacBook de 12 pulgadas y el debut del iPhone 17e; Los Peligros de la IA Generativa y el Desafío para los Influencers Reales; Especificaciones y precio del Google Pixel 10a confirmados en la última filtración; Android recibirá una nueva función de copia de seguridad de archivos locales a través de Google Drive; X está caído de costa a costa en EE.UU.; ademas OpenAI retiro el lenguaje GPT-4o. Toda esta información la pueden encontrar desde nuestra web www.infosertec.com.ar o bien desde el canal de Telegram/Whastapp, o Instagram. Esperamos sus comentarios.

How do you find employees who care as much as the founders? And in an AI-driven world, should you stick to traditional SEO or pivot to Answer Engine Optimization (AEO)?In this episode of Building MarsBased, CEO Alex Rodriguez Bacardit answers two deep-dive questions from the agency community. We explore the "Champion" profile, why former freelancers and entrepreneurs are the secret to delegation, and how MarsBased hit 30 people in 2025 by restructuring their leadership.We also discuss the marketing strategy behind their new spin-off, GPT apps. Alex explains why they are using paid ads for the first time in 12 years and how to optimize your content so AI bots recommend your brand.Support the show

OpenClaw's meteoric rise—from a weekend Claude experiment to the fastest-growing open source AI project in the world—just culminated in Peter Steinberger joining OpenAI to build the next generation of personal agents. This episode unpacks the agentic inflection point, why OpenClaw became the Schelling point for builders, what Anthropic may have fumbled, and what it means for multi-agent futures, coding models, and the broader AI power struggle. In the headlines: GPT-5.3 Codex Spark's speed play, Google's upgraded Deep Think agent, DeepSeek V4 rumors, and Anthropic's $30B raise.Want to build with OpenClaw?LEARN MORE ABOUT CLAW CAMP: https://campclaw.ai/Brought to you by:KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.kpmg.us/AIpodcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Rackspace Technology - Build, test and scale intelligent workloads faster with Rackspace AI Launchpad - ⁠⁠⁠⁠http://rackspace.com/ailaunchpad⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠https://blitzy.com/⁠Optimizely Agents in Action - Join the virtual event (with me!) free March 4 - ⁠⁠⁠⁠⁠⁠⁠⁠https://www.optimizely.com/insights/agents-in-action/⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LandfallIP - AI to Navigate the Patent Process - https://landfallip.com/Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Agent Readiness Audit from Superintelligent - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://besuper.ai/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠to request your company's agent readiness score.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/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai

Former NPR host David Greene sues Google for allegedly replicating his voice in NotebookLM, Western Digital reveals 2026 capacity is already booked through, and OpenAI officially discontinues access to the GPT-4o model. MP3 Please SUBSCRIBE HERE for free or get DTNS Live ad-free. A special thanks to all our supporters–without you, none of this wouldContinue reading "Former NPR Host Sues Google Over ‘Stolen Voice’ – DTH"

Our 235th episode with a summary and discussion of last week's big AI news!Recorded on 01/02/2026Hosted by Andrey Kurenkov and Jeremie HarrisFeel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:* Major model launches include Anthropic's Opus 4.6 with a 1M-token context window and “agent teams,” OpenAI's GPT-5.3 Codex and faster Codex Spark via Cerebras, and Google's Gemini 3 Deep Think posting big jumps on ARC-AGI-2 and other STEM benchmarks amid criticism about missing safety documentation.* Generative media advances feature ByteDance's Seedance 2.0 text-to-video with high realism and broad prompting inputs, new image models Seedream 5.0 and Alibaba's Qwen Image 2.0, plus xAI's Grok Imagine API for text/image-to-video.* Open and competitive releases expand with Zhipu's GLM-5, DeepSeek's 1M-token context model, Cursor Composer 1.5, and open-weight Qwen3 Coder Next using hybrid attention aimed at efficient local/agentic coding.* Business updates include ElevenLabs raising $500M at an $11B valuation, Runway raising $315M at a $5.3B valuation, humanoid robotics firm Apptronik raising $935M at a $5.3B valuation, Waymo announcing readiness for high-volume production of its 6th-gen hardware, plus industry drama around Anthropic's Super Bowl ad and departures from xAI.Timestamps:(00:00:10) Intro / Banter(00:02:03) Sponsor Break(00:05:33) Response to listener commentsTools & Apps(00:07:27) Anthropic releases Opus 4.6 with new 'agent teams' | TechCrunch(00:11:28) OpenAI's new GPT-5.3-Codex is 25% faster and goes way beyond coding now - what's new | ZDNET(00:25:30) OpenAI launches new macOS app for agentic coding | TechCrunch(00:26:38) Google Unveils Gemini 3 Deep Think for Science & Engineering | The Tech Buzz(00:31:26) ByteDance's Seedance 2.0 Might be the Best AI Video Generator Yet - TechEBlog(00:35:14) China's ByteDance, Alibaba unveil AI image tools to rival Google's popular Nano Banana | South China Morning Post(00:36:54) DeepSeek boosts AI model with 10-fold token addition as Zhipu AI unveils GLM-5 | South China Morning Post(00:43:11) Cursor launches Composer 1.5 with upgrades for complex tasks(00:44:03) xAI launches Grok Imagine API for text and image to videoApplications & Business(00:45:47) Nvidia-backed AI voice startups ElevenLabs hits $11 billion valuation(00:52:04) AI video startup Runway raises $315M at $5.3B valuation, eyes more capable world models | TechCrunch(00:54:02) Humanoid robot startup Apptronik has now raised $935M at a $5B+ valuation | TechCrunch(00:57:10) Anthropic says 'Claude will remain ad-free,' unlike an unnamed rival | The Verge(01:00:18) Okay, now exactly half of xAI's founding team has left the company | TechCrunch(01:04:03) Waymo's next-gen robotaxi is ready for passengers — and also 'high-volume production' | The VergeProjects & Open Source(01:04:59) Qwen3-Coder-Next: Pushing Small Hybrid Models on Agentic Coding(01:08:38) OpenClaw's AI 'skill' extensions are a security nightmare | The VergeResearch & Advancements(01:10:40) Learning to Reason in 13 Parameters(01:16:01) Reinforcement World Model Learning for LLM-based Agents(01:20:00) Opus 4.6 on Vending-Bench – Not Just a Helpful AssistantPolicy & Safety(01:22:28) METR GPT-5.2(01:26:59) The Hot Mess of AI: How Does Misalignment Scale with Model Intelligence and Task Complexity?See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Scams, spectacular failures, and billions burned! This special greatest hits episode of History's Greatest Idiots explores three tech disasters that prove innovation and incompetence make the perfect recipe for catastrophe.First up: Ruja Ignatova, the "Crypto Queen" who convinced investors OneCoin was the next Bitcoin whilst running one of history's largest Ponzi schemes. She vanished in 2017 with $4 billion of other people's money, becoming one of the FBI's Most Wanted. Her brother went to prison. Her victims lost everything. She's probably on a yacht somewhere laughing at all of us.Then we explore Y2K, the Millennium Bug that convinced the entire world civilization would collapse at midnight on 1st January 2000. Governments spent $300-600 billion preparing for disaster. Russia put nuclear forces on high alert. People stockpiled generators, tinned food, and guns (sales spiked 700% in some US areas). Airlines grounded flights. Survivalists moved to remote cabins. What actually happened? Some slot machines in Delaware stopped working. That's it. The most expensive non-event in human history.Finally, Sam Altman and OpenAI: the Stanford dropout who convinced the world he was building God whilst burning billions and destroying the planet. From nonprofit to capped profit to whatever OpenAI is now. ChatGPT's explosive growth to 100 million users in two months. The environmental catastrophe (training GPT-3 used enough energy to power 358 UK homes for a year). The brain drain to Anthropic as safety researchers fled. The board firing Sam for lying, 500 employees threatening to quit, and Sam returning five days later more powerful than ever. OpenAI projected to lose $14 billion in 2026 and potentially go bankrupt by mid-2027. Tech stocks making up 40% of the market. Microsoft losing $357 billion in a single day in January 2026. The AI bubble that might crash harder than dot-com.From crypto fraud to millennium panic to AI hype, these tech disasters prove that when greed meets fear meets overconfidence, billions of dollars disappear and nobody learns anything.Join Lev, Derek and special guest The History Obscura Podcast, as they count down the greatest hits of technology's most spectacular failures.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/HistorysGreatestIdiots⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/historysgreatestidiots⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://buymeacoffee.com/historysgreatestidiots⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Artist: Sarah Chey⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.fiverr.com/sarahchey⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

The pace of AI model releases is becoming almost impossible to follow. In just two weeks we saw GPT-5.3-Codex, GPT-5.2 updates, Gemini 3 Deep Think upgrades, Claude Opus 4.6 with a 1M context window in beta, Qwen3-Coder-Next, GLM-5, MiniMax M2.5, Cursor Composer 1.5, and even Kimi 2.5 just outside the window. This isn't a quarterly product cycle anymore - it's a daily arms race. In this episode Matt and Mike break down what this acceleration means for developers, open source, frontier labs, and the broader industry. Are we witnessing healthy innovation, or unsustainable velocity? At what point does this stabilize - if it ever does? If you're trying to build, learn, or compete in AI right now… this conversation is for you. ‍Show Notes: https://www.htmlallthethings.com/podcast/ai-competition-is-out-of-control

Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years. Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic. To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/ ----In this episode, I'm joined by Jaime Sevilla, founder of Epoch AI; Hannah Petrovic from my team at Exponential View; and financial journalist Matt Robinson from AI Street. Together we investigate a fundamental question: do the economics of AI companies actually work? We analysed OpenAI's financials from public data to examine whether their revenues can sustain the staggering R&D costs of frontier models. The findings reveal a picture far more precarious than many assume; we also explore where the real infrastructure bottlenecks lie, why compute demand will dwarf energy constraints, and what the rise of long-running agentic workloads means for the entire industry. Read the study here: https://www.exponentialview.co/p/inside-openais-unit-economics-epoch-exponentialviewWe covered: (00:00) Do the economics of frontier AI actually work? (02:48) Piecing together OpenAI's finances from public data (05:24) GPT-5's "rapidly depreciating asset" problem (13:25) Why OpenAI is flirting with ads (17:31) If you were Sam Altman, what would you do differently? (22:54) Energy vs. GPUs; where the real infrastructure bottleneck lies (29:15) What surging compute demand actually looks like (33:12) The most surprising finding from the research (38:02) The race to avoid commoditization (43:35) Agents that outlive their models  Where to find me: Exponential View newsletter: https://www.exponentialview.co/ Website: https://www.azeemazhar.com/ LinkedIn: https://www.linkedin.com/in/azhar/ Twitter/X: https://x.com/azeem  Where to find Jamie: https://epoch.ai or https://epochai.substack.com Where to find Matt: https://www.ai-street.co  Production by supermix.io and EPIIPLUS1 Production and research: Chantal Smith and Marija Gavrilov. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We're also joined by Steven Adler, ex-OpenAI safety researcher and author of Clear-Eyed AI on Substack. We cover: 1) The Viral "Something Big Is Happening" essay 2) What the essay got wrong about recursive self-improving AI 3) Where the essay was right about the pace of change 4) Are we ready for the repercussions of fast moving AI? 5) Anthropic's Claude Opus 4.6 model card's risks 6) Do AI models know when they're being tested? 7) An Anthropic researcher leaves and warns "the world is in peril" 8) OpenAI disbands its mission alignment team 9) The risks of AI companionship 10) OpenAI's GPT 4o is mourned on the way out 11) Anthropic raises $30 billion --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b EXCLUSIVE NordVPN Deal ➼ https://nordvpn.com/bigtech.  Try it risk-free now with a 30-day money-back guarantee! Learn more about your ad choices. Visit megaphone.fm/adchoices

Hiring's getting harder and the labor shortage isn't going away, but you can control how you sell your company to potential employees. Instead of listing features (like $20/hour or a 7–4:30 schedule), this episode teaches you to flip those into benefits that answer “What's in it for me?” so your job posting stands out.   You'll hear real examples (biweekly direct deposit → “never late paycheck”; consistent 7 a.m. start → “no guessing when to show up”) and a simple process to turn every feature into a hire-ready benefit. Kati also explains a custom GPT tool he built that writes these benefit-driven job posts in minutes — link in the show notes to join there free AI for Contractors group and grab the template. https://t2m.io/aiforcontractors   Ready to hire this season? Join the free AI for Contractors group (link in show notes), subscribe for more hiring tips, and tune in next week when Scott walks through behavioral interview questions to help you spot reliable, on-time employees.   Join the AI for Contractors group at https://t2m.io/aiforcontractors   Follow Million Dollar Landscaper: Website | Facebook | Instagram | YouTube

In this week's live-stream replay, we go live for a 2-hour, hands-on deep dive into GPT-5.1 Codex Max with Alexander Embiricos, product lead for OpenAI Codex. You'll walk out feeling like an agentic-coding wizard, even if you're starting from zero. GPT-5.1 Codex Max is OpenAI's latest frontier agentic coding model. It's built on an upgraded reasoning backbone and trained to handle real-world software engineering tasks end to end: PRs, refactors, frontend builds, and deep debugging. It can work independently for hours, compacting its own history so it can refactor entire projects and run multi-hour agent loops without losing context. In this live session, we'll set it up together, build real agents, and push Codex Max to its limits.

From EU fines that never get paid to cyber warfare grounding missiles mid-battle, this week's episode uncovers the untold stories and real-world consequences shaping today's digital defenses. How is the EU's GDPR fine collection going. Western democracies are getting serious about offensive cybercrime. The powerful cyber component of the Midnight Hammer operation. Signs of psychological dependence upon OpenAI's GPT-4o chatbot. CISA orders government agencies to unplug end-of-support devices. How to keep Windows from annoying us after an upgrade. What is OpenClaw, how safe is it to use, what does it mean. Another listener uses AI to completely code an app. Coinbase suffers another insider breach. What can be done Show Notes - https://www.grc.com/sn/SN-1064-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zscaler.com/security hoxhunt.com/securitynow trustedtech.team/securitynowCSS guardsquare.com

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For most of my career, I've been focused on two things: Operating businesses and Multifamily real estate. The strategy has been pretty simple. Take money generated from higher-risk, active businesses… and move it into more stable, long-term assets like apartment buildings. That shift—from risk to stability—is how I've tried to build durability over time. Now, to be fair, the sharp rise in interest rates a few years ago put a dent in that model. But zooming out, it's still worked well for me overall. So I'm sticking with it. That said, there are other ways to think about real estate. In some cases, the real opportunity is when you combine real estate with an operating business. We've done that before in the Wealth Formula Investor Club with self-storage, and the results were excellent. Storage is operationally simple, relatively boring—and that's exactly why it works. But there's another category that sits at the opposite end of the spectrum. Hotels. They're sexier.They're more volatile.And yes—they're riskier. But the upside can be dramatically higher. One of my closest friends here in Montecito has quietly built a fortune doing boutique hotels over the past few years. He started with a no-frills hotel in Texas serving the oil drilling industry. Over time, he combined his operational experience with his talent as a designer—and eventually created some of the highest-rated boutique hotels in the world. He's absolutely crushing it. Of course, most of us aren't world-class designers or architects. I'm certainly not. Still, his success made me curious. Hotels have been on my radar for a while now—not because I understand the business, but because I don't. When I asked him how he learned the hotel industry, his answer was honest: “I figured it out on the fly—starting with my first acquisition and a great broker.” That's usually how real learning happens. So this week on the Wealth Formula Podcast, I brought on an expert in hospitality investing to educate both of us. We cover the basics: How hotel investing actually worksWhere the real risks are (and where they aren't)How returns differ from multifamilyAnd what someone should understand before ever touching their first hotel deal If you've ever thought about buying or investing in hotels—but didn't know where to start—welcome to the club. You don't have to jump in tomorrow. But you do have to start somewhere. This episode is a good starting point. Listen on Apple Podcasts: https://podcasts.apple.com/gb/podcast/545-should-you-invest-in-hotels/id718416620?i=1000748759003 Listen on Spotify: https://open.spotify.com/episode/5Lx5Rp4x704lWRazWLqDOK Watch on YouTube: https://youtu.be/GMFf6-g8w_0 Transcript Disclaimer: This transcript was generated by AI and may not be 100% accurate. If you notice any errors or corrections, please email us at phil@wealthformula.com. Welcome everybody. This is Buck Joffrey with the Wealth Formula Podcast coming to you from Montecito, California. Before we begin today, I wanna remind you, if you’ve not done so and you are an accredited investor, go to wealthformula.com, sign up for our investor club. Uh, the opportunity there is really to see private deal flow that you wouldn’t otherwise see because it can’t be advertised. And, uh, only available to those people who are deemed accredited. And then what does accredited mean as a reminder? Well, if you’re married, you make $300,000 per year combined for at least two years with a reasonable expectation, continue to do so, or you have a net worth of a million dollars outside of your personal residence. Or if you’re single like me, $200,000 per year or a million dollars net worth. Anyway, that’s probably, uh, most of you. So all you gotta do is go to wealth formula.com, sign up for investor club because hey, who doesn’t wanna be part of a club? And, uh, by the way, it’s a great price. It’s free. So join it. Just get onboarded and all you gotta do is just wait for deal flow. What a deal. Now let’s talk about different kinds of things to invest in. For most of my career, I, I have really focused on two things I’ve focused on. Either operating businesses, uh, in my case, those operating businesses largely have been medical and multifamily real estate. Uh, the strategy itself, theoretically the way I think about it, take money from sort of these active businesses, a higher risk, move them into more stable long-term assets like apartment buildings. Okay? The idea is that’s how you build some durability over time. Now, to be fair, okay, to be fair. Sharp rise in interest rates a few years ago. Put a little bit of a dent in that model. But here’s the thing is that you can’t throw out the, uh, baby with the bath water. ’cause when I zoom out, still worked well for me overall. So I’m sticking with it and, uh, that’s my story. I’m sticking with it. That said, there are always other ways to think about real estate, right? Real estate is not just multifamily. Um, in some cases, the real opportunity is when you combine real estate and operating businesses. So. We’ve actually done that before in our wealth formula investor club. Um, and we’ve done that through self-storage, for example, and the results were really good. Storage is operationally, generally pretty simple. Probably not that simple, but you know, but more so than other things, relatively boring. Boring is good, and that’s exactly why it works. There’s another category that sits at the opposite end of the spectrum of boring, and it’s sexier and it’s more volatile and it’s riskier. And uh, that is the area of hotels, right, like leisure, that kind of thing. But the upside in those things can be dramatically higher. You know, one of my closest friends here. Montecito, I talk about him all the time. He’s a, he is a little bit of an inspiration to me, although I wouldn’t tell that to in space. He’s built a fortune doing boutique hotels over the past few years and the way he started, you know, and I think it was only about a decade ago because he bought like this no frills hotel in Texas that was serving the oil industry. There was a bunch of guys, you know, drilling needed a place to say, and you know, he had this and he actually. I don’t know that I would recommend this, but he, he told me he bought it sight unseen just based on the numbers. Ah, man, I gotta tell you, I don’t think I’m that lucky. If I bought something sight unseen, it would not work great for me, but it did work great for him. But over time, what he did is he, he combined his operational experience with his talent as he’s like a designer, like designs, homes, an architect, uh, of sorts, although more than that. Um, and he, he used to build houses for like famous people in Hollywood. Anyway, he took that skill and so he combined it with hotels and he created some of the highest rated boutique hotels in the world. And he’s absolutely crushing it. Just crushing it. Of course, the reality is that most of us aren’t world-class designers or architects. I’m certainly not. I’m not artistic at all. Still, um, you know, the fact that he’s had so much success in this space and that he loves hotels. What got me curious? So, hotels have been on my radar for a while, not because I understand the business, but actually because I don’t. And when I asked him how he learned, uh, about the hotel industry, he just said, you know, I figured out on the fly and, uh, you know, started with my first acquisition, had a great broker who taught me everything I, you know, needed to know at the beginning and. That’s a great story. I mean, and ideally that’s how things happen. As you can tell, this guy is, uh, seems to just hit on everything. So good for him. So this week on Wealth Formula Podcast, I wanted to get a little bit of a hotel investing 1 0 1. So I brought on an expert in hospitality investing that could educate both you and me. So we’re gonna cover some of the basics, how hotel actually works, you know, what are the risks returns. Like, what should people do if they even consider, you know, buying their first hotel or investing in one? So if you’ve ever thought about investing, uh, in hotels, or maybe that’s the first time you’re hearing about it and you’re curious, uh, welcome to the club and uh, we will have a great interview for you right after these messages. Wealth formula banking is an ingenious concept powered by whole life insurance, but instead of acting just as a safety net, the strategy supercharges your investments. First, you create a personal financial reservoir that grows at a compounding interest rate much higher than any bank savings account. As your money accumulates, you borrow from your own. Bank to invest in other cash flowing investments. Here’s the key. Even though you’ve borrowed money at a simple interest rate, your insurance company keeps paying you compound interest on that money even though you’ve borrowed it. At result, you make money in two places at the same time. That’s why your investments get supercharged. This isn’t a new technique. It’s a refined strategy used by some of the wealthiest families in history, and it uses century old rock solid insurance companies as its backbone. Turbocharge your investments. Visit Wealth formula banking.com. Again, that’s wealth formula banking.com. Welcome back to the show, everyone. Today. My guest on Wealth Farm I podcast is, uh, John O’Neill. He’s a, a professor of hospitality management and director of the Hospitality Real Estate Strategy Group at Pennsylvania State University. Uh, he spent decades studying hotel valuation performance, Cabo flows and economic cycles in in the lodging industry. John, thanks for, uh, joining us. You’re welcome. So, you know, we’re talking offline. You’ve been in the hotel business for a long time. We’re trying to figure out how to frame this thing because you know, I mean there are, I know there are certainly people in. Uh, who in, in my group and my listeners, my community who are in the hotel space, but a lot of ’em aren’t. And you know, they’ve been thinking about, well, you know, we do a lot of apartment buildings, that kind of thing. Um, you know, what else should we be thinking about? And so, you know, when we hear, uh, hotel, um, they’re thinking of hospitality. But from an investor’s perspective, I guess the first question ask is what kind of real estate asset is a hotel? And, and may, may maybe just sort of fundamentally how different it is. From apartments office or retail? Yeah, that’s a great question because hotels are fundamentally different. But what I’ve seen over the past few years as well is hotels have increasingly been considered to be a component of commercial real estate. So we’ve always thought about office and retail and residential and industrial as being components of commercial real estate, but increasingly. Investors are thinking about hotels that way as well, because some of the high risk aspects of hotels have been moderated a little bit. So they are still considered to be a high risk and potentially high reward category, but they’re much more cyclical than those other types of businesses. So if we look at apartment leases, maybe being a year or two. Office leases may be being three to five years and retail leases could be five or 10 years. The leases in hotels are one or two nights, so there’s upside, but there’s risk involved in that as well. So when there’s pressure in a market to increase rates, like here where I am in University Park, Pennsylvania, when we have a home football game. We can see hotels with average daily rates of maybe a hundred to $200 a night charging seven, eight, $900 per night, and filling up on those rates. You can’t do that in an office building or in a retail center. And so there’s great opportunity when demand increases to push up rates and to greatly benefit from that. The flip side of courses on Sunday night when all those guests leave. You might be back to a hundred dollars a night and running 20 or 30% occupancy. Do hotels kind of follow the rest of real estate in terms of market cycles though? Yeah, it depends. I, I would say in many cases they’re actually leaders, which again, double-edged sword there. So for, yeah, when we plummeted in 2020 because of COVID hotels were probably the first category really to see it. Demand dried up overnight, and you go back to September 11th, 2001 on September 12th, 2001, a lot of hotels were empty and that wasn’t the case with office buildings and retail centers. The flip side, of course, is when the economy started improving, hotel operators could start pushing their rates very quickly. And so other categories of commercial real estate didn’t receive those benefits. Yeah, I mean, obviously there’s certainly gonna be. Real estate that’s often used that that’s often using debt and, you know, probably has the same sort of, uh, issues with regard to cap rate compression or decompression based on interest rates as well. Right, right. So, um, where are we? Right? What would you say right now, like, I mean, we know that. Our, we’ve been following very closely on the multifamily side. You know, prices are depressed. I mean, from 2022, we’re looking at probably 30% to 40%. Most, most, uh, large apartment complexes are not moving because people don’t wanna sell into a down market. But when they are, they’re being sold at 30, 40% discounts compared to 2022. Where is the, where is the hotel? Market at right now? It it, it’s challenged because right now we’re seeing discrepancies between where buyers wanna buy and sellers wanna sell. We’ve started to see some movement because some sellers have come down a bit in pricing because of what we’ve seen in 2025, the market really did soften as far as the hotel business is concerned. So in 2025. We really saw no increase in occupancy and in many markets we saw some decreases in occupancy. We are still seeing average daily rates going up a little bit, so yeah. Might be worth maybe a quick step backward that the two key indicators in terms of hotel lodging performance would be occupancy and average daily rate. With occupancy being the extent to which the guest rooms are occupied and average daily rate being the average price somebody is paying. We can talk about the mathematics of those, but, um, just I think conceptually, hopefully that makes sense. But, so, you know, at this point what we’re seeing is average daily rates are still going up a little bit, and the forecasts for 2026 are. Pretty much more of the same, where we’re not expected to see great occupancy increases, but we are anticipating that the average daily rates might go up a little bit. Uh, and, and in fact we might see occupancies decline slightly. And, uh, we might see, uh, average daily rates still possibly going up a little bit. That’s usually an indicator of being late in the cycle, you know, being somewhere near the peak and, and, you know, if the trough was 2020. Which was a pretty deep trough. 2021, we started seeing improvements and we saw great improvements in 22, 23, and 24, and so it’s looking like the end of a cycle. The thing we don’t really know for sure is, is there some reason that we’re going to really go into a substantial down period or are we actually in a situation where we’re going to have another upcycle? Yeah. You know, the other thing I was curious about too, like when you talk about these cycles for hotels, even within hotels, there are certainly, you know, different types of hotels. You know, there’s the boutiquey ones that are pe really pure tourism versus the ones that, okay, well maybe they are, you know, good for football games or. There’s others that are people use for, for, for work frequently, right? They’re, they’re just passing through for, for work trips. Do you, is there, um, is that difficult to extricate those types of different economies running at the same time? It’s not, I, I don’t know that it’s that difficult, you know, just to give you a little bit about my background, I’ve been a professor for some time, but prior to being a professor I worked for. Three of the four major hospitality organizations, namely Marriott, IHG, and Hyatt. Uh, and so going back into the 1980s when I was doing feasibility studies for proposed Marriott hotels, we, in most markets, analyzed three markets segments. And, and you essentially said what they are commercial business, which are your business travelers, leisure business, which are your pleasure travelers, and then groups, which includes conventions and, and those are still the three major market segments in most markets. In, in some markets. For example, if you’re approximate to a major international airport, there’s usually a fourth segment, which is that fourth segment is airline crew business, which is, is very different than the other three because. Whereas the other three go up and down throughout, not just the year, but throughout the week. Airline crew business tends to be stable throughout the year, so it, it, it’s in your hotel 365 nights outta the year. So it’s, it’s a very low risk, but also a very low rated market segment. So it, I don’t know if that’s that complicated, but it just needs to be broken out as you delineated it, which is that there’s. Three or four market segments in any market. And in terms of studying a hotel for development or for investment, it’s necessary to understand not just what’s going on on the supply side, in other words what’s going on in the hotels, but what’s going on in the demand side as well. So give you an example. I recently did a feasibility study in a market, which is a big pharmaceutical market. So I actually spent time with major pharmaceutical people talking about, where are you staying now? Why are you staying there? Are you a member of the Frequent traveler program? How does your business vary throughout the year? What rates are you paying? What facilities and amenities are you seeking? And things like that. So to really understand the demand because that demand segment. So important in that market. So it is ultimately a street corner business and what’s going on in a specific market in terms of the mix of commercial, leisure and group business and possibly other market segments. Really is something that we have to study in depth when we conduct a feasibility study or an appraisal for hotel. I, I don’t know if I mentioned, I’m a licensed real estate appraiser too, and although my licenses allow me to appraise any type of property, I only appraise hotels. Got it. Businesses fundamentally changed pre COVID and post COVID. I would assume that there’s probably less travel. Are you seeing impact? On those types of hotels from that kind of, you know, less travel, more zoom type activity. Yeah. And, and that’s a great, that’s a great follow up because with those market segments, although the segments are the same. The demand from each of those segments really has different, and, and as you said, it really changed substantially in COVID. It, it, it’s fascinating how once we were forced to use Zoom and, and other, you know, Microsoft teams and other technology like that, you know, we, we kind of did a kicking and screaming. But once we figured it out, we realized we didn’t get a lot done. Uh, now I spent last week in Los Angeles at America’s Lodging Investment Summit, and I go to this. Function every year, because I see many of the same people year after year, and the business cards might change, but it’s the same people involved in the hotel business, whether they’re brokers or investors or asset managers or consultants or appraisers. But in between. Each year I do a lot on Zoom with these people and you know, we can keep those relationships going. So it hasn’t eliminated, you know, in my personal case, my need to travel, but it has substantially reduced it. And I think a lot of other business people have seen the same thing. So if we look at the recovery since COVID, it was fascinating because the first market segment that recovered and recovered really strongly was leisure business and people, people see it as their right. To have a vacation and, and people were paying high rates, particularly in, in, in mountain locations and in beach locations. And so those rates came up really quickly. And then the group business followed. If people do wanna go to group functions like I did last week in la what has not recovered to the level of 2019 though is the business travel. Right. Interesting. So I, that’s probably a, uh, you know, and he, I can’t really see a particularly promising future for that Subsect either. Right. I think, in fact, bill Gates said it’s never going to be back to the, you know, he, he’s an investor in Four Seasons hotels, and he said it’ll never be back to the way it was in 2019. I don’t know if he’s right. I mean, because I, I still feel like we get a lot of things done. Face-to-face, person to person that we really can’t do in Zoom. I don’t think Zoom is great for establishing relationships. I, I still think that we need face-to-face, uh, personal contact. But, you know, that might be just my perspective because I’ve been working in hotels since I was a teenager and I’m really far from being a teenager now. And, you know, I, I’ve been indoctrinated in this philosophy of the importance of face-to-face contact. But yeah, you know, that might be generational. You with a younger generation. Yeah. Yeah, absolutely. Um, you know, just kind of going back to the difference differences, uh, with compared to other real estate hotels, ultimately the, one of the big differences, they’re operating businesses, right? I mean, they’re not that large. Apartment buildings aren’t, but they’re is I think, a specific sort of operational execution that matters a lot in hotels. So, you know, in invest, when investors are kinda looking at that, I mean, they, they should probably be not looking at it as nearly as passive as other real estate investments. Is that fair? I, I think that’s very fair because I think, you know, it, it shows what’s happened in terms of the market with real estate investment trust. Because I’ve sold my entire position in hotel real estate investment trust and, and as you probably know, if we look at real estate investment trust. Different categories in, in commercial real estate, hotels lag, which is fascinating because everything else we’ve been talking about explains why hotel returns tend to outperform other classes of commercial real estate. More volatility, but higher returns on average. If you can withstand the long period, uh, that you need to be an investor. On real estate investment trust, it’s the opposite. Hotels actually lag and, and I think it really is because of exactly what you’re talking about, which is that they really are like an operating business where there’s also real estate as opposed to a real estate play where it’s almost like there’s an annuity of rent that is very easily projected, uh, in hotels. You know, we, we. Project all the time how they’re going to perform. But you know, you know, I hope my projections are very good, but there’s always things that can COVID. For example, you know, now there’s a virus in, in India that you know might be coming and, you know, we don’t know, will this be substantial or will it be really minor in the Americas? We really don’t know. Uh, that won’t have a big effect on, on other classes of real estate investment trust, but. It could have a big effect in hotels, so, so the unknowns in hotels are very high. And then when you combine that with the fact that they are an operating business, which are very labor intensive and wage rates are going up. So the cost structure and the management of that cost structure becomes. Very important and the expertise of the hotel managers becomes very important. And so, yeah, like you say, other classes of commercial real estate or, or institutional real estate investments have an operational component. It’s much greater when it comes to hotels. So I actually have a friend who’s an, um, owns, uh, a few boutique hotels here in, in California, and he was telling me one of the things that he’s kind of worried about is, um, you know, they, they’re, they have some, um. Some mandates coming up with regard to, you know, minimum wage and, and all these things that, uh, hotel workers have to get, uh, give you just outta curiosity. I mean, most of my audience is not in California. I am, but have you heard about this? Can you tell us a little bit about those pressures? Yeah, I have heard about it. And there’s, there’s forces on the other side as well, namely the American Hotel and Lodging Association, which represents hotel owners, managers, and franchisers. And so they have a voice in these things as well. But the, the, the forest, particularly in places like California and, and in the west coast in general, we’ve seen it in Seattle as well. Um, you know, in, in terms of increasing minimum wages to rates that, that are shocking to me. Um, you know, that’s, that’s a big issue. You know, you don’t see it as much in the middle of the country, but you do see it on the coast and particularly in the, on the West Coast. So, you know, if we’re looking at projections, say into 2026 and, and perhaps beyond, we expect in many cases to be seeing higher growth in wage expenses than we expect to see growth in RevPAR, which is room revenue, preoccupied room, which is just occupancy times average daily rate. So the, the overall revenue is expected, at least in the short term, to grow more slowly. Than expenses and, and wages are really driving a lot of it. And then anything that’s affected by wages, so insurance, for example, property taxes, other expenses are really growing at this stage more than what we’ve seen in terms of revenue growth. So that’s, that’s a challenge right now. The, the question I think really then is how much will AI affect that and to what extent will guests become more comfortable with checking in? On an iPad type of a situation as opposed to seeing a person face to face, and there’s probably generational differences there. What it is forcing hotel operators to do is the same kinds of things that restaurant operators have been forced to do, which is find ways to use technology and actually have the guests face the technology and get the guests comfortable with that. In terms of things like check in and check out, you know, but still in hotels the rooms have to be cleaned and, and although there’s robots that. You know, they’re nowhere near what, where they need to be to actually clean Hotel guestroom jet, at least in any sort of economically viable way. But, you know, the long-term question is to what extent will the industry be adopting AI and other technology in order to address that issue? Because that’s what’s going to happen. It’s, it’s, you know, it’s not just going to be a situation where. The operators will accept paying higher wages and have the same number of employees in each hotel. Right. Um, branding, you know, sort of confusing to a lot of people. Not in the space, but you know, what role do hotel brands actually kind of play in, in protecting revenue and value? Um, and I guess when does a brand help an owner versus become a constraint? Yeah. You know, brands have been very important and, and I, I forget if I mentioned but of the, the big brand companies I’ve worked for three of them and, um. You know, they, they, they typically started as management companies. So originally companies like Hilton and Marriott primarily generated revenue through management fees. And so they own some of the real estate, although they’ve become asset light over the years and own very little, if any, anymore. Uh, but they do still manage hotels. So one thing that the brand companies do have is expertise in terms of management. That’s one of the fees that a branded hotel and a non-branded hotel would have as well, would be a management fee, which is usually expressed as a percentage of revenue. And sometimes there’s an incentive structure in there as well. But then there’s a franchise fee, which is just paying for the brand, and, and that’s usually as a percentage of total revenue, higher than the management fee. But what it does is it, it, it. Puts the property in a global distribution system, so the global distribution systems that brands like Marriott and Hilton and IHG and, and HIA have, uh, they. Generate heads and beds. You know, that’s, that’s the term we always, when I worked at Hyatt and Merritt, we always talked about heads and beds. Every night you’re trying to, trying to get people in the rooms. The brands do a lot to put heads and beds, you know, in a typical hotel with a good brand affiliation. Somewhere between probably a third and two thirds of the occupy rooms actually came in through the brand global distribution system, which historically was a toll free reservation system. And although the, you know, those still exist now, it’s really more of a focus on the online system and, and, and sometimes toll-free reservations and direct reservations. But, but that’s what the brand does. It, it, it ultimately is a generator of. So kind of just focusing on somebody who’s potentially thinking about hotels as an investment. So far, what I gleaned from you, and, and correct me if I’m wrong, is that timing probably isn’t perfect right now. We’re probably, you know, we’re probably in a, you know, a peak and you generally not a great idea to buy in peaks. Um. I personally, from what I understand, would stay outta California. You know, uh, you know, like my friend was saying that it was gonna make it very difficult for a lot of hotels to have their, you know, hotel restaurants even. And so he foresees like a lot of them having to close those down. Um, and then the, the next thing I think is, gosh, you really have to be cognizant of the, of the fact that, you know, work patterns are changing. And so maybe that’s not a good. Way to go, either. What other, what are some other big picture things that you think people ought to be thinking about as they evaluate the space? Yeah. Well, I think there’s a couple of things. One of which is. That is a street corner business. So it really depends on what street corner you’re in. Uh, I’ve done some research just on how hotels perform in university towns versus other locations because, for example, there are brands now called graduate hotels, which eventually was acquired by Hilton, uh, and, uh, scholar Hotels and, and these properties are university town hotels. They’re doing okay. You know, they’re, they’re doing okay. If you look at how universities operate, we’ve seen some Ivy League schools pay 60, $80 million or more just to make sure they keep that billion dollars a year coming in from the federal government that they, they get for research grants and, and we’ve seen, you know, look at what’s going on with NIL now in terms of, of university sports. Universities clearly are willing to. You gen willing to spend a lot of money to keep doing what they do, which is, you know, they, they generate a lot of research and I’m talking about. Big universities now, uh, you know, a lot of research and, and there’s a sporting business aspect to universities as well. So university towns are okay, and, and what I ultimately found in my research is they’re much less cyclical than the average. So, you know, we talk about the risk of hotels as things go up and things go down and things go up and down. That doesn’t happen as much in university towns. You know, big universities don’t close and, and don’t even substantially change their business model. So it really depends on, on where you’re located. And then there’s certain cities as well, you know, people, you know, I, I don’t have to go into detail about my last visit to San Francisco and how weird it was, and I was with students and, and told my female students don’t go out at night alone. I mean, it was, it was, it was really freaky, but. San Francisco now might be a place to invest. Now San Francisco probably has bottomed out. Uh, and the same might be true with New York. So, you know, it really depends on where you’re going. I, I think in general, yeah, you know, there’s, there’s concerns, but even so, you know, I think it’s still might be a good time to invest in. Good quality hotel companies, just, you know, in terms of the stock market and, and equity in, in businesses like Marriott and, and Hilton because their franchise fees and their management fees are a percentage of total revenue. So hotels that are not profitable, that are a member of those brand affiliations are still paying. Into those systems and you know, hopefully the goal is that these properties become profitable, but even while they’re not profitable, they owe franchise fees and in some cases management fees as well. So I think there are a lot of ways to still invest in the hotel business. It’s just what vehicles are being used and where. So, you know, it sounds a little overwhelming, um, for someone who, again, who’s new to the space. Any suggestions on how somebody might just learn more about this ecosystem and, you know, start to go down this path of potentially becoming, you know, a hotel investor? Yeah. Well, first thing is, you know, we talked about ai. AI is pretty good for helping people to learn. So if you wanna learn about the hotel business, you can go and have a really good conversation with chat GPT about what makes it click and where could the opportunities lie today. Uh, you know, I’ve gone over the past year from essentially not using AI at all to using it essentially every day. And so that’s a great way because that’ll access a lot of, there, there’s trade journals, for example, but it’ll access those things. Uh, the conference, like I went to last week, the America’s Lodging Investment Summit, which is in LA every year is a. Is a great place to learn as well. There’s, there’s wonderful sessions and that conference is attended by everybody from Anthony Capano, who’s the CEO of Marriott, down to people involved in real estate and investments in the hotels and, and who essentially make their living. Off of those as brokers, appraisers, consultants, asset managers and things like that. So, so there’s ways online to do it and there’s ways to do it actually by attending conferences as well. Yeah. A good broker as well. Right. I mean, you know, going back to my, my friend who, who’s become a very successful hotelier, the first one he bought, he threw a broker and he said he learned everything about hotels that he knows from that guy. Um. So that’s probably, it probably tells you something as well. Yeah. And, and there are some excellent hotel brokers. There’s some who are national in scope and some who are local in scope. So again, it depends on where you’re thinking you might wanna be investing. Uh, but, but there’s some great local brokers, but then there’s national firms like JLL and CBRE and Hunter, uh, that, you know, they have really good people who are very knowledgeable about the hotel business. Yeah. John, thanks so much for, uh, joining us here on Wealth Formula Podcast and giving us sort of an overview of the, uh, um, hotel, uh, real estate, uh, uh, asset class. You bet you make a lot of money, but are still worried about retirement. Maybe you didn’t start earning until your thirties. Now you’re trying to catch up. Meanwhile, you’ve got a mortgage, a private school to pay for, and you feel like you’re getting further and further behind. Now, good news, if you need to catch up on retirement, check out a program put out by some of the oldest and most prestigious life insurance companies in the world. It’s called Wealth Accelerator, and it can help you amplify your returns quickly, protect your money from creditors, and provide financial protection to your family if something happens to. The concepts here are used by some of the wealthiest families in the world, and there’s no reason why they can’t be used by you. Check it out for yourself by going to wealth formula banking.com. Welcome back to the show everyone. Hope you enjoyed and again, uh, hey hotels. Think about it. I guess. Uh, I continue. I will continue to do so, uh, especially given my buddy’s success in this space. Um. Although, I will tell you, I probably am not a boutique hotel guy. Um, you know, I don’t, I don’t know that I could make it super fancy, you know? And then on the other hand, you hear about these, uh, hotels that are. For the people traveling through and they’re not doing this so great. So maybe wait till that we hit that, um, that trough that he was talking about, he said we’re kind of at a peak right now. Anyway, that’s it for me. Uh, this week on Wealth Formula Podcast. This is Buck Joffrey signing off. If you wanna learn more, you can now get free access to our in-depth personal finance course featuring industry leaders like Tom Wheel Wright and Ken McElroy. Visit well formula roadmap.com.

Things got kinda catty between OpenAI and Anthropic