Podcasts about Perplexity

Wer KI-Modelle bauen will, braucht leistungsstarke Chips und riesige Rechenzentren. Davon profitieren viele Firmen. Doch Entwickler wie Google, Anthropic, Google oder OpenAI haben selbst noch keinen stabilen Weg gefunden, um ihre Modelle zu Geld zu machen. Zwar versuchen sie es mittlerweile verstärkt über Nutzungsgebühren - aber je höher diese Kosten sind, desto mehr Kunden überlegen, wie sehr ihnen die Modelle wirklich nutzen – eine Zwickmühle. Wie und ob sich KI zu Geld machen lässt, klären Markus Plettendorff und Alex Drost in 10 Minuten Wirtschaft.Links:  Berauscht von KI - eine neue Blase an den Märkten? https://www.tagesschau.de/wirtschaft/finanzen/ki-blase-100.html Was KI kostet und wer das alles bezahlt https://www.tagesschau.de/wirtschaft/finanzen/kuenstliche-intelligenz-kosten-100.html Neue chinesische KI fordert US-Konkurrenz heraus https://www.tagesschau.de/wirtschaft/unternehmen/ki-konkurrenz-china-usa-100.html

Annie Jacobsen is a Pulitzer Prize finalist, investigative journalist, and bestselling author. Her latest book, "Biological War: A Scenario," is out now.www.penguinrandomhouse.com/books/783250/biological-war-by-annie-jacobsen/www.anniejacobsen.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Learn more about your ad choices. Visit podcastchoices.com/adchoices

The Dodleston Messages | Paranormal Podcast Hey everyone! This bonus episode is an older collab we did with Kaydra on her podcast, Perplexity: A Mystery Podcast. Enjoy! Episode Description: We joined Kaydra over at Perplexity: A Mystery Podcast, for a deep dive into one of the most well-documented and genuinely bizarre cases in English paranormal history — the Dodleston Messages, where a schoolteacher named Ken Webster moved into a rundown cottage in 1984 with his girlfriend and a borrowed BBC computer, and somehow ended up in an 18-month three-way conversation between a 16th century farmer named Lucas Waynesman, and an entity that only identified itself as 2109. The lore builds layer by layer — six-toed footprints walking up walls, furniture stacked to the ceiling, shadow figures, chalk writing in Latin, and a ghost who flirts with Debbie across the centuries — and just when you think you've got a handle on what's happening, the investigators brought in to study it turn out to either not exist or to vanish completely.

In this episode of The Ross Simmonds Show, Ross joins Nick in The Nick Standlea Show to break down how search is changing as Google AI Overviews, ChatGPT, Gemini, Perplexity, and other LLMs reshape how people discover brands. They unpack what marketers, creators, and business owners need to do now to improve AI visibility, build authority across platforms like YouTube and Reddit, and create content that gets found, cited, and trusted. Key Takeaways and Insights: 1. How LLMs actually build answers - Ross explains “query fan-out,” where AI tools rephrase a user's prompt into many variations and scan multiple sources at once. - Platforms like Reddit, YouTube, Quora, Yelp, and Google results all help shape the final response. - The brands mentioned most often—and with the strongest supporting signals—are more likely to appear in AI-generated answers. 2. The coffee shop framework for local AI visibility - Local businesses should align site pages and language with the exact questions customers ask. - Review signals from Yelp, TripAdvisor, and other directories strengthen trust and authority. - Encouraging real customer conversations on Reddit and other platforms can influence how AI tools perceive your brand. 3. Why YouTube is a major AI search advantage - Google has a built-in incentive to surface YouTube content because it owns the platform and monetizes attention there. - YouTube remains one of the most powerful search engines in the world and a rich source of human-led content. - Video stands out in an AI-heavy world because it delivers a stronger sense of trust, personality, and connection. 4. Gemini, personalization, and the future of search - Google may have a long-term advantage because Gemini can connect with products like Gmail, Calendar, Chrome, and more. - Search experiences are becoming more personalized, which makes traditional ranking analysis harder. - Marketers need to prepare for a world where different users may get very different answers to the same prompt. 5. How nonprofits and mission-driven brands should adapt - Start by mapping website content to the real questions your audience asks before they know your brand exists. - Build long-form, useful resources that directly address audience pain points and decision-making moments. - Combine LLM optimization with human-centered storytelling to connect both logically and emotionally. 6. The four E's of content that builds trust - Ross highlights four content goals: educational, engaging, entertaining, and empowering. - Strong brands don't just publish information—they create content people want to remember and share. - Human connection still matters, especially when AI-generated content is becoming more common. 7. Old-school customer research is the new edge The deepest marketing insights still come from direct conversations with real customers. Interview transcripts, sentiment analysis, and qualitative feedback can be turned into sharper messaging with AI. The brands that win will combine human insight with AI execution, not replace one with the other. Resources & Tools:

In This Episode The future of online visibility isn't about ranking higher on search engines—it's about becoming the answer AI chooses to recommend. In this episode, Adi Klevit interviews Dr. Tamara Patzer, media systems architect and AI visibility expert, about how professionals can prepare their knowledge for the rapidly changing world of AI-powered search. Tamara explains how search behavior has shifted from clicking website links to asking conversational questions of AI platforms such as ChatGPT, Gemini, Claude, Perplexity, and Bing AI. Adi and Tamara explore the importance of creating a structured "source of truth" that AI systems can understand. Rather than relying exclusively on attractive websites or social media profiles, Tamara explains why businesses should organize their expertise using structured data, schema markup, transcripts, and machine-readable content. These systems help AI platforms verify expertise and confidently surface professionals when users ask industry-specific questions. The conversation also highlights the risks of building an entire digital presence on rented platforms like social media. Tamara emphasizes that businesses should own their digital assets by maintaining authoritative content on their own websites while using podcasts, press releases, articles, and social media to amplify those signals. Adi draws parallels between documenting business processes and documenting professional expertise, noting that both rely on organizing knowledge into repeatable systems. Perhaps the biggest takeaway is that AI visibility is not a one-time project but an ongoing system. Businesses that consistently publish structured content, document their expertise, and adapt to changing AI technologies will be better positioned to become trusted sources in the emerging AI search landscape.  

Hey, it's Alex (yeah, I'm finally back from my vacation!) What a freaking week to come back to! Just after our last episode was published, Anthropic releases Opus 5, Jensen joins X and drops the “Open Weights & AI Leadership” open letter, Kimi K3 is released the following Monday beating expectations, and then the AI hack (OpenAI model breaking sandbox and infiltrating HuggingFace) is on everyone's mind, another Open Letter, this time from over 1K employees inside the frontier AI companies all talk about pacing the pace of frontier AI development. We played with Opus 5 and Kimi K3, and had the great pleasure to chat with friends of the pod Elie Bakouch (Prime Intellect) and Philip Kiely (BaseTen) about this important open weights release, then covered our general thoughts on Opus 5, and made order of all the different open letters that came out this week. Finally we chatted with Max from Pangram about the next version of AI writing detection (their biggest yet) and finished with Zuckerbergs (also on X! what's going on with everyone joining X) op-ed on the vision of personal superintelligence for everyone. Let's dive into this (as always, all the links and sources at the end, please don't forget to sub to our podcast on your favorite podcast app!) Open Weights AIKimi K3 the king of open weights - 2.8T chonker MoE near frontier model (X, HF, Blog, Tech report)This has got to be the biggest news of this week, and maybe the open weights AI news since GLM 5.2. MoonShot came back with Kimi K3, and we haven't seen any models quite this large in the open. Even Grok 4.5 is around 1.5T, this model is nearly 2x the size. Coming in at close to 3T parameters (and 2.5terabytes of weights at MXFP4 format), this model comes in very close to frontier! This was such an important release that I invited 2 friends of the pod, Elie Bakouch (prev HuggingFace, now Prime Intellect) and Philip Kiely (Author of Inference Engineering book, BaseTen) to dive deep into what makes this special! Elie's take, from reading the tech report, there's no single secret sauce, it's a combination of already available in the open techniques. Like KDA (Kimi Delta Attention) that has been out for a while, attention residuals, NVIDIA's latent MoEs. The highlight for Elie was the scaling work they did that reported a 2.5x scaling efficiency over Kimi K2.5 (2.5 performance at the same compute)! They also skipped RoPE entirely in favor of NoPE (the report calls it No Positional Encoding) for long context.Serving 1.4TB on eight GB300s (Baseten blog)Philip's team at Baseten was a day-zero provider (we're still working on bringing this model to CW Inference, stay tuned!) so I invited him to tell us behind the scenes of hosting this beast. Philip said that just loading the weights takes about 1.5TB!! of VRAM, and that's before the KV cache allocation + 1M token windows, so they're serving it on 8 GB300s where NVL72 . Baseten worked with the vLLM and SGLang teams on kernels and he also said they contributed patches back upstream! The model was trained with MXFP4, which, unlike Nvidia's own NVFP4 is a more standard format per Philip. I enjoyed his deep dive analysis into the differences, but because of this and because they trained the model with quantization awareness, it's “only” 1.5TB vs the would-be 5-6 TB if that this model in FP16 would demand. One of the more favorite nerd snipes moments, Philip pointed out that his colleague discovered that with over 99% of the usage being cached (think harnesses that send millions of the same cached tokens back and forth), tokenization actually starts to become a bottleneck. So they released a custom “basetenkenizer” that reduces the latency to serve the first token significantly! Great job!The harness in question is very importantOne important callout with 2 evidence pieces - the way you inference this model really matters. Kimi trained K3 with preserving thinking history, so when your harness uses it, it must send back the full thinking and tool use into the API to get the best next response. If your harness strips that out, you're not getting the most intelligence out of Kimi (shoutout to Niels from HF team for pointing this out). Additionally, the Composio folks, tested K3 on 3 harnesses, Kimi Code, Hermes and Claude Code. The difference in outcome was negligible, but the different in cost and number of tokens is definitely surprising! Claude Code (as a harness only) took 9x more Kimi tokens to get the same responses! This is also why Kimi Vendor Verified exists, their own held back benchmark of how well model providers serve Kimi across different quantization, tokenizer and KV cache settings. Benchmarks and the license! Ok let's start with the ugly... this isn't MIT, not remotely. This model is suspiciously served by all providers with exactly the same price (check OpenRouter) and requires inference companies to sign a contract with Kimi (I've no internal knowledge of this except that CW folks are working on it). Not something I particularly like, but hey... we're still advancing the frontier here! Speaking of frontier, this model approaches the frontier very closely. On DeepSWE, K3 sits just behind Fable 5 and GPT-5.6 Sol at 67%, beating GPT-5.5 & Opus 4.8. On Terminal-Bench 2.1 it takes second place behind GPT 5.6 Sol! It's 4th overall on Agentic Arena, with frontend design being genuinely good across the board - 1st on Design Arena

Das Wiener Traditionsrestaurant Figlmüller und die Schmuckmarke Arion Jewelry bringen eine limitierte Schnitzelkette aus vergoldetem Sterlingsilber für 119 Euro heraus, erhältlich im Arion-Store in der Wiener Spiegelgasse sowie im Figlmüller-Onlineshop. Der Anhänger bildet das berühmte Wiener Schnitzel bis ins Detail nach und trägt auf der Rückseite die Gravur "From Vienna with Love". Begleitet wurde der Launch von einer eigenen Aktivierung durch die Wiener Innenstadt unter dem Motto "Pursuit of the Golden Schnitzel", bei der Medien, Content Creators und geladene Gäste eingebunden wurden. Ich ordne ein, was das für Markenkooperationen zwischen traditionsreichen Institutionen und Lifestyle-Marken bedeutet. Außerdem in den Marken- und Marketingnews der Kalenderwoche 31 2026:

Diana Pasulka is a professor of religious studies at the University of North Carolina Wilmington and the author of several books. Her most recent, "The Others: UFOs, AI, and the Secret Forces Guiding Human Destiny," is out now.https://static.macmillan.com/static/smp/the-others-9781250394866/www.youtube.com/@Diana.Walsh.Pasulkahttps://substack.com/@dwpasulkawww.dwpasulka.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Use code ROGAN at https://BlueChew.com to get 10% OFF + Free Overnight Shipping on your first order. Switch today at https://www.Visible.com for just 25/mo. Or Save $10 on your first month of Visible+ Pro with code ROGAN.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

Everything we knew about getting found on search engines has been upended by AI. It's no longer enough to have a great SEO strategy to help people find you online. ChatGPT, Claude, Perplexity –– they need to see you too.Implementing GEO (generative engine optimization) is essential for getting your business surfaced and recommended by AI tools. Can you optimize being found by AI and still keep your humanness and authentic voice?Today's guest has gone all-in on becoming an expert in doing just that. Amy Yamada is a dear friend, AI expert, and one of the most heart-centered, connected, human people you could hope to meet.Amy Yamada is an AI Business Strategist and the founder of TopAuthority.ai, where she helps experts become the ones AI recommends. She and her team created the Discovery Hub - an AI Authority Infrastructure that structures a client's body of work so it's clearly understood, trusted, and surfaced by AI platforms. Known for making Generative Engine Optimization simple and actionable, Amy is leading a new wave of human-centered AI strategy through private advisory, group programs, and speaking.Tune into this episode to hear:Why now is the time to implement a GEO strategy for your businessThe top three things AI engines prioritize when evaluating contentThe code you need to add to your website and why it's not as hard as you thinkHow creating a discovery hub helps AI view you as an authorityWhere to start, whether you're an established expert or your business is newLearn more about Amy Yamada:Website:  http://www.amyyamada.comTopAuthority.ai: http://www.topauthority.aiFacebook: @amyyamadaInstagram: @amyyamadaConnect on LinkedIn: https://www.linkedin.com/in/amyyamadaMentioned: Free AI website audit: amyyamada.com/free-toolThe Discovery Hub: www.topauthority.ai/discovery-hubResources:Grab the first chapter of my new book Scale Solo: scalesolobook.comProgram: No BS Mastery: https://nobsmastery.com/programThe Price to Freedom Calculator™ - http://nobsmastery.com/priceGrab a copy of my book: Badass Your Brand - https://www.badassyourbrand.com/Program: No BS Agency Mastery: https://join.nobsmastery.com/agency-masteryNo BS Clients Lab: https://nobsclientslab.com/

Tim Robbins is an Academy Award-winning actor, director, writer, and producer known for such films as "The Shawshank Redemption," "Mystic River," and "The Hudsucker Proxy." He currently stars in the Apple TV+ series "Silo."www.apple.com/tv-pr/originals/silo/www.timrobbins.net Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Open an account in minutes at https://Chime.com/Rogan Switch today at https://www.Visible.com for just 25/mo. Or Save $10 on your first month of Visible+ Pro with code ROGAN.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

https://soundcloud.com/rene-de-paula-jr/a-jornada-do-heroi-e-um-mito-e Daniel Kahneman spent a lifetime studying judgment and distilled one warning into a single sentence: “Nothing in life is as important as you think it is while you are thinking about it” https://spacedaily.com/m-daniel-kahneman-spent-a-lifetime-studying-judgment-and-distilled-one-warning-into-a-single-sentence-nothing-in-life-is-as-important-as-you-think-it-is-while-you-are-thinking-about-it/ fact-checking do artigo acima via Perplexity https://www.perplexity.ai/search/hi-could-you-please-fact-check-PqAxb7wdTEOMOtJ5Nf.U5Q We’re getting closer to a breakthrough on hearing loss https://www.nationalgeographic.com/health/article/hearing-loss-hair-cell-regeneration-research Why does every mammal get 1 billion heartbeats in their life? https://youtu.be/tL9Lw250spc?si=6JIUikf1Ygnxl3aW Accepting free will doesn't exist could make us less hateful and ashamed https://theconversation.com/accepting-free-will-doesnt-exist-could-make-us-less-hateful-and-ashamed-282155 The pseudoscience of the heroic narrative https://carlosorsi.substack.com/p/the-pseudoscience-of-the-heroic-narrative?triedRedirect=true There is no redemption https://youtube.com/shorts/P3xAqlYjuww?si=lhkbq7yP-QUUgG33 a app do radinho!!!    http://radinhodepilha.com/radinho  canal do radinho no telegram:   http://t.me/radinhodepilha meu perfil no Threads: https://www.threads.net/@renedepaulajr meu perfil no BlueSky https://bsky.app/profile/renedepaula.bsky.social meu twitter http://twitter.com/renedepaula aqui está o link para a caneca no Colab55:  https://www.colab55.com/@rene/mugs/caneca-rarissima  para xs raríssimxs internacionais, aqui está nossa caneca no Zazzle: https://www.zazzle.com/radinhos_anniversary_mug-168129613992374138 minha lojinha no Colab55 (posters, camisetas, adesivos, sacolas):  http://bit.ly/renecolab meu livro novo na lojinha!  blue notes https://www.ko-fi.com/s/550d7d5e22 meu livro solo https://www.ko-fi.com/s/0f990d61c7  o adesivo do radinho!!!   http://bit.ly/rarissimos  minha lojinha no ko-fi: https://ko-fi.com/renedepaula/shop muito obrigado pelos cafés!!!  http://ko-fi.com/renedepaula

Forrest Galante is an international wildlife adventurer, conservationist, and author. His new special, "Alien Sharks: Untamed America," premieres July 29 as part of Discovery Channel's annual "Shark Week" programming block.www.discovery.com/shark-weekwww.patreon.com/cw/ForrestGalantewww.youtube.com/@ForrestGalantewww.forrestgalante.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Try ZipRecruiter FOR FREE at https://ziprecruiter.com/rogan Learn more about your ad choices. Visit podcastchoices.com/adchoices

→ Wanna use SEO to generate revenue? : Book a call here  https://www.breakingb2b.com/book-a-call Episode #494 and this week Sam presents the full AI SEO system he uses to rank SaaS businesses in ChatGPT, Claude and Perplexity. There's a huge amount here for you and Sam really gets into the detail with this one! - Ready to learn how to get AI SEO to work for your B2B?, then hit play now!   Sam give you:   

AI is changing the way patients find chiropractors, but that doesn't mean traditional SEO is dead. It means the rules are evolving.In this episode, you'll learn what AI Search Optimization really is, how it differs from traditional SEO, and what chiropractors can do today to improve their chances of being recommended by AI-powered search tools like ChatGPT, Google AI Overviews, Gemini, Perplexity, Microsoft Copilot, and Grok.We'll cover why authority matters more than ever, the trust signals AI looks for before recommending a clinic, common mistakes chiropractors make with their websites, and practical strategies to help your practice stay visible as search continues to evolve.Whether you're just starting to explore AI search or looking to stay ahead of your competition, this episode will help you prepare your practice for the future of online visibility.Episode webpage and blog post: https://propelyourcompany.com/ai-seo-for-chiropractors/Send in your questions. ❤ We'd love to hear from you!Webinar: The Hidden SEO Mistakes Costing Clinics Patients Right Now (And Easy Fixes You Can Start Making This Week)Save your spot: https://propelyourcompany.com/june/** Can't make it live? Register anyway. You'll get access to the limited-time replay. *** 

Sign up for Practi, a new platform that helps law firms use subscription billing.Here are the top 5 takeaways from this episode:* Perplexity Enterprise is a cost-effective, secure AI hub for lawyers. At $400/year, it provides SOC 2, HIPAA, and GDPR compliance while giving access to multiple top AI models without needing separate subscriptions to ChatGPT, Claude, or Gemini.* The Comet Browser unlocks agentic workflows that let AI control your browser on your behalf. By clicking “Control Browser,” you can instruct Perplexity to navigate websites, fill out forms, and complete tasks like adding calendar events without you lifting a finger.* Connectors (MCPs) let Perplexity directly read and write to tools like Google Calendar and Drive. Once connected, the AI can bulk-schedule deadlines from case management orders or contracts by computing dates itself using its Wolfram Alpha integration.* AI can handle contract redlining and document drafting in stages, with the lawyer staying in the loop. By combining Paxton for legal analysis with Perplexity's agentic browser to apply suggested edits in Google Docs, attorneys can maintain judgment and oversight while offloading manual work.* Whisprflow enables voice-driven input across all apps for around $288/year. Speaking instead of typing, with the AI intelligently cleaning up dictation errors, dramatically speeds up the process of giving instructions to AI tools throughout the day.__________________________Want your question to be answered on a future show? Fill out this short survey.Have subscription model question? Check out this free resource to ask all of your questions at notebook.practi.ai.Sign up for Paxton, my all-in-one AI legal assistant, helping me with legal research, analysis, drafting, and enhancing existing legal work product.Get Connected with SixFifty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, a business and employment legal document automation tool.Sign up for ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Gavel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, an automation platform for law firms.Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Law Subscribed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to subscribe to the weekly newsletter to listen from your web browser.Prefer monthly updates? Sign up for the Law Subscribed Monthly Digest on LinkedIn.Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mathew Kerbis'⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ law firm ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscription Attorney LLC⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Want to use the subscription model for your law firm? Click here to sign up for a new platform that helps law firms use subscription billing. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.lawsubscribed.com/subscribe

Over 3 hours, OpenAI, Anthropic, Google AND Microsoft all dropped new AI upgrades that are live. How you use AI in your work literally changes every day, as frontier labs are racing to roll out big quality of life updates between big model drops. How can you keep up? With our Friday Features show, where we break down the latest AI updates that are live and available to all, and we tell you how to use them and why they matter. This week did not disappoint. You don't want to miss what's now at your fingertips. JARVIS mode, anyone? ChatGPT goes Jarvis Mode, Claude can learn from you, Google unleashes spark agent and 7 more AI updates you can use today -- An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Anthropic Claude Opus 5 Model LaunchOpenAI Agent Hacks Benchmark SandboxOpenAI vs. Hugging Face Security BreachUS AI Kill Switch Legislation ProposalMicrosoft, Nvidia Defend Open Source AIAnthropic Opposes Open Weight Model CoalitionUS Accuses China's Moonshot AI of DistillationChinese Kimi K3 Model Closes Capability GapNvidia Chips Allegedly Used by Moonshot AIOpenAI Jarvis-Style Voice Assistant for CodexChatGPT Remote Desktop Voice Control ReleaseAnthropic Opus 5 Model Benchmark ResultsAnthropic Opus 5 Model User FeedbackStripe OpenRouter Acquisition TalksMeta Muse Agent and Feature UpdatesAlibaba Qwen 3.8 AI Model PreviewGoogle Gemini 3.6 Flash Model UpdateAnthropic Claude Voice Upgrades and Skill RecordingTimestamps:00:00 OpenAI agent hacks Hugging Face04:58 Discussing GPT-6's creative problem-solving07:33 Proposed AI shutdown legislation13:08 Debate over open-weight AI policies15:54 Future of consumer hardware20:01 Global competition with AI models21:21 US-China AI trade tensions26:38 Using AI for desktop tasks27:42 Discussing app screenshot capabilities32:24 Early user feedback and issues36:13 Discussing medium and low reasoning AI39:29 Gemini Spark launches for Pro usersKeywords: Claude Opus 5, Anthropic, best AI model, AI model comparison, OpenAI agent, sandbox breach, AI safety, AI kill switch bill, US government AI regulation, Hugging Face hack, GPT 5.6 Soul, rogue AI agent, autonomous AI agents, AI benchmark exploits, bipartisan AI bill, Department of Homeland Security AI shutdown, AI technical throttling, AI enterprise adoption, NVIDIA, Microsoft, open source AI, open weight models, Meta, Google, AMD, Cloudflare, GitHub, Block, IBM, Dell, Palantir, Perplexity, y Combinator, AI market resilience, Anthropic revenue model, AI token sales, consumer AI hardware, AI distillation, Chinese AI models, Moonshot AI, Kimi K3, intellectual property theft, NVIDIA chip export controls, US-China AI dispute, Amazon, AI image generation, ChatGPT work, Codex app, full duplex voice model, knowledge work automation, app shots, AI at work, Claude Voice, Gemini Spark, record a skill, cloud cowork, AI business impact, AI industry news, model weights, collaborative AI, AI productivity tools, AI cybersecurity.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

Irish SMEs often rank well on Google but are invisible to ChatGPT and Perplexity. This episode breaks down what a proper AI visibility audit must include, how to avoid free-tool traps, and why founder-led interpretation beats template-driven reports every time. BeaconSites City: Dublin Address: 77 Camden Street Lower Website: https://beaconsites.ie/ Phone: +353 1 234 6662 Email: info@beaconsites.com

В этом выпуске: разминаемся мелкими темами, смотрим как Perplexity запускает долгоживущих агентов, делаем выкройки из STL файлов, смотрим последние взломы от OpenAI, Саша рассказывает про спутники и как следить за ними, обсуждаем темы слушателей, и разбираемся почему San Andreas такой унылый. Шоуноты: [00:02:48] Чему научились за неделю techexplain (@techexplain): «Siri doesn't listen to words, it… Читать далее →

On this episode of Self-Publishing with ALLi, Dan Holloway covers three stories pointing in the same direction: books are everywhere. He reports on AI search engine Perplexity launching an ebook store, adding yet another major platform to the growing list selling books directly to readers. He examines the Library of Congress's initiative to acquire indie and self-published titles — and explains why copyright registration and deposit matter more than ever in the age of AI lawsuits. And he closes with Spotify's announcement that it has passed 100 million audiobook listeners, now dwarfing Audible in audience size. Show Notes Library of Congress self-published books collections policy US Copyright Office mandatory deposit PrePub Book Link (apply for an LCCN) Sponsor Self-Publishing News is proudly sponsored by PublishMe—helping indie authors succeed globally with expert translation, tailored marketing, and publishing support. From first draft to international launch, PublishMe ensures your book reaches readers everywhere. Visit publishme.me. Find more author advice, tips, and tools at our Self-publishing Author Advice Center, with a huge archive of nearly 2,000 blog posts and a handy search box to find key info on the topic you need. About the Host Dan Holloway is a novelist, poet, and spoken word artist. He is the MC of the performance arts show The New Libertines, He competed at the National Poetry Slam final at the Royal Albert Hall. His latest collection, The Transparency of Sutures, is  available on Kindle.

Timothy Alberino is an author, lecturer, and explorer. His latest release is a new edition of the ancient text “The Book of Enoch,” for which he wrote the introduction and commentary. www.youtube.com/@TimothyAlberinowww.timothyalberino.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Jeremy Knauff spent nearly two decades building a successful marketing agency — until a severe health crisis nearly killed him and took the business down with it. In this raw, unfiltered conversation, the U.S. Marine Corps veteran and founder of Spartan Media shares what it was like to lose everything, the autoimmune condition that brought him to the edge, and the moment a fellow Marine's suicide became the turning point that changed how he showed up in the world.Jeremy walks us through exactly how he rebuilt his authority from zero: writing his way onto top podcasts and into outlets like Forbes and Entrepreneur, then multiplying every feature into a network of content across social and video. We also dig into what "authority" means now that AI tools like ChatGPT, Claude, and Perplexity are the ones vetting experts before a journalist — or a client — ever does, and why pay-to-play media features can quietly work against you.If you're rebuilding after a setback, or wondering how to be findable and credible in an AI-driven world, this episode is your roadmap.In this episode:How a health crisis and years of chronic pain nearly ended Jeremy's career — and his lifeThe fellow Marine's suicide that became his turning pointThe exact content strategy that took him from invisible to Forbes and EntrepreneurHow to turn one media feature into dozens of pieces of contentWhat "authority" means when AI tools are the ones evaluating youWhy fake/pay-to-play media features can hurt more than they helpThe mindset shift that keeps you moving when you want to quitConnect with Jeremy:https://spartanmedia.com/Connect with Sabine:https://sabinekvenberg.com/resources

AI ready website pet business structure is what gets you recommended by ChatGPT and Perplexity instead of skipped, and most pet sitting and dog walking websites are not built for it yet. In this episode of Bella In Your Business, pet sitters, dog walkers, and pet care business owners will learn exactly what AI checks on a website before it recommends a business, and what to fix first. Web developer Erika Godwin of Barketing Solutions joins Bella Vasta to explain why keyword-stuffed pages don't work anymore, what trust signals AI is actually looking for, how schema markup works behind the scenes, and why raw server data matters more than Google Analytics for tracking AI traffic. This is Episode 473 of Bella In Your Business. IN THIS EPISODE: • How AI decides if your AI ready website pet business setup earns a recommendation, and what it skips over • What schema markup actually does, and why your site needs it • Why a generic services page keeps you invisible to ChatGPT and Perplexity • How raw server data shows AI traffic Google Analytics cannot track • What to do first if your website hasn't been touched in over a year Erika also breaks down why an AI-built website alone is not enough. A developer still handles the schema markup, DNS setup, and page structure an AI tool will never get right on its own, the exact parts AI is reading closely before it decides whether to trust your pet business. She walks through why a bio page for the owner matters, why one general services page is not enough anymore, and why AI cross-checks your directory listings and news mentions against what your website says before it trusts any of it. Bella and Erika also cover directories, citations, and how a hub and spoke content strategy helped one client's Bloomfield Hills dog walking page jump in rankings across search engines within one month of launch. Bella shares her own shift away from social media as the main marketing focus toward content, schema, and signals, and explains why she believes pet business owners who build this now will be trusted ahead of anyone who tries to catch up later. If you want to know exactly where your own site stands, Bella runs a free AI ready website pet business audit at jumpconsulting.net/audit that checks your schema, your AI citations, and what ChatGPT and Perplexity currently say about your business. TIMESTAMPS: [0:00] Cold open, pet parents are asking ChatGPT, not Googling [0:45] Welcome back Erika Godwin, web developer and referral partner [2:00] How search behavior for pet businesses has changed in 2026 [4:00] Why an AI-built website still isn't enough on its own [6:30] What AI actually reads, trust signals and schema explained [10:00] The raw server data most pet business sites are missing [13:00] From static brochure to trust engine, how site design has shifted [17:00] Building real service pages, location pages, and FAQs [19:30] Hub and spoke content, the Becky Lea Bloomfield Hills case study [22:00] Predictions, what happens to pet businesses that wait [26:00] Citations, directories, and getting featured in the news [29:30] How to check your own website's AI health today [32:00] Closing thoughts and where to find Erika RESOURCES: Get your own AI ready website pet business audit: https://jumpconsulting.net/audit Barketing Solutions: https://barketing.co Jump Mastermind: https://jumpconsulting.net/mastermind Book 20 minutes with Bella: https://jumpconsulting.net/20 AI For The Busy Human: https://bellavasta.com/busyhuman The AI booking story, Episode 465: https://jumpconsulting.net/episode-465 CONNECT: Website: https://jumpconsulting.net Instagram and Facebook, search Bella Vasta: https://bellavasta.com #AIReadyWebsite #PetBusiness #BellaInYourBusiness

¿Deberías tirar a la basura todo lo que sabes sobre SEO tradicional para apostar al 100% por el GEO (Generative Engine Optimization)? El verdadero dolor del creador actual no es la falta de palabras clave, es que los usuarios ya no buscan términos sueltos: le hacen preguntas conversacionales complejas a inteligencias artificiales como Gemini o Perplexity. En este video, LuisGyG desarma la transición del SEO al GEO, explicando por qué los motores de IA penalizarán a quienes intenten subirse a tendencias de forma deshonesta y cómo la IA puede diferenciar el nivel de profundidad de tu contenido (¡hasta detectando mayúsculas y minúsculas!). Aprenderás por qué el verdadero juego en 2026 radica en la autoridad de tu marca personal y cómo una simple táctica de un minuto en tu sección de comentarios puede salvar tu estrategia esta misma semana.

Zach Bush, MD,  is a physician specializing in internal medicine, endocrinology, and hospice care. He is the founder of Seraphic Group and Farmer's Footprint, a nonprofit dedicated to regenerative agriculture.www.youtube.com/zachbushmdwww.farmersfootprint.uswww.seraphicgroup.comwww.zachbushmd.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Visit https://ketone.com/Rogan for 30% OFF, or find Ketone-IQ at Target nationwide. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Host Mike Palmer connects with Monica Marquez, founder of ⁠FlipWork⁠ and founding director of the ⁠TIDE Center at UNT Dallas⁠, to explore how humans can navigate the rapid disruption of AI in the workplace. Drawing from her deep background in human capital, diversity, and leadership development at industry giants like Goldman Sachs, Google, and Bank of America, Monica brings a deeply human-centered approach to the AI revolution.  Mike and Monica skip the standard AI hype to discuss why simply rolling out AI tools isn't enough to drive real adoption. They dive into the psychology of AI integration, unpacking what Monica calls the "identity bottleneck" - the challenge workers face when shifting from a traditional mindset where "effort equals success" to a modern reality where "impact equals success." Monica also introduces her "long division" analogy for AI, explaining why we shouldn't ban the tool in classrooms or boardrooms, but instead require users to show their work and actively interrogate the AI's logic.  Key Discussion Topics:  * The Identity Bottleneck: Why our traditional conditioning to reward "grit and elbow grease" is causing resistance to AI's effortless outputs, and how to overcome the feeling of "cheating."  * Measuring AI Fluency: A look at FlipWork's psychometric diagnostic, which assesses "agentic velocity" (individual adoption) and "enterprise symbiosis" (organizational support).  * The Calculator Analogy: How educators and leaders can demand the "long division" of AI prompting to combat passive consumption ("work slop") and prevent cognitive atrophy.  * Agentic Teams: Why AI isn't a one-size-fits-all solution and how to orchestrate specialized models (like Claude, Perplexity, and Gemini) just like human team members.  * Democratizing Expertise: How everyday users can use AI as an accessible thinking partner to overcome biases, expand diversity of thought, and level the playing field.  Whether you're an educator, an enterprise leader, or an individual trying to disrupt yourself before you get disrupted, this episode offers a practical blueprint for multiplying human genius in the AI age. Subscribe to Trending in Education on your preferred podcast platform, leave a review, and share this episode with your network. Visit ⁠TrendinginEd.com⁠ for more episodes and conversations on the future of learning and work. Timestamps: 00:00 Welcome and Guest Intro 01:05 Monica's Career Journey 03:57 Why FlipWork and AI 07:41 Enterprise Adoption Reality 13:45 Measuring AI Fluency 17:13 Identity Bottleneck Shift 21:56 Teaching Critical Thinking 26:08 Bias Trust and Agency 30:31 Guardrails and AI Teams 33:41 Final Takeaways

A lo largo de los últimos 25 años los medios y Google han mantenido un pacto tácito que beneficiaba a ambos. Los editores dejaban que sus contenidos fueran indexados por el buscador y, a cambio, recibían visitas que se convertían en publicidad, suscripciones y salarios para los periodistas. Ese acuerdo se está desmoronando a gran velocidad y ha pillado a la industria informativa con el pie cambiado. El causante es la inteligencia artificial generativa. Antes el usuario tecleaba una pregunta, obtenía una lista de enlaces y pinchaba en alguno para encontrar la respuesta. Con ese sistema el posicionamiento en los buscadores era fundamental para cualquier editor. Ahora el propio buscador da la respuesta ya masticada en lo alto de la página sin necesidad de acudir a ningún otro sitio. Google está dejando de ser un motor de búsqueda para convertirse en un motor de respuestas. No hay medio de comunicación que no lo haya notado. El tráfico orgánico proveniente de Google del Huffington Post y del Washington Post ha caído a aproximadamente a la mitad en los últimos 3 años. Business Insider se ha hundido un 55% desde 2022 y ha tenido que despedir al 20% de su plantilla. La revista People ha pasado del 60% al 30% de visitas procedentes de Google. Las webs pequeñas han sufrido lo mismo y muchas han terminado cerrando. Dos movimientos de Google han agravado aún más el problema: los AI Overviews, resúmenes automáticos colocados sobre los resultados, y el AI Mode, que responde como un chatbot y ofrece muchos menos enlaces. Los editores están reaccionando en varios frentes. En el frente técnico tratan de poner nuevas barreras contra los rastreadores porque el viejo Robots.txt ya no disuade a unos robots que suponen más de la mitad del tráfico de la red. El segundo frente son los tribunales. Penske Media, editora de Rolling Stone, Variety o Billboard, es la primera gran empresa periodística que lleva a Google ante un juez por la vía antimonopolio. Denuncian que sus ingresos por afiliación se han desplomado más de un tercio desde finales de 2024. Se encuentran realmente ante una trampa ya que cada artículo publicado alimenta a la máquina que después roba las visitas, pero bloquear al buscador equivale a desaparecer del principal escaparate. El tercer frente, el de los acuerdos comerciales, parece contradictorio de primeras. El New York Times está pleiteando contra OpenAI y, al mismo tiempo, licencia su material a Amazon. News Corp ha firmado un acuerdo con OpenAI mientras algunas de sus filiales han demandado a Perplexity. La industria no sabe aún si el futuro pasa por cobrar peaje, por litigar o por ambas cosas. El marco legal sigue abierto y sus primeras decisiones no favorecen del todo a los editores. Ante semejante incertidumbre algunos medios ya vislumbran un futuro sin Google y eso les está llevando a apostar por los boletines personalizados, las suscripciones y los actos presenciales, una vuelta a la relación directa con el lector. Desconocemos por dónde irá esto, pero lo que salga de aquí determinará el aspecto de internet en unos años. Lo que no volverá es aquel viejo pacto tácito porque Google ha cambiado y ahora se parece más a un chatbot cuyo único objetivo es que no salgas de ahí. En La ContraRéplica: 0:00 Introducción 3:47 La rebelión de los medios 36:16 Las restricciones del aire acondicionado en Europa 43:54 El aire acondicionado en Estados Unidos 48:17 El SaaSpolalipsis · Canal de Telegram: https://t.me/lacontracronica · “Contra el pesimismo”… https://amzn.to/4m1RX2R · “Hispanos. Breve historia de los pueblos de habla hispana”… https://amzn.to/428js1G · “La ContraHistoria del comunismo”… https://amzn.to/39QP2KE · “La ContraHistoria de España. Auge, caída y vuelta a empezar de un país en 28 episodios”… https://amzn.to/3kXcZ6i · “Contra la Revolución Francesa”… https://amzn.to/4aF0LpZ · “Lutero, Calvino y Trento, la Reforma que no fue”… https://amzn.to/3shKOlK Apoya La Contra en: · Patreon... https://www.patreon.com/diazvillanueva · iVoox... https://www.ivoox.com/podcast-contracronica_sq_f1267769_1.html · Paypal... https://www.paypal.me/diazvillanueva Sígueme en: · Web... https://diazvillanueva.com · Twitter... https://twitter.com/diazvillanueva · Facebook... https://www.facebook.com/fernandodiazvillanueva1/ · Instagram... https://www.instagram.com/diazvillanueva · Linkedin… https://www.linkedin.com/in/fernando-d%C3%ADaz-villanueva-7303865/ · Flickr... https://www.flickr.com/photos/147276463@N05/?/ · Pinterest... https://www.pinterest.com/fernandodiazvillanueva Encuentra mis libros en: · Amazon... https://www.amazon.es/Fernando-Diaz-Villanueva/e/B00J2ASBXM #FernandoDiazVillanueva #prensa #ia Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

Send us Fan MailGoogle still matters, but the way people search is shifting under our feet. More buyers are starting with AI search tools like ChatGPT, Perplexity, Claude, and Gemini, then making decisions from the answer they get back. When that happens, ranking well is not the whole game anymore. The new question becomes: will an answer engine cite your business by name when someone asks where to buy a shed near them?Kimberly Reynolds from AI Advantage Agency joins us to explain Answer Engine Optimization (AEO) in plain terms and connect it to what shed dealers care about most: leads, calls, and sales. We dig into the practical building blocks that help AI systems understand your business, including schema markup, entity signals, and why WordPress tools like Rank Math can simplify setup. We also talk about content strategy that works for AI search, like answering one question per page, leading with the answer, and adding FAQs with the right schema so your site becomes easy for AI to parse and trust.We also cover what is changing in paid media, including how Meta's ad algorithm now relies heavily on creative and copy, plus why Google Business Profile and reviews are even more important as Google rolls out AI Overviews and more searches end without a click. If you've got a solid website, a local presence, and a limited marketing budget, you'll walk away with a clear 90 day plan to improve SEO, AEO, and local SEO together. Subscribe for more shed sales and marketing breakdowns, share this with a dealer friend, and leave a review so more people can find the show.For more information or to know more about the Shed Geek Podcast visit us at our website.Would you like to receive our weekly newsletter?  Sign up on our website: shedgeek.comFollow us on Twitter, Instagram, Facebook, or YouTube at the handle @shedgeekpodcast.To be a guest on the Shed Geek Podcast visit our website and fill out the "Contact Us" form.To suggest show topics or ask questions you want answered email us at info@shedgeek.com.This episodes Sponsors:Studio Sponsor: Shed ProVelocity 360J Money LLCCardinal LeasingiFAB LLCIdentigrow

Is Google AI changing your website traffic? Quite possibly, but the real answer is in your data. In this episode of the Elevated Marketing Podcast, Jennifer Denney, founder of Elevated Marketing Solutions, talks through Google AI Overviews and AI Mode and what they may mean for your website traffic, SEO, and marketing results.Website traffic has been a major marketing measurement for years, but AI-powered search is changing how people find answers. Some users may get what they need directly from Google AI Overviews or continue their research inside AI Mode before ever clicking through to a website. That can lead to fewer clicks, even when your business is still being seen.Jennifer explains the difference between Google AI Overviews, Google AI Mode, and other AI tools like ChatGPT, Perplexity, and Claude. She also shares why Google Search Console is still one of the most important places to look when trying to understand what is happening with your visibility, impressions, clicks, and conversions.Read the full blog over at: https://elevatedmarketing.solutions/are-google-ai-overviews-and-ai-mode-affecting-your-website-traffic/Tired of vague marketing advice? So are we. This podcast brings you real, in-the-trenches conversations about what actually works no scripts, no fluff, just honest strategy and real-time insights.

Cassie Coppersmith is an independent researcher studying ancient civilizations and archaeological mysteries, and host of the “Secrets in Stone” podcast.www.youtube.com/@CassieCoppersmith Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Get 30% off + 2 free gifts at https://ARMRA.com/rogan Learn more about your ad choices. Visit podcastchoices.com/adchoices

Is traditional SEO officially dead, or has search simply evolved? In this episode of "Why SEO isn't enough anymore: The rise of GEO", hosted by Àlex Rodríguez Bacardit, Clemens Rychlik from Hello Operator joins the show to examine the seismic shift away from Google's Page 1 and into AI interfaces like ChatGPT, Claude, and Perplexity.Together, they explore why customer decisions and conversions are now happening directly inside LLMs long before anyone visits your website, and why traditional SEO metrics fall apart in a probabilistic search landscape. Clemens shares practical insights on how to adapt your content so AI models actually cite your brand, why admitting what your product can't do actually builds trust with LLMs, and the dangerous "GEO hacks" currently being sold across the industry that you should stay far away from.Hosted by Àlex Rodríguez Bacardit: https://www.linkedin.com/in/alexrodba/Guest: Clemens Rychlik (Hello Operator): https://www.linkedin.com/in/clemensrychlik/If you enjoyed the episode, make sure to subscribe to the channel, hit the like button, and let us know in the comments how your team is adapting to AI search!Support the show

What if the reason you're not getting more sales isn't your website... it's that ChatGPT doesn't know you exist?Millions of people now ask ChatGPT, Claude, Gemini, and Perplexity which products, services, and businesses they should choose. If your business isn't being recommended, you're invisible at the exact moment customers are ready to buy.In this episode, PR expert and former U.S. diplomat Gloria Chou shares the five biggest ways to increase your AI visibility—without spending thousands on SEO agencies, paid ads, or complicated software.You'll learn: Why ChatGPT recommends some businesses but not others  The difference between traditional SEO and AI visibility  Why PR is becoming more important than ever for getting discovered  How media mentions influence AI recommendations  Website changes that help AI better understand your business  Free ways to check whether AI is already recommending you—or your competitors  Simple steps you can take today to become more visible in AI search If you're a small business owner, Shopify brand, Etsy seller, coach, consultant, or entrepreneur, this episode will help you understand how customers are finding businesses in 2026—and what you need to do to become the one AI recommends.In my free AI Visibility Masterclass, I'll show you how small business owners are using PR, media features, and credibility signals to become the businesses AI recommends. You'll learn how to earn press without hiring a PR agency, increase your AI visibility, and get discovered by customers at the exact moment they're ready to buy.Watch the free masterclass:

What happens when someone asks ChatGPT, Claude, or Perplexity to recommend an expert in your industry? Does your name appear, or does your competitor get the opportunity?In this episode, Holly welcomes award-winning PR strategist, former U.S. diplomat, and Small Business PR host Gloria Chou back to the podcast for a timely conversation about PR, AI visibility, and the changing way customers discover brands.You'll learn how podcast interviews, media mentions, expert quotes, and other third-party features can strengthen your authority signals. Gloria also shares how she uses Perplexity, ChatGPT, and Claude for different parts of her business and how entrepreneurs can use these tools to research relevant angles, write stronger pitches, and compete with larger brands without a massive PR budget.00:00:49 — The question every entrepreneur should ask about AI recommendations00:02:14 — Gloria Chou shares what building a life-first business means to her00:03:28 — How AI is changing discovery, trust, and purchasing decisions00:04:39 — Why PR features can become powerful authority signals00:06:02 — The opportunity for small businesses to compete with major brands00:07:40 — How AI tools are making PR research and pitching more accessible00:08:36 — Using Perplexity to find trends, angles, competitors, and podcasts00:10:31 — Why specific data makes a pitch more compelling00:12:14 — The two elements every strong pitch needs: specificity and relevance00:14:30 — Gloria's CPR pitching method explained00:15:29 — What to prioritize when you only have a few hours for visibility00:17:42 — How to find PR opportunities through HARO, Substack, and social media00:20:26 — How Gloria uses Claude, ChatGPT, and Perplexity in her business00:23:36 — Why AI visibility creates an opportunity for quieter, smaller brandsCONNECT WITH GLORIA:Website: https://gloriachoupr.com/Instagram: https://www.instagram.com/gloriachoupr/

In this episode, Lex chats with Jeff Grimes — who is Head of Live Events Products at Perplexity, the AI company that has evolved from an "answer engine" into an "agent platform" built around Perplexity Computer, its multi-agent digital worker. They discuss how Perplexity has shifted financial research from the how to the what, letting a user describe an outcome in a single sentence while Computer orchestrates 20+ frontier models, direct tool calls to licensed live data, and finance-specific skills to produce the artifact. Jeff explains the enterprise strategy behind traceability - the north star that 100% of every quantitative figure traces back to its source filing - alongside bring-your-own-license connections via MCP and the consumer "personal CFO" vision powered by Plaid. They explore what 5x revenue growth on a 34% headcount increase signals for finance jobs, and why the future looks like a 24/7 family office that proactively surfaces and, with permission, executes financial actions for everyone. NOTABLE DISCUSSION POINTS: The “how to what” collapse is the real product thesis, not just better models. The shift to zero-shot rests on three stacked unlocks: direct tool calls to licensed live data (Quartr for earnings transcripts, unusual whales for insider and political holdings, SEC filings for historicals) instead of relying on web freshness; a thinking-model router that orchestrates 20+ frontier models in parallel, matching the model to the job (a heavy thinking model for macro analysis, a lighter one for ticker-matching 550 names); and ~20 opinionated finance skills (DCF, three-statement, LBO, comps) tuned through expert-led evals. Together they turn one sentence into a polished equity-research artifact. Traceability is the enterprise wedge, framed as “don't trust and verify.” The stated north star is that 100% of every number in any output is hover-traceable back to the source filing - pre-scrolled to the page, highlighted, with the full chain of calculations exposed. The framing inverts the usual “trust but verify”: assume the user won't trust the model, so trust must be earned per number. Paired with bring-your-own-license via MCP (FactSet, LSEG, Morningstar, CarbonArc, PitchBook), this is the concrete answer to why regulated institutions get comfortable adopting. The productivity and jobs signal is quantified and lived internally. Perplexity grew annual run rate 5x while increasing headcount only ~34%. Computer began as a company-wide Slack bot where every request was visible to all employees; Jeff now runs 9–10 scheduled cron jobs each morning and says essentially all code is written first by his agents. On the consumer side, the emergent pattern is build-your-own long-tail apps that no roadmap-bound product could serve - a DraftKings-addiction accountability system that emails a user's spouse on any bet, or a GitHub-style heatmap of daily spending - which is the real substance of the personal-CFO bet. TOPICS Perplexity, Perplexity Computer, Perplexity AI, Google, Shadebot, Plaid, Yodlee, Claude, ChatGPT, AI, Artificial Intelligence, LLM, CFO, financial services, AI commerce   ABOUT THE FINTECH BLUEPRINT

As a nurse with MS, I’m interviewed about AI’s real role in care: pattern recognition, human-in-the-loop skepticism, and the Three T’s and Two C’s framework. Click here to view the printable newsletter. More readable than a transcript. Click here for a verbatim transcript Summary I sit in the guest chair on Practical AI in Healthcare with Steve Labkoff. I walk through my experience feeding my own symptom logs, lab results, and ten years of clinician notes into an AI LLM: a physical therapy referral I needed and hadn’t scheduled, a medication side effect my neurologist later confirmed, and a rating scale buried in my chart that no one had surfaced. I describe the less impressive side: the four-pound box of unsorted paper my primary care practice mailed me and the 296 pages of unsearchable PDFs I got back from another system in fifteen minutes. Along the way, I lay out my framework for judging any digital health tool, the Three T’s and Two C’s: time, trust, talk, control, and connection, and explain why I insist on keeping humans in the loop even though the research on that is more complicated than people assume. This isn’t a pitch for AI in healthcare. It’s a working nurse and patient’s honest field report. What’s your experience been feeding your own health data into an AI LLM? Tell us in the comments. Episode Transcript Proem I usually ask the questions. This time I'm the guest. I met Drs. Steve Labkoff and Leon Rozenblit a couple of years ago at a DCI Network conference. They host Practical AI in Healthcare, a show I've listened to steadily, though it creates more tension for me than any other podcast I keep coming back to. Usually, I jettison podcasts that do that. I stay with this one because I approach AI in healthcare the way I approach best health; I'm an N of one and resist generalizing, while most guests do a fair amount of it. I bristle at most of them, wanting the shades of gray that reflect deep understanding. In four of 33 episodes, the guest has had lived experience: ePatient Dave DeBronkart, Amy Price, Hugo Campos, and me. I invited Steve and Leon to join my virtual Reckoning group, which I've hosted since 2019. We give podcasters warm critiques of selected episodes: the kind of feedback you give when you've made a hundred mistakes yourself, can spot them quickly in someone else's cut, and have endless thoughts about production, audience, dissemination, and life. They took the critique well. When Steve later asked me to come on his show to talk about how I use AI, not the theory but the daily grind, I readily agreed. They let me publish it here unchanged, apart from this Proem and Reflection. I struggled to prepare for this conversation. I wanted to wear all my hats, but had to narrow my focus to two. I chose my lived experience and nurse hats. Underneath it all was the question I keep circling back to. Not a cure. Best health, the most function, and Hello, and welcome to this week’s edition of Practical AI in Healthcare. My name is Dr. Steven Lapcoff, and this week I’m actually on my own because my partner, Dr. Leon Rosenblatt, is actually on spring break with his kids, so I am covering for him and he’ll be back in the next week. This week we have a guest who we met at a conference in Boston a few months ago at the Beth Israel at the DCI network. Steven Labkoff: We have Danny van Leeuwen. Danny is a nurse. He has background in giving actual physical care to patients. He actually runs his own podcast called Health Hats, the Podcast, and he’s been using AI in both his personal life and in his professional life very extensively. Also, Danny has a significant medical condition, and I’ll let him explain that in the course of the discussion because it’s with that lens that we got introduced at our patient-centric AI conference, and that’s why we thought it’d be a good idea to have Danny come and have a chat with us. So welcome to the podcast, Danny. How are you today? Health Hats: I’m good. Thank you. Thanks for having me. I appreciate it. Steven Labkoff: So Danny, as you probably have heard because you’ve helped us with our podcast, and for that I want to say thank you. For those who are listening in, Danny runs actually a group that actually helps folks running podcasts improve their podcasts, and he’s had Leon and I on many times to listen to critiques and feedback, and it’s been very, very helpful. Danny, we often start our podcast with asking for folks’ origin stories, like how did they get their cape and their superhero tights. What did you do to get you to this point in your life? And just tell us the background of what brought you here. Health Hats: Oh, thanks. So I’m a child of Holocaust survivors, and my parents– when I was young, my parents were active in the civil rights and fair housing movement in the ’60s. And when I was 16 and I was thinking about the war in Vietnam and worried about getting drafted, I wanted to learn what I could learn about the draft and how I could protect myself and manage. And I went to a church in downtown Detroit, and I went for a session of draft counseling as, you know, a little precocious at 16, and I found it fascinating, and they found me fascinating, and they encouraged me to become a draft counselor. And so I, uh, I actually took their course and became a draft counselor, and what I learned is that you change systems from the inside, not the outside. And I learned how the sausage was made, and that, uh, really pointed me in a direction. The way I got into nursing is really because I didn’t want to cut my hair I had an opportunity for a job at one point, and I could have read water meters or become an aide at the Detroit Psychiatric Institute. And reading water meters paid more, but I didn’t wanna cut my hair, so I got the job as, as nurse’s aide. And while I was there, they introduced me to the idea of going to nursing school, which was amazing. Steven Labkoff: It was more– You got paid more to read meters, water meters, than you did- Health Hats: Yes. Steven Labkoff: That’s unbelievable. Life gives you some real interesting turns and twists, doesn’t it? Health Hats: It does. And I was really fortunate because my first jobs in nursing were in physical rehabilitation and home care. I just happened to be in a place where the Holyoke Visiting Nurses was dying to hire a guy, and I was a brand-new nurse, and they ended up hiring me. And so my first introduction to nursing was not in acute care. It was in home care, and actually, I was the first male public health nurse in Western Massachusetts in 1976. And really, what I learned there was that most healthcare does not occur in the medical system. It occurs outside the medical system. And so when I ended up getting into medical care, it was always so interesting to me that everybody there thought this is where, you know, health happened, which it doesn’t. So over the 20 years of working as a nurse, I’ve worked in, other than the rehab and home care, I’ve worked in the emergency department, I’ve worked in ICU, I worked in pediatrics, behavioral health. And after about 15, 20 years, I shifted from becoming a student of individual health to a student o- of organizational health. And what I mean by that is I got into performance improvement. I led a couple of electronic health record implementations. I had a couple of gigs in the C-suite. I did some consulting. Now, in 2009, I was diagnosed with multiple sclerosis, and when I was diagnosed, I learned that I had had it for 25 years. And since my father died young, he died at 45 when I was 19 of his second heart attack, and so every time I would have some kind of episode, I would get a cardiac workup. And by the time the cardiac workup was done, you know, the episode was over, and this went on two, three, four times a year for a long time. And there was a pattern there, and nobody was connecting the dots for 25 years. That’s very important to me because the pattern of what was going on was in my records for 25 years, but nobody had synthesized it. Steven Labkoff: Yeah, they may have been biased, right? Because of your family history and having these episodes, you know, as a clinician, you get very biased by family history, and that can actually lead you down roads which may not be correct, and it sounds like that’s precisely what happened with you. Health Hats: So I’ve– I wanna bring in the caregiver role because I have been a caregiver for my grandmother, my mother, and a son in their end-of-life journeys. So I’ve been on many sides of very difficult decisions. As you said, that my shtick is health hats, and I’m health hats because I’m a patient, I’m a caregiver, I’m a nurse, I’m an advocate, I’m an informaticist, I’m a podcast host. I wear a lot of hats. And wearing many hats has gotten me a seat at many tables because they can check off boxes. When it was really different to be bringing patients o-on board, I was an easy choice. Uh, I was at the table for technical expert panels at CMS, at National Academy of Medicine, at AHRQ, National Quality Forum, PCORI, Patient-Centered Outcomes Research Institute. But really, I wasn’t really there in it for the seat itself. My goal was always to open seats for people who weren’t there yet Now let’s build the bridge, since this is a podcast about AI, let’s build that little bit of that bridge. So my first, like, serious experience with– Well, I don’t know about my first. I was involved in something that you probably are familiar with, which was the Blue Button Plus program, and my goal in that, I was there both as a patient and as somebody who was working with people with disabilities. I, I was VP of quality for an organization that supported about 40,000 people with disabilities. And my goal for that couple of years of weekly or every other week, I can’t remember, calls was, uh, to add a f- a caregiver field to the data set, and to also introduce the idea that what people needed was information that would be able to say what works for me when I’m in pain and what works for me when I’m afraid, which was an issue for me, and it was an issue for the organization that I was working with at the time. Now, I have to say that the caregiver field got added, so I felt some success in that. But as a nurse leader in the informatics group I was part of, really they were only interested in putting a name in the field, not doing anything with that information, which I- Just collecting, so just collecting the data. Steven Labkoff: They didn’t care what the data was used for? Is that what you’re saying? Health Hats: Correct. Yeah. And I couldn’t– got no traction on the pain and fear, which now that I’m older, I understand why, how difficult that is. Nevertheless, it’s something that’s important to patients and caregivers. So I think I would close this section with that I am both an early adopter of technology and a rapid skeptic, that I’m kinda making this number up, but I’ve probably tried over 100 health apps, and I would say that I’ve used five more than three times. And so I think there’s a gap between what’s promised with digital technology and what’s useful for people. So that’s really why I’m here and what’s guiding for me in this. Steven Labkoff: So let’s take it to the next step. In our prequel, I didn’t even know about your personal background to that degree. Mm-hmm. We can take that one offline later about the Holocaust survivor issues. We, we have family, I have family in that same situation, frankly. Let’s change gears and talk about the challenges that you’ve seen. You opened the door a little bit on that a few minutes ago- Yeah … in terms of people wanting to collect data but not necessarily doing much with the data, not being able to understand the true value of the data to some degree. And you said it yourself, people weren’t connecting the dots. Medical records have always been complicated. They’ve always been bulky. They’ve always been full of information, some of which is really relevant, a lot of which is not so relevant, and connecting the dots to making that a, uh, an important information source is not always an obvious task. So what, what was the particular angle on that challenge that you were trying to gun at? Health Hats: Well, I think we have to take a step back- and think about what is– Well, I’m just gonna speak for myself, okay? I know that I often, you know, as I said, I get asked to sit at the table because people can, you know, check boxes, like is that I’m a patient. I wanna be clear that I’m a privileged white old man with MS living in Boston, but I’m an N of one, and I don’t represent other patients. I’m representing myself here and my perspectives. My goal in terms of my health is best health, and what I mean by best health is optimal health and function, physical, mental, spiritual. Not a cure, but best health for where I am, what I have right now. And to get there, I need my own health data, not just what’s in my clinician’s chart, but what I know about myself, my circumstances, my environment, my history, my habits. Not just my medical history, my life history, my treatment responses. And so that’s like patient-reported data, and that’s stuff that’s only exists because I observe it and sometimes I record it And that’s where it falls apart right away. You were just alluding to some of it, that there’s all this medical data and what’s useful about that. I think Dave DeBronkart was a guest on your show. And when he launched his Gimme My Damn Data campaign, I responded to him with, “Watch what you wish for. You’ll be trying to drink dirty water from a fire hose.” And, and that was years ago, and it’s still true. So six months ago, I, I’d been on a mission to gather my medical data, and my– I’d been with my, uh, primary care practice since 2011, and I wanted all that data from 2011 to 2025. This was, like, in December I started on this crusade of trying to get my data. And actually, two months later, I got a box, a four-pound box of paper, and it was paper that was not in chronological order. And it’s just sitting right here. I’ve scanned it in. It’s not, um- Was it in– Steven Labkoff: Was it a printout of Epic or something, or was it actual- Health Hats: It’s a computer printout. It seems like it’s a vendor that they use to- Steven Labkoff: It wasn’t digital. They sent you, literally sent you a box of paper. Health Hats: Yeah, it was a box of paper. Oh. And then I use a lot the, the Beth Israel Lahey Mount Auburn system, and I asked for the last three months of my records, and I got 296 pages of redundant, non-searchable PDFs, and I got that in 15 minutes. Uh, I see a lot of doctors, so maybe I had seen Hmm. I think I had maybe eight or nine visits, and it just happened to be a three-month period that was busy for me, but I got s- 296 pages. And so that really adds to your comment, which is that access to data and access to usable data are really different. Steven Labkoff: Oh, absolutely. And yeah, I’ll tell you, in my world, I think you know that I’ve worked in the life sciences for many, many years, and we are consumers of healthcare data on many levels. We consume medical claims, we consume electronic medical records, and one of the hardest things about using medical records for research or for outcome studies and things like that is the very fact you’re describing, which is the data tends to be sparse, it tends to be poorly organized. It doesn’t always come in an encoded fashion. Thank God most of what we get these days is at least digital. No boxes of paper for us these days, but it wasn’t so long ago that when it was all paper, we couldn’t get that data in the first place. It just wasn’t even gettable. So at least you’ve made some progress. And- Yeah … yeah, I know that you sit on some national level boards, uh, around outcomes, and you can talk about that in a moment. But those are, you know, those boards are trying very hard to come up with outcome studies and ways of– Let me back that up. They’re coming up with ways of using data to perform outcome studies by harmonizing and, and distilling down to usable forms of this EHR data, which is so challenging. Health Hats: I think what’s key, I– like I, I think I w- I’d like to focus on my data. And so what I wanna do is I wanna see patterns. I wanna see patterns that takes my circumstances, my environment, my habits, my treatment over time, and because I think that these patterns are how I formulate the right questions, so the right questions before I go into a clinical encounter. They’re how I track when something is actually working, and it helps me to coordinate across care teams that don’t talk to each other and make decisions that I can live with that help me attain this goal of best health. So that’s the job, formulate better questions, g- seek better answers, make better decisions. And AI is the tool that I try to use to do it. Now, whether it’s up to the task or not is different. I wanna stick in the nursing angle, if you don’t mind- You know, one of the things that I learned the way I got started in nursing is that my goal as a nurse was to put myself out of a job. Steven Labkoff: So that sounds counterintuitive, but what I mean is from minute one with a patient and family, I’m planning my exit. Like, and to do that, I need maximum face time. I need real present, real conversation, real relationships, not less charting. I was gonna say not charting, not documentation, so that’s just ridiculous. Health Hats: But less, you know. The way you do that, I think, is, you know, less charting, less documentation, you know, not hunting through information you can’t find. And that’s where nursing, that’s a genuine promise. So pattern recognition across specific cohorts of patients. So as a nurse, even though I worked a lot of different places, in each place I worked, there was commonalities. In– When I lived in West Virginia and I was an ER nurse in a super rural hospital, if I had had more information about my patients, their families, I could get– an AI could help me surface those patterns that exist for the people that I’m taking care of, I think I could get time back as a nurse. And if the nurse gets time back, then the patient and family gets the presence of the clinician. So that’s the trade that I’m interested in I wanna go back to that thing about pain and fear. I wanna add what I’ve learned working on the blue button, plus I wanna add cognition. So when you think about it, the data almost never captures the variability of pain, fear, and cognition, and those things are really important because pain changes what you can do and what you can decide. Fear closes your heart. It closes your mind. And so when you’re scared in a clinical encounter, you’re not making good decisions. You’re just saying yes to end it. And cognition is, you know, it varies. Like I can absorb better at 10 in the morning on a good day compared to 3:00 in the afternoon when I’m spent. You know, you could extrapolate this to other people. They have their own particular patterns and circumstances. But I think What I’m trying to get at in all of this is it isn’t first about the data, it’s first about what about life and what about the things that are important to people, uh, patients, caregivers, and the clinicians that they partner with, and how can AI help them? Steven Labkoff: So you’ve explained to me in the pre-call that you’re doing some of this work, so maybe you can unpack a little bit about what it is you’re actually doing with it and how it’s helping or, in some cases, not helping those efforts. Health Hats: Well, what have I done? I, I’ve done different things. One of the things that, that I’ve done is to try to build my toolkit. You know? So when I say build my toolkit, I’m a, I’m a, a conglomeration of symptoms. I mean, you know, I’m, I’m not MS, I’m not my symptoms, but they’re big and they’re there, and I feel like I’m trying to, I’m trying to figure out for anything that I have to deal with, whether it’s any of the different kinds of pains I have, my, my anxiety, my bladder, you know, my mobility, I have challenges, and I, I need a toolbox. I need a toolbox, and the way I think is I need at least three things that will work so that when they happen, I got something I can go do, and pretty much the most common thing is drink water. Drink water is by far the most successful intervention across all of my symptoms. It’s kind of amazing. It’s so cheap, so easy. It isn’t the drugs. Okay, but so how do I do that? Well, for me, I’ve done that partially just in my head. Partially I’ve done that by keeping lists. Like, I keep track of the steps I take. I keep track of the amount of time I play music. I keep track of my falls. I keep track of my weight. And so I use digital tools to do that when I can. Steven Labkoff: I also record my clinician visits because- When you say record, do you mean like audio record or dig- Health Hats: Yeah. Yeah, audio record, right. And, uh, until recently I used Abridge, which is a company that, um- Steven Labkoff: How did you get to use Abridge? You– I thought Abridge was only selling basically into doctor’s offices, uh, from the clinician side. Do you- Health Hats: So I was before that. Ah. And they started as a patient-facing product, and actually they sponsored my podcast for three years. So I was pre that. So putting all that together, so I play with, you know, trying to put into Claude There’s nothing magic or special. You know, it’s me playing, just trying stuff. You know, some of it, you know, my wife will say, “Hey,” she sees a pattern. My kids will see a pattern, or I’ll- Steven Labkoff: Give, give, give us an example of what, of what this looks like. I mean, you’re saying you’re giving Claude or another LLM- Yeah … a series of symptoms, or you’re giving it a series of, plus your data. Like, unpack it and let us know. Yeah. What have you did- Okay, so what- … with the system, and how is it working for you? Health Hats: I’ve done a couple of different things. One is, you know, I have a spreadsheet, and I just put the spreadsheet in, you know, as a document or whatever you call it when you have a project and, you know, you load. I load my spreadsheet. I keep a annual summary, and I keep the year that I’m working on. And I will have fits of journaling. You know, I, this is not something that I am, like, super consistent on, but I’ll, especially when I’m struggling with something, if I’m struggling with my blood pressure or I’m struggling with my mood. I have a progressive mobility thing going on, and I’ll put that in and I’ll prompt. I’ll say, “Can you– do you see a pattern in this?” You know, and I’ve gotten, you know, that there’s- Steven Labkoff: Has it given you some insights? Is it… Like, give me an example of some of the insights it’s actually given you that you didn’t see yourself. Health Hats: Well, I’ve gotten, like, uh, it’s kind of humorous. But, but I’ve gotten, like, you know, “Have you thought about seeing a physical therapist?” And I, I have. You know, I have a physical therapist, uh, that I don’t go to very often. You know, my relationship with her is I go for a tune-up. But they’ll– I, I want– It’ll show, like, I’ll do my sort of things are clearly, you know, I’m not walking as far, I’ve fell on a few times, you know, and I’ll get this suggestion, you know. I also– What else have I done? Oh, oh, uh, once I had a medication that I was taking for neuropathy, and I was– my mood had, like, changed considerably and, you know, I got a thing on that might be a side effect. You know, “Have you talked to your doctor about this?” Steven Labkoff: And I- And you got that out of the LLM? You fed that to the LLM? Health Hats: I did. Yeah. Steven Labkoff: And it suggested it was a side effect, which you didn’t figure out. Health Hats: I didn’t. A neurologist said that he thought– He said, “It sounds like you have an allergy to it.” And, you know, he wanted it to be listed as an allergy because he thought it was very possible that he’s had people that have had a problem. Steven Labkoff: When you tell me that you’ve loaded your data, you give the LLM your signs, your symptoms, you give it your labs, you give it what’s in, in the system, and it comes up with a recommendation that you hadn’t thought– Now, you’re a clinician. You’re a nurse. Yeah. You’ve been a nurse for many, many decades. Health Hats: 50 years. Steven Labkoff: 50 years. And does it surprise you that it comes up with stuff that you didn’t see? Health Hats: No. Steven Labkoff: Cause I, to be honest with you- I- … if I, if I did what you just said and it came up with something completely radical that I’d never thought of and it was right- I would be scratching my head and thinking, “Okay, that’s in- that’s beyond interesting. I better pay more attention to this, and maybe I wanna use it differently.” Because not, it’s not just yous using it. Like, people around everywhere are starting to use it for the same, in the same sim- in the same exact way. So that’s the simplification of the medical system, right? Health Hats: It does. I mean, like when I tell my neurologist, he laughs, and he’s like a whatever works kinda guy, you know? That he feels like he doesn’t have all the answers, and that he likes- those stories. I feel like I’ve learned, I think you know Amy Price, right? Steven Labkoff: Yeah, very well. Health Hats: Yeah. We’re buddies. And so one of the things that I’ve learned from her is how to query and how to be skeptical and how to ask questions from different angles, from different perspectives so that you– And that’s why I think that’s where the unexpected comes up. Steven Labkoff: Well, you’re describing something that we did at the conference. I don’t know if you were in the room in the working group that we did this on, but you’re describing, and actually we’re submitting a paper on it very shortly, on AI literacy. Yeah. And you, you didn’t label it as such, but you’re describing yourself as being AI literate and understanding how to use the tools, most importantly, how to be skeptical of the answers, how to interpret the information that’s being presented to you. Health Hats: A- and that, those are all components of literacy, of AI literacy specifically. One of the things I’m finding in my world is that painfully few people are indeed AI literate. Even the folks in IT departments in large life science companies or hospitals who even work in the space and think that they’re good at it and are literate sometimes are not. That has other implications, which are if people are taking on these really impressively powerful tools and they don’t quite know how to use them as well as they should, and if they query them incorrectly, to your point earlier about making good queries, the responses that come out may or may not be the point. And if patients use that information inappropriately because they didn’t know how to ask the right questions to start with, that could have deep implications to the healthcare system. You could say that same thing about doctors. Steven Labkoff: I will say it about doctors. I mean, not about AI, about the advice that doctors give. Health Hats: There’s a, a tremendous variation, and it is very different. When I am feeling good enough to be organized and to be directive in the conversation with a clinician, I get a very different output than when I’m not. And I still have to be skeptical of what doctors tell me, and until I build some trust. And, and then I, you know, then there’s just too many decisions to make when you’re a person with chronic illness. It’s like putting in a kitchen. There’s so many decisions to make, and I’m happy for the doctors that I trust to make the decisions for me. But there are certain decisions I don’t want to give to the doctor or to AI, like I don’t wanna mess with my pathological optimism. I wanna progress as slowly as possible, and I wanna keep playing my horn. These are really important things to me, and I don’t give those decisions that affect that, I don’t give up. But all the rest of it I do, and, and I’ve worked really hard to build the team that I have that appreciates me and my strangeness and my assertiveness, and, you know, they’re not threatened by it. Steven Labkoff: Is your team AI literate? Do they also use the, these same tools in your care? Health Hats: Uh, like I don’t know. I mean, AI literate is like, is huge. You know? I mean, that’s just such a big thing. Do they use AI? Yes. Do I know how they use AI? Well, you know, they use what’s attached to Epic. I know that. Uh, I mean, look, my neurologist, who I just love, he thinks like he uses, he uses the portal well because he takes– he just keeps adding things to the end of the, a note. Yeah. And so he feels like… Well, I don’t find his notes at all useful, and I tell him that. I tell him, “What I really wanna know is, how am I doing? Am I getting better? Am I getting worse? Am I stable? What should I be paying attention to in the next six months till I see you again?” And I can’t find that in his note. That’s true. Yeah. Now, on the other hand, I’ve taken his note and asked Claude and say, “Here’s the note. How am I doing? You know, have I progressed? H-how is he measuring it?” Oh, well, then I find he’s using this scale, right? And it’ll come up with looking through this note, which is like 10 years running, and it’ll find, I can’t remember the name of it, but there’s a scale that he uses. And then we go back and I’ll say to him, “Oh, you’re using this scale.” And he goes, “Yeah.” And I say, “Well, why don’t you like put that at the top of your note?” You know, so that I can find it. You know, so we have that kind of conversation- Yeah … that AI has helped. Steven Labkoff: Well, that’s actually an interesting perspective that AI is helping to reorganize things, ’cause one of the use cases that has been discussed at, at length actually, and it was discussed at our conference, is using AI to digest medical records. Health Hats: And when I say digest, it’s not about like ingesting them, which is slightly different, but digesting, which means find all the different pieces, put them together, come up with a narrative that summarizes perhaps 300 pages of information which may be sparse and may be poorly organized, and bring it all together. And that’s actually a task that AI is actually turning out to be pretty darn good at. And that again changes the nature of the healthcare system and the healthcare journey. You know- And it does a fair job. You say it’s really good at it. So- It’s better than I could do. It’s better than I could do. Well, yes. Well, you’re not– First of all, that’s not your training, and you don’t have the time for it. And you still have to review it. Yeah, of course. Because I have never used AI that gave me a, “Oh, this is great.” I mean, the first time I read it pretty much every time I think it’s amazing. And then, you know, my rule is sleep on it and check it again. And then it’s like, oh my God, this, first of all, it either just said nothing very fancy or it got some very basic things wrong. And then I’ll say, “Oh, you know, you missed this and you missed that.” And it’ll go, “Oh, you’re right, I did.” You know? Steven Labkoff: Well, that also speaks to the concept of keeping a human in the loop- Yeah which is something that you espouse and many folks in the healthcare aisle- I do … espouse. Ironically, you know Adam Rodman, I think. He was at our conference, he spoke. Yeah. Uh, he’s done a study which shows actually having a human in the loop in some cases actually makes the conclusions worse, believe it or not. Ah. Which is w- a non-intuitive finding. You would think that the two together would be better than either one alone, but so that’s, that’s now relatively n- well, it’s not even that new anymore. That information came out about a year ago. So I, we gotta start wrapping up in a few minutes here. Yeah. You know, we didn’t cover the concept around outcomes around your three T’s and two C’s. Maybe we can cover that in the last bit here, and then we can get to closing. Health Hats: Okay. So I feel like one of the questions that you’ve asked is how AI helped, right? And so what I need to tell you is the framework that I’ve developed over the years, which I’ve actually shared in my AI Claude project that’s Danny’s Health, what I call the three T’s and the two C’s, and this is like the framework I use to evaluate any digital health technology. And so they are time, trust, talk, control, and connection. What I mean by that is time is, you know, you need time to learn, to plan, to talk, to build trust. So I say the clock isn’t the enemy, it’s the, the wrong things filling the time, so the, the time. The second is trust. You know, trust can take a really long time. It can happen really quickly. Sometimes you never have it, and you know in your gut when you don’t have it. And most digital health tools, AI, have a trust deficit, I think, not because they’re untru- untrustworthy, which maybe they are, but it’s really because the people who use them, use the tools, don’t, don’t trust them, and I think it’s really important. You c- you can’t shortcut trust in the use of any tool. I think talk is really important. It’s woven through all of it, real conversation. There is nothing like actual conversation that is making decisions together, which is a lot of what healthcare is about, is making decisions. AI can help you prepare for it, and it can help process it. And then control. I trust more when I have power in a situation. So if I’m feeling like an ant ready to be crushed, I’m not making good decisions. And finally, I would say connection is, it’s the human lifeline. You know, when somebody greets you when you cross a threshold, that’s a connection. When someone’s been where you’re going and they can say, “Oh, that helped me.” AI can extend that connection. They can help people find communities that are available at 3:00 in the morning, but you can’t manufacture it. I, I think that connection is really important, so that’s where I g- you know, time, talk, trust, control, and connection, and I use that framework when I’m evaluating. Steven Labkoff: And that framework gives you a better, you know, a how do I say this right? It gives you a, like a rubric, if you will, to go- Yes … through, uh, the information that’s coming out of it. Danny- Yeah … we’re gonna have to wrap up here in a second. Sure. Are there any last comments you wanna make that, that will, you know, help other patients in the, in the space in terms of how they might wanna think about adopting- an AI tool in their world? Health Hats: I think that I would say use it, use AI, keep using it, experiment with it. That, that i- i- just like anything else, it takes time to learn. It takes time to be comfortable with it. Use it. I would say advocate for humans in the loop. I don’t care what the study says. It’s about humans. We are human. Keep it humans in the loop. I would say find a buddy, you know. Do this with somebody else. Find a buddy- That’s good advice … and experiment. I would say, yeah, talk to your clinician about it. It’s a good barometer of a physician. If they don’t wanna talk or blow you off, that tells you something. Absolutely right. And I would say if you’re comfortable with it, mentor. You know- That’s a good idea … be the buddy. And for clinicians and for systems and developers, I would say you need to have patients, caregivers, and practicing partner clinicians in the design. They need to be there from the beginning. And, you know, so i- it solves the problems people have, not the problems that the developers think are there or the venture capitalists thinks are gonna make money. You know, y- and if you have an opportunity, join, you know, participate. Steven Labkoff: All good advice. Well, Danny, I wanna thank you very much for your participation in, in today’s discussion. Hopefully that there are other patients out there who listen to the podcast, they’ll take something away. For the clinicians out there who are listening, you know, you’ve heard it straight out from a patient who happens to be a healthcare provider himself, and he’s got very strong perspectives on how this can be used in a positive and productive way, and I think the framework that he’s put together is very useful. Danny, I wanna just say thank you for all the help that you’ve provided helping this podcast get off the ground. That’s been really incredibly generous of you and your friends who have helped us a lot, and a lot of the things that have happened on our podcast, uh, for improvement’s sake, have come directly from those conversations, so thank you for that. I wanna thank you for being a guest and sharing your journey and sharing your experiences here. And for the rest of us, I’m gonna say thank you for joining us, and we will see you again next time on another episode of Practical AI in Healthcare. Thank you for listening. Thank you for joining us this week on Practical AI in Healthcare. If you’re ready to go beyond buzzwords and hype and explore how AI is truly transforming healthcare, stay tuned for more conversations that get us to what works. Until next time, stay practical Reflection When Steve interviewed me, he didn't know that everything I told him is the origin story of TrustMyOwn.Health. The box of paper. The 296 pages that were technically my data and practically useless. Twenty-five years of a pattern that sat in my chart the whole time, that it took a person, my PCP, a year to put together. Could AI have done it in an afternoon?  I got tired of that being the normal experience instead of the exception. [Add: what specifically prompted starting TMOH, and when.] TMOH starts from a premise I didn't have language for until I said it out loud to Steve: trust isn't a feature you bolt onto a health platform after the engineering is done. It's the whole structure, or the whole thing fails. The three T's and two C's I use to size up any digital health tool turn out to be close to a design spec. Time, because a vault of your whole health history takes patience to build, not a single import. Trust, built into governance rather than promised in marketing; TMOH's Data Sovereignty Covenant binds the board and investors to the same terms as everyone else, which is the only version of trust I believe in. Talk, because the point was never to replace the conversation with my clinician, it was to walk in more prepared for it. Control, because I decide what goes in the vault and who sees it, the same way I decide which of my own decisions I hand to a doctor or an AI and which ones I keep for myself. Connection, which no vault can manufacture, but a good one can make room for. I told Steve that AI found a pattern in my chart that twenty-five years of clinicians missed. That's not really a story about AI being smart. It's a story about who owned the data long enough to ask the question. That's the whole bet behind TMOH: put the owner at the center, and let the rest of the ecosystem, the networks, the vendors, the AI, earn its place around that. See you around the block. Practical AI in Healthcare Episodes https://open.spotify.com/episode/4wA4ltjmZfIZ5VpmTeTTOF?si=KbEvc2_ERNWakJ3JeP2Ddg https://open.spotify.com/episode/0LDetUFJJrSV1cy6LtpGFx?si=qAqoqKBBSNm9PiwPjSIXYA https://open.spotify.com/episode/0wXEm1KnnGorOvTt9GTh7o?si=K_DKXzGyThusBPA6KoVkCg https://open.spotify.com/episode/6krV94ob6Lcv7VNo0qahZ5?si=B6lZDkvsQ9y2Z2FhkXzQGQ Referenced in episode Patient data access history: “Introducing Blue Button Plus: The Next Generation in PHRs” — HealthIT.gov (Office of the National Coordinator for Health IT) — https://www.healthit.gov/blog/consumer/introducing-blue-button/ The “Gimme My Damn Data” campaign Danny references: “Gimme My Damn Data (and Let Patients Help!): The #GimmeMyDamnData Manifesto” — Dave deBronkart, Journal of Medical Internet Research — https://www.jmir.org/2019/11/e17045/ Amy Price, mentioned as a mentor in questioning and skepticism: “Welcoming Dr. Amy Price as Editor-in-Chief” — Society for Participatory Medicine — https://participatorymedicine.org/2024/welcoming-dr-amy-price-dphil-as-the-editor-in-chief-for-the-journal-of-participatory-medicine/ AI literacy for patients, the concept Steve names in the episode: “Critical AI Health Literacy as Liberation Technology: A New Skill for Patient Empowerment” — National Academy of Medicine — https://nam.edu/perspectives/critical-ai-health-literacy-as-liberation-technology-a-new-skill-for-patient-empowerment/ Human-in-the-loop research Danny and Steve discuss (Adam Rodman): “AI and the Evolution of Medical Thought with Dr. Adam Rodman” — NEJM AI Grand Rounds (podcast) — https://ai-podcast.nejm.org/e/ai-and-the-evolution-of-medical-thought-with-dr-adam-rodman/ Abridge, the ambient AI scribe tool Danny mentions using: “Pioneers in Generative AI for Healthcare” — Abridge — https://www.abridge.com/about The DCI Network conference where Danny met the hosts: “About DCI Network” — DCI Network, Beth Israel Deaconess Medical Center — https://www.dcinetwork.org/about-us Please comment and ask questions: at the comment section at the bottom of the show notes on LinkedIn  via email YouTube channel  DM on Instagram, TikTok to @healthhats Substack Patreon Production Team Kayla Nelson: Web and Social Media Coach, Dissemination, Help Desk  Leon van Leeuwen: editing and site management Oscar van Leeuwen: video editing Julia Higgins: Digital marketing therapy Steve Heatherington: Help Desk and podcast production counseling Joey van Leeuwen, Drummer, Composer, and Arranger, provided the music for the intro, outro, proem, and reflection Claude, Perplexity, Auphonic, Descript, Grammarly, DaVinci Resolve, DaVinci AI Art Generator, OpenArt AI Creator Studio Inspired by and Grateful to: Steve Labkoff, Leon Rosenbilt, Amy Price, Leon and Oscar van Leeuwen, Laura Marcial Artificial Intelligence in Podcast Production Health Hats, the Podcast, utilizes AI tools for production tasks such as editing, transcription, and content suggestions. While AI assists with various aspects, including image creation, most AI suggestions are modified. All creative decisions remain my own, with AI sources referenced as usual. Questions are welcome. Creative Commons Licensing CC BY-NC-SA This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. If you remix, adapt, or build upon the material, you must license the modified material under identical terms. CC BY-NC-SA includes the following elements:    BY: credit must be given to the creator.   NC: Only noncommercial uses of the work are permitted.    SA: Adaptations must be shared under the same terms. Please let me know. dannyhealthhats@gmail.com  Material on this site created by others is theirs, and use follows their guidelines. Disclaimer The views and opinions presented in this podcast and publication are solely my responsibility and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute®  (PCORI®), its Board of Governors, or Methodology Committee. Danny van Leeuwen (Health Hats)

The way your customers search has changed. Not gradually. Dramatically. And most indie pet businesses haven't noticed yet. A year ago, if someone's dog had itchy skin, they'd Google "best dog food for itchy skin" and scroll through 20 links. Now? They're asking ChatGPT, Gemini, Claude, or Perplexity the same question in a conversation: "My seven-year-old Labrador has itchy skin and keeps licking his paws. I think it's food-related. I want a locally owned pet store near me that actually understands nutrition." That's not a keyword search. That's a conversation. And that's AEO (Answer Engine Optimization). Candace explains why this shift actually favors indie pet businesses and exactly what you need to do to win. She discusses: ⭐️ The difference between SEO and AEO (and why it matters more than you think) ⭐️ How customers are using AI tools instead of Google to find answers ⭐️ Why this isn't about panicking or hiring an expensive agency ⭐️ How AI scans your website differently than Google does ⭐️ Brand pages optimized for both humans and AI bots ⭐️ The one thing Candace would do first if she took over your business tomorrow Plus why the next 20 years are about helping people find trusted experts and not just products!  Transcript Show NotesJoin Us Online Find us on Facebook Join our Free Pet Industry Facebook Group Follow us on Instagram Read our Blog

In this episode of The Ross Simmonds Show, Ross shares why curiosity, execution, and continuous learning are becoming more valuable than traditional credentials in marketing, tech, and business. He breaks down how hiring managers, marketers, content creators, and business leaders can identify curious talent, build stronger teams, and stay relevant as AI, search, content distribution, and audience behavior continue to evolve. Key Takeaways and Insights: 1. Curiosity as a Career Advantage - Ross shares how growing up outside major tech hubs pushed him to use the internet as his mentor. - Curiosity helped him build a self-directed education across SEO, social media, content, SaaS, Reddit, LinkedIn, Quora, and startups. - The lesson: your location, background, or lack of connections does not limit your ability to learn and grow. 2. The Hiring Trap: Stacked Resume, Weak Execution - Ross warns leaders not to confuse impressive logos and credentials with real-world capability. - Some candidates know how to follow a playbook but struggle when asked to create or adapt one. - Hiring should focus on how people think, learn, ask questions, and solve problems—not just what appears on paper. 3. How to Identify Curious Marketers - Ask candidates what they are reading, what they are learning, and how they stay sharp in their craft. - Look for people actively tinkering with new tools, especially in the age of AI. - Curious marketers bring questions, data, and insights into conversations instead of relying on old playbooks. 4. Insight-Driven Marketing Decisions - Great marketers do not recommend SEO, CMS changes, or content strategies simply because they prefer them. - They gather data, ask about pipeline goals, conversion rates, customer lifetime value, and channel performance. - Curiosity turns marketing from guesswork into a structured, strategic process. 5. Where Curious People Spend Their Time - Curious professionals go where learning is happening: communities, subreddits, Discord servers, Slack groups, LinkedIn threads, and comment sections. - They engage in discussions, debate ideas, and test what they learn. - They do not just consume marketing tips—they apply them. 6. The Signals of a High-Curiosity Team Member - They research before making recommendations. - They reverse engineer why something worked instead of blindly repeating tactics. - They invest in courses, tools, and resources because they want to become better, not just get promoted. - They challenge leaders with data-backed thinking and fresh perspectives. 7. Why Curiosity Matters in the AI Era - AI is reshaping search, content distribution, GEO, AEO, and how buyers discover brands. - Channels that worked three years ago may not be enough today. - Marketers who stay curious will adapt faster as LLMs, Reddit, YouTube, short-form video, and emerging platforms shift the landscape. 8. Building a Learning Advantage - One to two extra hours of intentional learning per week can put you ahead of people doing none. - Those who invest more deeply in their skills create a larger competitive gap. - Continuous learning builds the taste, strategy, distribution skill, and human understanding needed to stay valuable. 9. Hiring for Curiosity and Growth - Leaders should ask candidates about newsletters, podcasts, tools, personal projects, and ideas they cannot stop thinking about. - Experience with tools like Claude, Perplexity, and ChatGPT can signal active experimentation. - Building a culture of curiosity helps teams stay adaptive, strategic, and ready for what comes next. —

The episode highlights a shift from technology selection to operational risk management in the AI landscape for MSPs. Service providers are being forced to navigate the fast-changing interplay between AI models, the harness software that mediates their deployment, and the financial realities of consumption-based billing. The rapid proliferation of open-source and open-weight AI models, alongside market behaviors from closed vendors and regulatory interventions, is introducing volatility and uncertainty in both cost structures and client offerings. This dynamic creates structural challenges related to margin maintenance, vendor dependency, and responsibility for AI-driven decisions. The discussion cites the release of GLM 5.2, an open-weight model from Z AI, which now rivals expensive closed models on key benchmarks at a fraction of the cost. At the same time, large-scale investments by commercial AI vendors have yet to deliver returns on expectations, with reports indicating businesses that adopted AI are not seeing projected value. Specific attention is given to operational constraints such as compute scarcity, token consumption variability, and export policy restrictions impacting AI availability. The episode notes that these pressures are driving both vendors and MSPs to reconsider the viability of reliance on expensive, closed offerings versus investigating open alternatives. Supportive examples include the proliferation of AI “harnesses” (middleware layers like Perplexity, Claude Code, and Cowork) that sit between service providers and underlying AI models, increasing both choice and complexity. Token billing models are highlighted as a source of unpredictability for MSPs, with vendors like Atera and ConnectWise experimenting with different abstractions to shield or pass through token risk to service providers. The potential for on-premises AI deployments using smaller language models is discussed as a cost-mitigation strategy, though this raises further questions about data privacy, infrastructure burden, and long-term vendor roles. Additionally, uncertainty is flagged around sustainability of leading vendors, with projections that at least one major AI player may exit or be acquired within a year due to financial vulnerability. For MSPs and IT service leaders, these structural and supporting developments translate into increased operational and financial complexity. There is a pressing need to evaluate not just which AI technologies to adopt, but how to architect solutions that can withstand rapid vendor movement, cost swings, and evolving regulatory requirements. Practical safeguards include testing open-source AI models alongside commercial offerings, exercising caution in vendor selection, and closely monitoring evolving consumption billing models. Preparing staff and clients for adaptive, process-oriented approaches—rather than fixed solutions—is positioned as a necessary step to maintain resilience as the AI adoption cycle continues to correct course. Supported by:Pax8CometBackupGuardz

In the latest episode of Executive Function, Brett sits down with Eric Sager, COO of Plaid, following stints as CRO of Bluevine and Head of Sales at Square. During his seven-year tenure at Plaid, Eric has helped lead the business through a pandemic, Visa's collapsed acquisition, a fintech downturn, and the AI boom. In today's conversation, he unpacks how he kept teams focused during turbulent times, why he refuses to run at 100% capacity, and how he re-architected the go-to-market function as Plaid scaled. In today's episode, we discuss: How Plaid stayed focused after the Visa acquisition fell through and then raised at nearly 3x the price Why great COOs deliberately make themselves obsolete Why Eric treats speed, risk, and cost as a three-way trade-off, and why sometimes going slower wins How refusing to run at 100% capacity helped Plaid win OpenAI, Perplexity, and Replit Why Eric personally cold-calls brand-new employees References Bain & Company: https://www.bain.com Bluevine: https://www.bluevine.com Chase: https://www.chase.com Citibank: https://www.citi.com Eyal Lifshitz: https://www.linkedin.com/in/eyallifshitz/ Françoise Brougher: https://x.com/FrancoiseBr Gokul Rajaram: https://www.linkedin.com/in/gokulrajaram1/ Jack Dorsey: https://x.com/jack Michael Mankins: https://www.linkedin.com/in/michaelcmankins OpenAI: https://openai.com Perplexity: https://www.perplexity.ai Plaid: https://plaid.com Replit: https://replit.com Sarah Friar: https://www.linkedin.com/in/sarah-friar/ Square: https://squareup.com Visa: https://www.visa.com William Hockey: https://www.linkedin.com/in/william-hockey-04536710 Zach Perret: https://www.linkedin.com/in/zperret/ Where to find Eric Sager LinkedIn: https://www.linkedin.com/in/eric-sager-a529516 Where to find Brett LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/ Twitter/X: https://twitter.com/brettberson Where to find First Round Capital Website: https://firstround.com/ First Round Review: https://review.firstround.com/ Twitter/X: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast Timestamps 00:00 Introduction 00:40 Leading a company through turbulent times 04:24 How to build a resilient team culture 08:33 How Plaid avoids bureaucracy, while operating at scale 10:58 The speed-quality tradeoff: Going faster isn't always better 15:32 When to move from generalists to specialized customer segments 20:14 Why Plaid has one owner for entire customer relationships 22:06 The "quarterback" model: one owner, experts on call 24:08 Why you should never run your org at 100% capacity 29:47 "Always available, never needed": the support mantra 36:49 Eric's unusual "hit by a bus" test to measure job success 43:57 Why Eric cold calls brand-new employees 52:14 Eric's week: 25% ecosystem, 50% business, 25% team 55:15 How to spot fake mission alignment in interviews 59:04 The one thing a founder has that no hire can replicate

JD Vance is the Vice President of the United States, a Marine Corps veteran, former U.S. Senator from Ohio, and author. His latest book, “Communion: Finding My Way Back to Faith,” is available now.www.harpercollins.com/products/communion-j-d-vancewww.whitehouse.gov/administration/jd-vance Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. 50% off your first box at https://www.thefarmersdog.com/rogan! Sign up at https://foxnation.com to watch RAF 11! Learn more about your ad choices. Visit podcastchoices.com/adchoices

This Episode is Sponsored by StayFi Your ultimate tool for Vacation Rental WiFi marketing allowing you to collect guest emails automatically via custom captive WiFi login splash pages. Drive repeat direct bookings and convert your OTA bookings to book direct for their next visit. Visit https://stayfi.com/vrsuccess/ and use code VRSUCCESS for 50% off 3 months of StayFi service. ________________________________________________________________________________________________________________________________________ Gil Chan came at the short-term rental industry from a direction most operators never consider. After 15 years in Silicon Valley, working with brands like Gap, Sephora, and Home Depot on their post-purchase e-commerce experience, he became an STR host - and immediately spotted a gap that his industry background made obvious. The tools that e-commerce businesses took for granted simply did not exist for vacation rental operators who wanted to build a direct booking website worth having. Crafted Stays is Gil's answer to that gap: a purpose-built direct booking platform that works the way a proper commerce site should, not as feature number 40 in a property management system's marketing materials. But what makes this conversation particularly timely is where Gil has taken the platform over the past year - deep into AI-powered search, website building, and the kind of content strategy that gets operators found in places Google's traditional search results simply can't reach. This episode covers direct booking strategy, how search is changing (and what SEO, AEO, and GEO actually mean for property managers), the Aria AI assistant Gil built into Crafted Stays, and how operators can start thinking about their online presence in a way that serves both guests and the AI systems that are increasingly mediating how people find places to stay. It's a practical, technically grounded conversation - and one that will stay relevant for some time. ‍KEY TAKEAWAYS‍ Direct booking websites built on WordPress and plugins were never designed for the live data demands of vacation rental commerce. Purpose-built platforms handle PMS connections, checkout, and mobile experience in a fundamentally different way.‍ SEO, AEO, and GEO are three different things. Traditional search engine optimization gets you on page one of Google. Answer engine optimization gets you into the snippet at the top of the page. Generative engine optimization gets you cited when someone asks ChatGPT, Perplexity, or Claude for a recommendation. Operators need to think about all three.‍ AI-powered review analysis is an underused tool. Most operators check a five-star review and move on. Mining reviews for recurring themes - a screened porch that guests keep mentioning, a location detail that keeps coming up - surfaces the specific things guests value most, and those become the content anchors for the entire website. The Sightline Report that Aria generates combines property data, review sentiment, and third-party SEO keyword research to produce a strategic playbook for each operator. It tells them which keywords to target, which landing pages to build, and which guest personas to write toward - without requiring any marketing expertise from the operator. Building your AI business brain before you start using AI tools is not optional - it is foundational. Gil has been giving every new team member at Crafted Stays the same 40-page document about the business since he built it a year ago. The quality of AI output is directly tied to the quality of context you give it. The divide in AI adoption is getting wider, not narrower. Some operators are building sophisticated automated systems; others have barely touched ChatGPT. The window to build a real advantage by getting in early is still open, but it will not stay that way indefinitely.‍ ________________________________________________________________________________________________________________________________________

Nick Bostrom is a philosopher whose work focuses on artificial intelligence, existential risk, and the future of humanity. He is Principal Researcher at the Macrostrategy Research Initiative and the author of several books, the most recent of which is “Deep Utopia: Life and Meaning in a Solved World.”www.simonandschuster.com/books/Deep-Utopia/Nick-Bostrom/9781646871643www.nickbostrom.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Switch today at https://Visible.com for just 25/mo. Or Save $10 on your first month of Visible+ Pro with code ROGAN.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

Of course you need data to fuel your AI. You know what's just as helpful though?

Watch the YouTube version of this episode HERETired of the billable hour, overlearning, and feeling like your tech stack still owns you? In this episode, Tyson Mutrux sits down with subscription‑based attorney and Practi co‑founder Mathew Kerbis to break down exactly how AI tools like Perplexity, WhisperFlow, Paxton, Gemini, and agentic workflows are reshaping how modern law firms are built and run. You'll hear how Mathew went from insurance defense litigator to “AI‑native” transactional lawyer, why he believes the billable hour is bad for both clients and lawyers, and how subscription models and recurring revenue can unlock more freedom, better margins, and a saner life.They dig into real‑world examples: using AI dictation and desktop agents to draft and format complex contracts, running redlines across multiple tools, replacing parts of traditional case management, and orchestrating systems so that actual legal work keeps happening while Mathew is teaching a CLE or recording a podcast. Tyson and Mathew also wrestle with big‑picture trends, MSOs and private equity in law, BigLaw's addiction to the billable hour, and how bar regulators and ethics rules might respond to the AI wave. If you're a law firm owner wondering how to actually use AI to save time, make more money, and serve clients better (instead of just “playing” with tools), this one is packed with practical insights.What You'll LearnWhy the billable hour breaks incentives and how subscription/flat fees create better results for lawyers and clientsHow Mathew's AI stack (Perplexity, WhisperFlow, Paxton, Gemini, Google Workspace) powers his daily legal workWhat agentic workflows look like in practice for reviewing, redlining, and improving complex contractsHow WhisperFlow lets him talk instead of type across apps and replace traditional dictationWhy he runs his practice on Google Docs, NotebookLM, and AI search instead of case management softwareHow standardized templates plus AI speed up NDAs, MSAs, and other routine documentsThe core business model behind Practi and how it helps firms launch subscription legal servicesWhy solos and small firms may be better positioned than BigLaw in an AI‑driven legal marketHighlights00:00 – Challenging the status quo and taking aim at the billable hour06:10 – Lawyers as “professional students” and the trap of endless overlearning09:01 – Why many women and lawyers of color leave BigLaw to start their own firms12:10 – Perplexity, WhisperFlow, and Paxton as Mathew's core AI tools15:01 – Using WhisperFlow for OS‑level dictation, prompts, and text expansion27:43 – Orchestrating AI tools to clean up, analyze, and redline contracts at scale31:00 – Running a subscription practice on Google Workspace and NotebookLM45:15 – MSOs, private equity, and why Practi is being built as an alternative path49:08 – How subscriptions and recurring revenue unlock growth beyond hourly billing56:59 – Letting AI run recurring tasks so work continues while you're offlineAccess Agentic Browser Redlines Demo HereConnect with Mathew KebrisLinkedIn https://www.linkedin.com/in/kerbisverse/

Joe is joined by mixed martial artists John Rallo, Matt Serra, and Din Thomas. John Rallo owns Shogun Fights and is the owner and head coach of Ground Control Mixed Martial Arts Academy.www.groundcontrolbaltimore.comwww.shogunfights.com Matt Serra is a mixed martial artist and host of "UFC Unfiltered" with Jim Norton and "Geeking Out with Matt Serra." He is the owner and an instructor at Serra BJJ.www.youtube.com/@MattSerraBJJwww.serrabjjacademy.com Din Thomas is a mixed martial arts analyst, actor, and host of "Din Thomas' Fight Court."www.youtube.com/@FightCourt Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Don't miss out on all the action this week at DraftKings! Download the DraftKings app today! Sign-up using https://dkng.co/rogan or through my promo code ROGAN. Get watch party snacks and groceries on Uber Eats. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Rupert Lowe is a British politician who has served as the member of Parliament for Great Yarmouth since 2024 and the leader of Restore Britain. Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. onX Offroad: Try onX Offroad for 50% off- go to https://onXmaps.com/joerogan This video is sponsored by BetterHelp. Visit https://BetterHelp.com/JRE Learn more about your ad choices. Visit podcastchoices.com/adchoices

Ali Siddiq is a comedian, author, and public speaker. His new special, "My Father," is now streaming on YouTube. See him live on the "Custom Fit" Tour.https://youtu.be/XiSewRUOVygwww.youtube.com/@AliSiddiqComedywww.alisiddiq.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Don't miss out on all the action this week at DraftKings! Download the DraftKings app today! Sign-up using https://dkng.co/rogan or through my promo code ROGAN. Get 30% off + 2 free gifts at https://ARMRA.com/rogan Learn more about your ad choices. Visit podcastchoices.com/adchoices

Tony Hinchcliffe is a comedian, writer, actor, and host of the podcast and live show “Kill Tony.” His new special, "Man of the People," is now streaming on Netflix.www.youtube.com/@killtonyhttps://tonyhinchcliffe.komi.iowww.tonyhinchcliffe.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Try ZipRecruiter FOR FREE at https://ziprecruiter.com/rogan Learn more about your ad choices. Visit podcastchoices.com/adchoices

Aravind Srinivas, PhD, is the co-founder and CEO of Perplexity AI, creator of the AI-powered search and answer engine Perplexity.www.perplexity.ai Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. This video is sponsored by BetterHelp. Visit https://BetterHelp.com/JRE Learn more about your ad choices. Visit podcastchoices.com/adchoices

Tommy Lee is a genre-spanning solo musician, producer, and songwriter as well as the drummer and co-founder of Mötley Crüe. His latest album is “Tommyland Rides Again.” See him live with Mötley Crüe on The Return of the Carnival of Sins Tour beginning July 17.www.youtube.com/tommyleewww.motley.comwww.tommylee.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Don't miss out on all the action this week at DraftKings! Download the DraftKings app today! Sign-up using https://dkng.co/rogan or through my promo code ROGAN. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Scott Eastwood is an actor and producer known for his roles in films including “Fury,” “The Fate of the Furious,” and “Outpost.” His new film, “Lucky Strike,” will be released June 26.https://youtu.be/vtEnjikCXyAwww.fandango.com/lucky-strike-2026-246022/movie-overviewwww.roadsideattractions.com/filmography/luckystrike Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Use code ROGAN at https://BlueChew.com to get 10% OFF + Free Overnight Shipping on your first order. Try ZipRecruiter FOR FREE at https://ziprecruiter.com/rogan Learn more about your ad choices. Visit podcastchoices.com/adchoices