Podcasts about Loom

Listen to the Top News of 15/06/26 in Hindi.

AP correspondent Julie Walker reports on President Trump's 80th birthday present, UFC fights at the White House.

Buyer's agents are coming under increasing scrutiny over financial advice in the wake of the Dashdot collapse. But it's not all bad news for investors, with backlash building against the government's tax reforms and rate cuts looming on the horizon. After a challenging few weeks for the real estate industry, this episode of Property Buzz, hosted by Phil Tarrant and Liam Garman, explores whether relief could be emerging as yields return to focus and Australia's major banks flag potential rate cuts. The pair discuss how quarantining losses can provide longer-term tax relief for investors, alongside the shifting political landscape shaping property sentiment. They also turn to the property advice ecosystem, including growing scrutiny around unlicensed financial advice and the standards expected of buyer's agents operating in an increasingly complex environment. The discussion continues around the fallout from the Dashdot collapse, and what it signals for the ongoing professionalisation of the buyer's agent industry.

What does it actually take to build a go-to-market strategy for a category that barely existed 18 months ago?In this episode of The Growth Leaders Series, Charlie Marchant sits down with Nick Lafferty, Founding Marketing Engineer at Profound, the AI Search tracking platform helping major brands understand how they show up in ChatGPT, Gemini, Perplexity, and other LLMs.Nick brings serious growth experience to this role. Before Profound, he drove millions in B2B SaaS pipeline at Loom and Mailgun, then spent two years running a solo consulting agency before joining Profound. In this episode, Nick Lafferty covers:Why velocity is a moat in AI SearchWhat a modern, lean marketing team actually looks like, why Nick hires for a generative marketer mindset, and his advice for showcasing this online The growth strategy behind Profound, centred on sharing data and insightsThe go-to-market motion behind Profound's Zero Click events, scaling from 400 to 800+ attendees across New York and LondonThe layered mentality around AI Search for different business sizesWhy FAQ content and FAQ schema is the lowest-hanging fruit most big brands are leaving on the tableHow to make the internal case for AI Search investment when leadership is still thinking in Google termsThe career advice he'd send back to his first dayRead the full show notes: https://exposureninja.com/podcast/growth-leader-series-nick-lafferty/Follow Nick Lafferty on LinkedIn: https://www.linkedin.com/in/nicklafferty/New episode launches every Wednesday throughout June 2026, so stay tuned to hear from growth leaders from leading brands like McKinsey and Company, Wise, and AirOps! Book a consultation to get a live review of your website and marketing

In this episode of Domina Tempora, we spread our wings into the shadowed realm of the owl — a creature of night, mystery, and duality that has haunted and inspired humanity for millennia.Regarded as the “monster of the night” and harbinger of death by Pliny and many ancient cultures, the owl was linked to desolation, ill omens, and the underworld. From the ukuku of Sumerian curses and Phoenician funeral rites to its transformation into the demonic Lilith, and its ominous appearances before the falls of emperors and armies, the owl has long been a messenger of doom and darkness.Yet this nocturnal predator also embodied profound wisdom and fortune. As the sacred companion of Athena, the owl graced Athenian coins as a symbol of strategic brilliance and victory in battle. In Hindu tradition, it served as the vahana of Lakshmi, goddess of wealth and prosperity, representing the light of wisdom piercing through ignorance. Across cultures, its cry could foretell both disaster and triumph, its gaze both a warning and a blessing.We explore this ancient tension — the owl as bird of death and symbol of enlightenment, associate of witches and goddess of strategy, creature of fear and bringer of prosperity.If the seductive interplay of darkness and wisdom, divine power, and dangerous omens resonates with you, my debut novel Clotho Unbound is calling. In its pages, Clotho — the Fate who has spun death for Zeus across the ages — becomes entangled with Aphrodite in stolen, blasphemous nights of passion that make the Loom of Fate itself tremble. Their love is treason. Their desire could unravel destiny.Clotho Unbound is out now — order your copy today on Amazon (Kindle, paperback, and audiobook).Direct link:https://www.amazon.com/Clotho-Unbound-Marianne-Fisher/dp/B0GTZ8PZFVThank you for listening.Until next time — may your omens be wise and your nights watchful.

Rome Resources Plc (AIM:RMR) CEO Paul Barrett tells Proactive's Stephen Gunnion that the company is kicking off its first field programme as operator at its New Brunswick tin-tungsten-indium project in Canada this week, adding critical mineral exposure while keeping its primary focus on high-grade tin and copper assets in the DRC. More than 500 samples are planned across three target areas, with trenching and surface work designed to build confidence toward a drilling campaign next year. Barrett is clear about the priorities: "It's a multi-commodity. But tin is the main focus." Back in the DRC, Bisie North assay results are pending, a pilot mining project is being prepared, and a geophysical survey is nearing completion, keeping the newsflow busy on both fronts. Watch the full interview to hear more about Rome Resources' exploration strategy, the significance of tin and critical minerals markets, and the company's plans for both Canada and the DRC. Visit Proactive's YouTube channel for more interviews and market insights. Don't forget to like this video, subscribe to the channel and enable notifications so you never miss future content. #RomeResources #PaulBarrett #TinMining #TinExploration #CriticalMinerals #Tungsten #Indium #NewBrunswick #CanadaMining #MiningStocks #ResourceInvesting #JuniorMining #TSX #LSE #Exploration #BisieNorth #DRCMining #CommodityMarkets #NaturalResources #ProactiveInvestors

The sound of warping and weaving on a traditional Canarian loom, alongside the voice of Herminia Pimentel Tejera and the weaving of Jennyfer Cabrera Guerra. A living testimony of the linen cultivation and textile traditions of Gran Canaria, preserved by the Asociación Amigos del Linolillo. Part of the participatory sound mapping project "Voices and Sounds of the Sacred Mountains", by the Union of Associations of the Biosphere Reserve of Gran Canaria.Recorded in Barranco Hondo (Juncalillo), Spain by Jenny Guerra Hernandez.

On the latest episode of Rugby Direct, Elliott Smith and Liam Napier react to a major coaching coup for New Zealand Rugby, with Tony Brown signing on as an All Blacks assistant coach from 2028. The boys also turn their attention to the Super Rugby Pacific semi-finals - can anyone stop the Cane train as the business end of the season heats up? LISTEN ABOVESee omnystudio.com/listener for privacy information.

这期节目聊的是 Tiago Forte 的《打造第二大脑》，一本关于个人知识管理的实用指南。Bear 结合自己作为产品设计师的成长经历，分享了读完这本书之后的真实感受和行动计划。---###

Award-winning war correspondent Zarina Zabrisky, who was officially honored with the Order of Merit, III class, by President Volodymyr Zelenskyy on June 6, 2026, brings a chilling live report from Kherson to this critical episode of Ukrainapodden. Joining the conversation alongside host Tormod Malvin Sæther, author John Færseth, veteran correspondent Øystein Bogen, and Dr. Liliia Honcharevych, Zabrisky exposes the brutal reality of Russia's «Human Safari». This horrifying tactic employs AI-powered FPV drones to systematically hunt down ordinary civilians, public transport, and emergency first responders. She uncovers a catastrophic drone siege on the occupied left bank of the Dnipro River, where thousands of hostages endure a severe hunger crisis, freezing conditions, and a total breakdown of basic human infrastructure. The studio panel breaks down the geopolitical reality behind these atrocities, proving that the Kremlin's reliance on psychological terror and hybrid warfare stems directly from an undeniable military failure. The guests emphasize that Nordic solidarity must transition into immediate, un-bypassable economic sanctions and accelerated military aid. To defend Europe’s broader security architecture, the West must implement a no-fly zone to halt these relentless drone waves. Highlighting the literal life-and-death stakes of frontline reporting, the episode takes a shocking turn when a close-range Russian explosion forces Zabrisky to abruptly cut her feed and run for cover. This harrowing broadcast serves as a definitive warning against coordinated Russian propaganda and ongoing war crimes. You can find Carpathian Sea Democracy Week's facebook page here: https://www.facebook.com/profile.php?id=61557071418003 See omnystudio.com/listener for privacy information.

Among four-shaft weavers, A Handweaver's Pattern Book is commonly referred to by just the author's name—Davison—or as “the green book,” a reference to the iconic cover of many of the book's printings. Since Marguerite Porter Davison first published it in 1944, it has been a foundational reference, the first book that many weavers buy and the one they keep close at hand. Packed with drafts and photographs for overshot, twill, crackle, and dozens of other structures, it's the weaver's answer to The Joy of Cooking: a starting point for design, a resource for understanding a structure, and a map for exploration. Although it remained in print for decades, it became unavailable in 2005, and the weaving community felt the loss. For the past several years, a group of nearly 100 weavers and other volunteers has been working to bring it back. Weavers from guilds from coast to coast have nearly finished reweaving all of the book's samples—more than 1,200 of them—in color. Technical reviewers have created contemporary drafts. The original instructions for sinking-shed looms have been adapted to the jack looms more common in most weavers' studios. Despite the updates, the project's north star has been to honor Davison's voice and intentions. The updated edition, to be published by Schiffer Craft, is expected in summer 2027. Leading the effort is Caroline Cooley Browne, who happens to be Marguerite Porter Davison's granddaughter. Davison died when Caroline was a baby, but she grew up hearing stories from her mother of warping looms in Marguerite's attic studio, of train rides to the printer, of the woman who traveled to numerous guilds because she loved being with other weavers. When the copyright to the 1951 edition eventually came to Caroline through her family, she knew what to do with it, and she enlisted a team of eager volunteers to help bring the new edition to life. In this episode, Caroline is joined by Donna Johnson of the Whidbey Weavers Guild, who coordinates volunteers for the guild's sample weaving, and Anita Osterhaug, who connected the project with the publisher and has been part of the technical steering committee. Together they talk about the logistical undertaking of standardizing hundreds of samples across dozens of weavers, the technical decisions involved in updating the book, and what it has felt like to be part of the next chapter of something this important. Listen in to hear why the green book has never gone out of fashion, what surprised the weavers as they worked through structures they'd never tried before, and what Marguerite Porter Davison's granddaughter hopes she would think of the whole endeavor. Links Visit the page dedicated to The Big Weave on the Bainbridge Artisan Resource Project (BARN) website and sign up for updates. When the project is finished, the WIFs will be available through BARN. This episode is brought to you by: Treenway Silks is where weavers, spinners, knitters and stitchers find the silk they love. Select from the largest variety of silk spinning fibers, silk yarn, and silk threads & ribbons at TreenwaySilks.com. You'll discover a rainbow of colors, thoughtfully hand-dyed in Colorado. Love natural? Treenway's array of wild silks provide choices beyond white. If you love silk, you'll love Treenway Silks, where superior quality and customer service are guaranteed. “Hi, I'm Gabi van Tassell from Bluebonnet Crafters, and I'm the inventor of TURTLE pin looms. Pin looms are small, handheld looms that quickly weave self-contained fabric pieces like squares, hexagons, and more. Weave them with almost any yarn you have on hand, then combine them into projects of any size. They make a wonderful companion for any fiber lover, at home or on the go. I'd love for you to visit us at turtleloom.com to explore the full loom catalog, patterns, and more. Hope to see you there.”

The Finals Loom, some Racin, Tennis & Baseball!The ONLY! Tyler Peacock! Is back for yet another episode of the PodCock PeaCast! On this episode of we'll talk a little NBA & NHL Conference Finals that are still ongoing. Next we discuss some NASCAR, R.I. P. Kyle Busch, Coke 600 & Indy 500 reactions, also a preview of what to come in Nashville, next a brief touch on the French Open. Lastly we update our MLB Tiers. Thanks for listening!RATE REVIEW SUBSCRIBE! Follow the show on X @podcockpeacast & like the Facebook page @ PodCock PeaCast, Available on Apple Podcast, Spotify, Amazon Music, Google Podcast & the rest of the major podcast platforms! Finally enjoy your listen!A semiprofessional sports podcast that may or may not have a gambling problem, we will touch some entertainment subjects as well & elements of general tomfoolery, also it may have a witty moment or two along the way.

 Johan Bruyneel and Spencer Martin break down Paul Magnier's incredible victory on Stage 18 of the Giro d'Italia, which gave him three stage wins at this race and likely sealed the battle for the Points Jersey. They discuss the unexpected outcome, how it came to be, even with a tough climb before the finish, and preview tomorrow's Stage 19, the hardest stage of this race, and how it will shape the overall classification. See THEMOVE live in Belgium for the final Giro stage on May 31st https://www.myticketshop.be/event-details/wattage-festival-2026/777 Become a WEDŪ Member Today to Unlock VIP Access & Benefits: https://access.wedu.team  

Would you like access to our advanced agency training for FREE? https://www.agencymastery360.com/training Are you still optimizing your agency's content for Google while your clients are getting their answers from AI? Are you charging for the execution that AI is about to make obsolete, while giving away the strategy that commands real fees? Today's featured guest works with agencies navigating the shift from traditional search to generative engine optimization. He'll talk about what the Anthropic research actually says about how much of the work agencies do today can be automated, how AI reads content differently than Google does, and the practical steps any agency can take right now to show up in AI-generated answers before competitors figure it out. Tom Lee is an AI search and SEO specialist and co-founder of Visto, a platform that helps agencies build the visibility and optimization layer for the AI search era. Tom and his team advise agencies on generative engine optimization, or GEO, and how to position their clients to show up in AI-generated answers across platforms like ChatGPT, Claude, Perplexity, and Google's AI Overviews. His background includes working inside large enterprise companies including Apple and Walmart, where he managed SEO at scale. He now works directly with SEO and GEO agencies helping them build the strategic frameworks and content systems that translate traditional search authority into AI visibility. In this episode, we'll discuss: Is your value proposition still execution? Why GEO does not replace SEO Repackaging existing content will get you nowhere Subscribe Apple | Spotify | iHeart Radio Sponsors and Resources E2M Solutions: Today's episode of the Smart Agency Masterclass is sponsored by E2M Solutions, a web design and development agency that has provided white-label services for the past 10 years to agencies all over the world. Check out e2msolutions.com/smartagency and get 10% off for the first three months of service. What the Anthropic Research Actually Says Tom referenced an Anthropic study published earlier this year that mapped out the theoretical automation potential across industries. For software development, AI can already handle around 35% of code generation, with a theoretical ceiling of 97%. For business and marketing functions including SEO, that ceiling is 94%. In his view, those numbers are not a reason to panic, but they are a reason to get clear on which part of the work you are actually selling. The agencies at risk are the ones whose value proposition is execution. Writing the content, building the links, pulling the reports: if that is what you are charging for, you are in the category that AI is actively compressing. The agencies that will hold their ground and grow their fees are the ones charging for judgment. Which topics to chase. Which content gaps matter. How to translate client expertise into something AI will actually cite. That is the 6% that automation cannot touch, and it is also the highest-margin work in the engagement. GEO Is Built on Top of SEO, Not Instead of It Something that gets lost in the noise around AI search is that GEO does not replace SEO. It extends it. Showing up in Google search results is still the foundation. What has changed is that showing up is no longer enough. AI reads content the way a human being reads it, evaluating whether the argument is convincing and whether the source is credible, not just whether the right keywords appear in the right density. That changes what good content has to do. The practical starting point Tom recommends is mapping what he calls the semantic space for a client: Identifying what topic areas people are actually raising in AI conversations that the client should be part of. From there, you translate that semantic space into specific prompts, run those prompts across the major AI platforms, and audit what comes back. Who is being cited? Where is the client showing up and where are they absent? What content is AI pulling from competitors that the client has not produced yet? That gap analysis is the strategic deliverable that commands real fees. It is also the work that no AI tool will do for you, because it requires knowing what the client actually wants to be known for. Why Repackaging Existing Content Gets You Nowhere Once you're clear about the topics your audience is looking for, there's something that will for sure not work the way many think it does. When you identify a content gap and ask AI to fill it, you get repackaged information drawn from the same sources the AI already used to generate the gap. That content does not move anything forward. AI knows where it got the data from. Recycled information does not earn citations. What earns citations is new data, original perspective, and subject matter expertise that advances the conversation rather than summarizing what already exists. The 5 step system Tom uses with his clients: Identify the content gaps Build a specific set of questions tied to those gaps Send those questions to a subject matter expert at the client Have them record a Loom or voice memo answering freely Use AI to transcribe and chunk that recording into content The raw material is original. The expertise is real. The content that comes out earns its place in the semantic space rather than competing with what is already there. Your Clients Are Training AI. Are You Helping Them Do It Right? The broader point running through this conversation is one that matters whether you run an SEO agency or not. AI systems are being trained on open-source content: social media posts, forum conversations, podcast transcripts, FAQ pages, markdown-formatted content. Every piece of content a client publishes is either building their presence in that training data or failing to. Agencies that understand this and can show clients where they are absent, who is filling that space instead, and what it would take to reclaim it, are in a fundamentally different conversation than agencies still talking about keyword rankings. The founders who will build authority in this environment are the ones creating real content from real expertise, showing up broadly enough to be present in the long tail of AI conversations, and charging for the strategic thinking that makes all of it coherent. The execution is becoming a commodity. The strategy never was. Do You Want to Transform Your Agency from a Liability to an Asset? Looking to dig deeper into your agency's potential? Check out our Agency Blueprint. Designed for agency owners like you, our Agency Blueprint helps you uncover growth opportunities, tackle obstacles, and craft a customized blueprint for your agency's success.

Greetings Listeners! The only thing I love more than chatting with a really talented filmmaker is chatting with a REALLY NICE and lovely person that also happens to be a very talented filmmaker.                                                                  Jesse Cook III is absolutely both and I was thrilled to have him on to chat about his SOFF 2025 Official Selection LOOM that took home the Filmmakers Award – Outstanding Film – Short Film – SciFi Follow Jesse on Instagram @jc3.mov P.S.- I also couldn’t NOT take a photo of these adorable pups that may have been trying to steal the spotlight during the interview. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Discover Indie Film Links DIF Podcast Website – DIF Instagram – DIF BlueSky Discover Indie Film Foundation (nonprofit for the arts) Website Sherman Oaks Film Festival Film Invasion Los Angeles

After stocks hit record highs Tuesday, Fed speakers and tech earnings are in focus today, while key inflation and GDP data are on the menu later this week. Important Disclosures This material is intended for general informational and educational purposes only. This should not be considered an individualized recommendation or personalized investment advice. The {securities, investment products and investment strategies mentioned are not suitable for everyone. Each investor needs to review an investment strategy for his or her own particular situation before making any investment decisions. For illustrative purpose(s) only. Investing involves risk, including loss of principal, and for some products and strategies, loss of more than your initial investment. Supporting documentation for any claims or statistical information is available upon request. Past performance is no guarantee of future results. Diversification and rebalancing strategies do not ensure a profit and do not protect against losses in declining markets. Indexes are unmanaged, do not incur management fees, costs, and expenses and cannot be invested in directly. For more information on indexes, please seeschwab.com/indexdefinitions. The policy analysis provided by the Charles Schwab & Co., Inc., does not constitute and should not be interpreted as an endorsement of any political party. Digital currencies [such as bitcoin] are highly volatile and not backed by any central bank or government. Digital currencies lack many of the regulations and consumer protections that legal-tender currencies and regulated securities have. Due to the high level of risk, investors should view digital currencies as a purely speculative instrument. Cryptocurrency-related products carry a substantial level of risk and are not suitable for all investors. Investments in cryptocurrencies are relatively new, highly speculative, and may be subject to extreme price volatility, illiquidity, and increased risk of loss, including your entire investment in the fund. Spot markets on which cryptocurrencies trade are relatively new and largely unregulated, and therefore, may be more exposed to fraud and security breaches than established, regulated exchanges for other financial assets or instruments. Some cryptocurrency-related products use futures contracts to attempt to duplicate the performance of an investment in cryptocurrency, which may result in unpredictable pricing, higher transaction costs, and performance that fails to track the price of the reference cryptocurrency as intended. Please read more about risks of trading cryptocurrency futures here. Fixed income securities are subject to increased loss of principal during periods of rising interest rates. Fixed income investments are subject to various other risks including changes in credit quality, market valuations, liquidity, prepayments, early redemption, corporate events, tax ramifications, and other factors. All expressions of opinion are subject to change without notice in reaction to shifting market, economic or political conditions. Data contained herein from third party providers is obtained from what are considered reliable sources. However, its accuracy, completeness or reliability cannot be guaranteed. Schwab does not recommend the use of technical analysis as a sole means of investment research. The Schwab Center for Financial Research is a division of Charles Schwab & Co., Inc.Apple Podcasts and the Apple logo are trademarks of Apple Inc., registered in the U.S. and other countries. Google Podcasts and the Google Podcasts logo are trademarks of Google LLC. Spotify and the Spotify logo are registered trademarks of Spotify AB. (0130-0426) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Several years ago, Shalene Roberts sat with her two young children under the age of three, wrestling with thoughts about motherhood and wondering why it was so desperately hard. Pulling out her phone, she poured out her thoughts in a blog post entitled “When Mothering Is Hard and No One Sees.” Unexpectedly, those honest musings went viral, and that heartfelt post has had more than 630,000 views.Now a mother of five, Shalene understands that women everywhere struggle with the all-consuming service of motherhood—feeling unseen and underappreciated. Even those whose motherhood ride has been fairly smooth may wonder if what they're doing is making any difference. The words in Shalene's post gave voice to these questions. And it was out of that post that this book was born.You may be a younger mom or an older mom, a mom of toddlers or teens. The children you care for may be biological, adoptive, foster, or grandchildren. In When Mothering Is Hard and No One Sees, you will feel seen for your own motherhood struggles and challenges. This book helps you gain a new sense of how God views you as you move toward the hope He has revealed to Shalene: a bigger picture of being a mom with an impact that ripples throughout eternity. In creation and in redemption, you were made—and remade—to mother.In these pages, you will discover…God's original design for motherhoodYour position as a daughter of the King, elevating your motherhood roleThe assurance of abundant forgiveness for mistakes and failuresHow God has uniquely equipped you for this sacred role—with your specific childrenHow to find true rest amid the never-ending demandsWhen mothering is hard…God sees. And He will take you from the gritty to the glorious in your journey as a mom. When Mothering is Hard and No One Sees Bruce T Davis Shalene Roberts Shalene C. Roberts is a wife, part-time homeschooling mom of five, writer, photographer, and small business owner. As a former magazine editor, she seeks to inspire women to anchor in Christ, nurture grace-filled families, and foster life-giving homes. Her work has appeared in an array of outlets, including Her View From Home, Motherly, the Thrive Moms Exhale Bible study, the MOPS Blog, MICI Magazine, KirkCameron.com, SHINE magazine, TODAY Parents, Stroll Magazine, and a variety of other publications. Her post “When Mothering Is Hard and No One Sees” has had more than 630,000 views and has been shared worldwide. Shalene has also taught at the Declare Conference and is the author of Bruce the Brave, a heartwarming children's book about courage and faith. Additionally, she is the founder of Lily & Loom, a boutique vintage Turkish rug shop. Lily & Loom rugs have been seen on HGTV, the Magnolia Network, and Fixer Upper: Welcome Home.WebsiteLinkedInWhitaker House

Send us a question/idea/opinion direct via text message!In this special reaction episode, Nick Goodall and Kelvin Davidson unpack the latest RBNZ OCR decision. The rate was held, but only just. The vote was split 3–3, with the Governor casting the deciding vote. This highlights how finely balanced the outlook is.The key message is that rate rises are likely coming. The OCR track has been revised higher. An increase as soon as July now looks probable. Some committee members wanted to hike now. Their view was to act early to limit future inflation risks.Inflation forecasts have been lifted. Headline inflation is expected to rise above 4% in the near term. This is driven by fuel and import costs. Core inflation is easing, however, and longer-term expectations remain stable. This creates uncertainty around how aggressive the RBNZ needs to be.Growth has been downgraded. The recovery is expected to be slower. Unemployment is set to stay elevated for the next 12–18 months.The housing market outlook is weak. House prices are expected to be flat or slightly down. Sales volumes also look subdued. Mortgage rates may rise further, although much has already been priced in.Overall, the OCR is on hold for now. But the balance has shifted. Future increases look increasingly likely.Sign up for news and insights or contact on LinkedIn, X @NickGoodall_CL or @KDavidson_CL and email ngoodall@cotality.com or kdavidson@cotality.comThis podcast is for educational and entertainment purposes only and does not constitute financial, legal, or tax advice. The hosts are not licensed Financial Advice Providers in New Zealand. All information is of a general nature and does not take into account your personal situation or goals. Please consult a qualified professional before making any financial decisions.

The AI slop problem is getting worse. AI can crank out code, decks, and landing pages in minutes, but somehow everything starts to look exactly the same. That sameness is not just an aesthetic problem; it is a trust problem. I sit down with David Okuniev (Founder of Typeform and Supercut) to unpack what “taste” really means when anyone can one-shot a product, and why people still crave signals of real craft.We also dive into the hidden cost of easy creation: from small-team dynamics to a "65 PR backlog," we discuss how AI shifts the bottleneck from writing code to building a harness for shipping safely.Beyond the philosophy, we get practical about the future of async work. Supercut's bet is that the winning Loom alternative is not just about recording your screen, it's about searchable transcripts, AI Q&A, and agentic workflows that turn a video into a document your team can act on immediately.If you care about product design, reliability, and building honest software in the AI bubble, this conversation will sharpen your thinking.Support the show

In this episode of the Ecomm Breakthrough Podcast, host Josh Hadley shares his "10x AI SOP Method" for scaling businesses by using AI to clone founder judgment. Rather than automating routine tasks, Josh explains how recording real-time work, feeding transcripts into AI models, and rigorously answering hundreds of probing questions creates highly accurate SOPs that capture nuanced decision-making. Through repeated iterations, entrepreneurs can build comprehensive procedures enabling teams to execute with founder-level expertise, eliminating bottlenecks and unlocking sustainable business growth.Bullet Points:Use of AI to replicate founder's judgment and decision-making in business processes.Importance of documenting nuanced decision-making beyond traditional SOPs.Step-by-step method for creating an AI-assisted SOP.Recording real-time work processes to capture decision-making rationale.Feeding transcripts of recorded processes into an AI language model.Iterative refinement of SOP through detailed questioning and feedback.Achieving high accuracy in SOPs by rigorously interrogating the founder.Utilizing training videos effectively for onboarding new team members.Maintaining context and continuity in AI interactions for better SOP development.Emphasizing the transformative potential of AI in scaling business operations.Timestamps:00:00:00 Introduction: How to Clone Yourself with AIThe host introduces the concept of using AI to replicate a founder's judgment and decision-making to scale a business.00:01:48 The Founder Mindset ShiftOvercoming the belief that "nobody can do this like me" by documenting the nuanced judgment calls behind your business processes.00:02:41 The Problem with Normal SOPsStandard Operating Procedures often fail because they miss the crucial, unarticulated judgment calls and trade-offs made by the founder.00:03:38 The Lazy Way People Use AIA warning against simply asking AI to create an SOP, as it lacks the specific context and nuances of your business.00:04:33 The 10x AI SOP Method OverviewAn introduction to the host's four-step method: record your process, feed transcripts to AI, have AI interrogate you, build SOP.00:05:33 Step 1: Record the ProcessThe importance of recording yourself performing a task multiple times over several weeks to capture various scenarios and nuances.00:07:26 Why Multiple Recordings Are CrucialRecording a process over time captures seasonality and different business scenarios, creating a more robust and accurate SOP.00:08:21 How to Record Effective LoomsThe key is to vocalize every decision, explain trade-offs in real-time, and record during different business scenarios.00:09:18 Live Demo IntroductionThe host begins a practical demonstration of his AI process for creating an SOP for his product research and development.00:10:21 Step 1 of the Prompting ProcessExplaining the initial prompt that sets up the AI as an expert SOP architect and instructs it on the process.00:12:09 Steps 2-4: Feeding Transcripts to the AIHow to upload weekly transcripts and use an "SOP memory" to have the AI continuously update its understanding of the process.00:13:16 Step 5: The First InterrogationPrompting the AI to ask numerous questions to ensure the SOP captures your full judgment with 95% accuracy.00:15:06 Step 7: The Second InterrogationPushing the AI further by asking it to ask more questions to achieve 99.9% accuracy in the final SOP.00:15:33 Step 10: Creating a Training PlanUsing the AI to analyze all recorded videos and create a structured onboarding and training plan for new team members.00:17:24 Live Demo WalkthroughA screen-share demonstration showing the actual ChatGPT thread, from the initial prompt to the AI's 240 interrogation questions.00:21:17 Why This In-Depth Process MattersEmphasizing that thorough systems are what truly scale a business, preventing the frustration of team members not executing correctly.00:22:29 The AI-Generated Onboarding PlanThe AI's final output, which suggests the best order to present training videos to a new hire for maximum clarity.00:23:31 The Importance of the Loom Training LayerLeveraging the recorded videos as training assets, using AI to determine the most effective sequence for onboarding new hires.00:24:32 Key TakeawaysAn SOP is complete when someone can make the same decisions as you, which is achieved by using AI interrogation.Links and Mentions:Tools and Websites  "Helium 10": "00:02:36"  "Cerebro": "00:02:36"  "Data Dive": "00:02:36"  "Loom": "00:05:29"  Videos and Demos  "YouTube Demo": "00:10:14"  Prompts and Processes  "AI Prompt Library": "00:25:09"  Key Takeaways  "SOP (Standard Operating Procedure)": "00:24:00"Transcript:Josh Hadley 00:00:00  If you're a business owner, you've probably thought, hey, is there an ability for me to clone myself? Because if I just had 3 or 4 more people on my team that thought the same way I do that, execute the same way I do, and actually have the same work ethic that I do. Man, our business could be ten x bigger than it is today. Well, today I'm going to show you how to utilize AI to clone yourself in the exact process that I'm following to clone myself in my business. Welcome to the Econ Breakthrough Podcast, I'm Josh Hadley. I've scaled my own ecommerce brand from 0 to 8 figures, and I'm actively building towards nine figures in sales. This podcast is where I document that journey and share the systems, the strategies, and the lessons learned in real time so that you can learn what actually matters and scale your own business. Who am I? My name is Josh Hadley. First and foremost, I am a man of faith. I'm a husband to a beautiful wife and the father of four children.Josh Hadley 00:00:49  I have been selling in the e-commerce space for over a decade now, doing over $20 million in annual revenue and selling multi-millionaire on multiple sales channels including Amazon, TikTok, Shop and Shopify. And I am also the host of the E-com Breakthrough podcast, the number one business strategy podcast for eCommerce entrepreneurs. Today, I'm going to be showing you how I use AI to clone myself in my business. And this doesn't just mean I'm using AI agents to go clone myself. What I'm actually doing is following a system that allows me to replicate my same level of judgment and decision making throughout the team, whether it's a team member executing tasks for me, or it's AI executing tasks for me, the most important thing that you need to do truly is to clone the way you think and the judgment calls that you make that is ultimately what you're looking for. Most people use AI to just...

The “St. Louis Morning Brief” opens with the viral “tarps off” trend at Busch Stadium, where fans in a designated upper-deck section are encouraged to go shirtless after the stunt originated with a visiting Texas team and quickly became a stadium-wide marketing moment embraced by the Cardinals organization. The discussion then shifts to the rollout of autonomous vehicles, focusing on Waymo testing in St. Louis since December, which is now facing uncertainty after Missouri legislation aimed at standardizing regulations and liability rules failed to pass, creating new barriers to full deployment. A parallel anecdote from another city highlights how self-driving vehicles have created unexpected gridlock issues in residential neighborhoods, fueling skepticism about driverless safety and usability. The segment then turns sharply to city finances, as St. Louis officials weigh how to allocate remaining Los Angeles Rams settlement funds while preparing residents for a proposed 18% water rate increase, with further hikes projected in coming years. The discussion criticizes city priorities, arguing that settlement money intended for economic redevelopment has instead been directed toward infrastructure gaps, even as major investments like a planned Google data center in nearby New Florence signal broader regional tech growth. Hashtags: #StLouis #BuschStadium #Waymo #SelfDrivingCars #RamsSettlement #WaterRates #Google #MissouriPolitics #UrbanPolicy #TechInvestment

Andy discusses the upcoming SEC Spring Meetings and the current outlook for the CFP playoffs, plus Eli Hoff joins the show to talk all Mizzou sports!

In this episode, I sit down with three senior product leaders who just came through the senior job search in this market: Dana Ingraham from Harvey, Briana Ings from Atlassian, and Pei-Chin Wang, who's founding her own company. While the search itself continues to be exhausting, I was surprised to learn that everything else has changed: the playbook is completely out of date, in at least ten different ways. All three reported feeling something I've started calling smiling exhaustion: working hard, going long, and surprised by how good it feels. If you're a senior leader, sitting in a stable role debating a move, weighing how you can ride the AI shift, or quietly wondering if founding finally belongs on your career path, this conversation is for you.Key topics:• How AI agents have flipped the first year at a new role from headwind to tailwind, and are even bringing joy to the first year of a new role• The new founding math: fast, fun, and skill-additive, with a much lower downside than it used to be• How to navigate the job search when you don't live in San Francisco—and remote jobs are dwindling• Why structured AI learning is the wrong move, and what to build instead, so your fluency is hard to fake• How to signal hard boundaries to a new boss, and differentiate between real respect and performative virtue-signalling• Why holding your professional identity loosely matters when the role of senior leader is getting reformatted in real timeReferenced:• Airbnb: https://www.airbnb.com/• Atlassian: https://www.atlassian.com• Claude Code: https://claude.com/product/claude-code• Harvey: https://www.harvey.ai• Loom: https://www.loom.com• Modern Animal: https://themodernanimal.comBrought to you by:• Guru—Trusted knowledge for every AI tool and team: https://www.getguru.com/?utm_source=the-skip&utm_medium=podcast&utm_campaign=skip-promo• Customer.io—The customer engagement platform for human messaging: http://customer.io/skipWhere to find Nikhyl• Twitter/X• LinkedInWhere to find Dana• LinkedInWhere to find Briana• LinkedInWhere to find Pei-Chin• LinkedInJoin The Skip• Skip Coach• Skip CommunityFind The Skip• Website• Substack• YouTube• Spotify• Apple PodcastsTimestamps:00:00 Introduction04:08 Welcome, and why this is the second job-search postmortem05:50 Meet Dana, Briana, and Pei-Chin06:15 What the "smiling exhaustion" state is09:58 Three career transitions, three different triggers15:26 Has founding become a must-have on the modern career path?17:09 Why "AI company" doesn't need to be a hard filter21:43 The new founding math: Three-month traction windows and "everyone codes"26:16 How AI agents flipped onboarding from headwind to tailwind31:33 How to navigate the decline of remote-friendly roles36:27 Setting hard family boundaries in the 996-company era40:47 How proactive do senior leaders need to be to build their role pipeline?43:10 Standing out to recruiters when your CV lacks traditional experience47:43 Discovering Claude Code: "I felt like a sorcerer"53:21 Why structured AI learning isn't necessary57:21 When your resume doesn't fit the pattern, teach the interviewer58:48 Closing wisdom: hold your identity loosely This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit theskip.substack.com

The two main features today come after lunch starting with Fed minutes and concluding with Nvidia's post-close results. High yields have stocks down three straight sessions.Important Disclosures This material is intended for general informational and educational purposes only. This should not be considered an individualized recommendation or personalized investment advice. The {securities, investment products and investment strategies mentioned are not suitable for everyone. Each investor needs to review an investment strategy for his or her own particular situation before making any investment decisions. For illustrative purpose(s) only. Investing involves risk, including loss of principal, and for some products and strategies, loss of more than your initial investment. Supporting documentation for any claims or statistical information is available upon request. Past performance is no guarantee of future results. Diversification and rebalancing strategies do not ensure a profit and do not protect against losses in declining markets. Indexes are unmanaged, do not incur management fees, costs, and expenses and cannot be invested in directly. For more information on indexes, please seeschwab.com/indexdefinitions. The policy analysis provided by the Charles Schwab & Co., Inc., does not constitute and should not be interpreted as an endorsement of any political party. Digital currencies [such as bitcoin] are highly volatile and not backed by any central bank or government. Digital currencies lack many of the regulations and consumer protections that legal-tender currencies and regulated securities have. Due to the high level of risk, investors should view digital currencies as a purely speculative instrument. Cryptocurrency-related products carry a substantial level of risk and are not suitable for all investors. Investments in cryptocurrencies are relatively new, highly speculative, and may be subject to extreme price volatility, illiquidity, and increased risk of loss, including your entire investment in the fund. Spot markets on which cryptocurrencies trade are relatively new and largely unregulated, and therefore, may be more exposed to fraud and security breaches than established, regulated exchanges for other financial assets or instruments. Some cryptocurrency-related products use futures contracts to attempt to duplicate the performance of an investment in cryptocurrency, which may result in unpredictable pricing, higher transaction costs, and performance that fails to track the price of the reference cryptocurrency as intended. Please read more about risks of trading cryptocurrency futures here. Fixed income securities are subject to increased loss of principal during periods of rising interest rates. Fixed income investments are subject to various other risks including changes in credit quality, market valuations, liquidity, prepayments, early redemption, corporate events, tax ramifications, and other factors. All expressions of opinion are subject to change without notice in reaction to shifting market, economic or political conditions. Data contained herein from third party providers is obtained from what are considered reliable sources. However, its accuracy, completeness or reliability cannot be guaranteed. Schwab does not recommend the use of technical analysis as a sole means of investment research. The Schwab Center for Financial Research is a division of Charles Schwab & Co., Inc.Apple Podcasts and the Apple logo are trademarks of Apple Inc., registered in the U.S. and other countries. Google Podcasts and the Google Podcasts logo are trademarks of Google LLC. Spotify and the Spotify logo are registered trademarks of Spotify AB. (0130-0426) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ryan, Dana, and Nathalie Rodriguez discuss Trump's remarks on Cuba saying “we are going to get that solved,” including expectations that the U.S. will unveil criminal charges against Raul Castro.See omnystudio.com/listener for privacy information.

You introduced the new tool. You explained it. You maybe made a Loom. And your team is still doing it the old way. This isn't a people problem- it's almost always a framing problem. When leaders lead with what the organization needs instead of what each person gets, adoption stalls. Every time. In this episode, Lia breaks down the framework she's used at Microsoft, Apple, and Google to change that.In this episode you will learn:Why "we need this" is the wrong frame for any rollout and what to lead with insteadHow reframing a new platform around what the design team actually wanted got full adoption at Microsoft in one weekThe one question to ask before introducing anything new: what does each person specifically get from this?What this looks like in practice for a simple weekly check-in processAn introduction to Snippets: Lia's new web app for team check-ins built around making adoption straightforwardResources mentioned:Snippets web app: liagarvin.com/snippetsLooking for support for yourself of your team? I've got you covered.Explore manager training, leaders keynotes & offsites, and 1:1 advisory, or my 90-Day-COO program for business owners who want simple systems that actually work.I help teams build clarity, accountability, and momentum through practical tools and research-backed strategies that make managing easier.Get all the details at: www.liagarvin.comor reach out at hello@liagarvin.com

Welcome to this episode of the Legal Nurse Podcast! In this episode, Pat Iyer and Tracey Kapper dive into the transformative power of video marketing through the lens of their newly released books, "AI-Powered Video for LNC's" and its companion workbook. Listeners are invited behind the scenes as Pat Iyer shares her journey from nervously recording presentations with outdated technology to becoming a seasoned video creator, offering invaluable tips for overcoming common obstacles like stage fright, equipment overload, and noisy backgrounds. Tracey Kapper, on the other hand, recounts her recent entry into video production, driven by the need to stand out in a crowded legal consulting field, and discusses the challenges and rewards of video challenges that pushed her out of her comfort zone. The conversation explores both practical and emotional strategies for getting started with videos, highlighting the importance of consistent practice, learning to edit, and adapting to evolving technologies. They address the significance of creating concise, engaging content tailored to the needs and language of legal professionals. They also discuss current tools such as AI-powered teleprompters, free editing programs, and platforms like Loom and Canva that make video production accessible to beginners and professionals alike. Throughout the episode, they emphasize authenticity and the willingness to experiment, urging legal nurse consultants to start, even if their early videos feel awkward. They offer guidance on leveraging AI for topic research, the nuances of protecting expert witness credibility, and maximizing visibility through platforms like LinkedIn, YouTube, and Instagram. Whether you're new to video or looking to refine your process, this episode is packed with actionable insights, relatable stories, and encouragement to embrace video in your professional journey. What You'll Learn in This Episode on Overcoming Video Anxiety with AI Tools and Practical Editing Tips Here are 5 discussion questions answered in the podcast: What were the initial challenges faced by Speaker A and Speaker B when they started creating videos, and how did they overcome them? How has video content changed the way legal nurse consultants and related professionals market themselves to attorneys? What are some advantages and drawbacks of using AI tools, such as ChatGPT and AI-generated videos, for content creation as discussed in the episode? In what ways can participating in video challenges help professionals become more comfortable with video marketing? How important are editing skills for producing effective marketing videos, and what editing tools did the speakers recommend? Listen to our podcasts or watch them using our app, Expert.edu, available at legalnursebusiness.com/expertedu. Get the free transcripts and also learn about other ways to subscribe. Go to Legal Nurse Podcasts subscribe options by using this short link: http://LNC.tips/subscribepodcast. https://youtu.be/DzwiSe6xptQ Your Presenter for Overcoming Video Anxiety with AI Tools and Practical Editing Tips Pat Iyer Pat Iyer is a seasoned legal nurse consultant and business coach, renowned for her expertise in guiding new legal nurse consultants to successfully break into the field. As the host of the Legal Nurse Podcast, Pat addresses critical challenges that legal nurse consultants face, such as difficulty in landing clients and a lack of response from attorneys. Through her insightful episodes, she emphasizes the importance of effectively communicating one's value to potential clients. With a wealth of experience, Pat has empowered countless consultants to overcome these hurdles and thrive in their careers. Connect with Pat Iyer by email at patiyer@legalnusebusiness.com Tracey Kappers IV sedation nurse expert, legal nurse consultant, scuba diver, and travel enthusiast. I began my career in high-acuity trauma ICU, cardiac critical care nursing, and recovery room with experience in GI endoscopy and procedural sedation recovery. I now work with attorneys through TKO Consulting, reviewing medical records and translating complex clinical details into clear timelines and insights that support case strategy. My work focuses on identifying what happened clinically, what should have happened, and where breakdowns occurred in patient care. With a background spanning ICU trauma care, procedural sedation, and outpatient recovery, I bring a practical clinical perspective to legal cases involving medical injury. When she is not on this podcast, she is scuba diving in some of the world's most memorable waters or spending time with her family and planning her next travel adventure. Connect with Tracey Kappers by email at traceykappers@tkoLNCconsulting.com

Comprehensive coverage of the day's news with a focus on war and peace; social, environmental and economic justice. Senate passes War Powers resolution (finally), House vote expected Wednesday; Dems blast Iran war as strategic failure as commanders testify before House Armed Services committee; States hold primaries as gerrymandering in southern states threaten Black representation on massive scale; California joins lawsuit over Trump administration's student loan rules limiting access for critical professional degrees; Health activists urge Governor Newsom to approve $500 million emergency health funding as federal cuts loom The post Senate passes War Powers resolution on 8th try; California health activists urge $500 million emergency health funding as federal cuts loom – May 19, 2026 appeared first on KPFA.

Ben Pascoe visited the Loom assistance center in Bratislava to find out how the first year has been and what the center is offering to foreigners living in Bratislava. Zuzana Weberova, Dominika Nagyova and Salma Al Henami from the center explain some of the problems foreigners in Bratislava face and how Loom is trying to help.

Damaging winds, hail and flash flooding are possible as rounds of thunderstorms track from the Plains and Midwest into the Ohio Valley, mid-Atlantic and Northeast through midweek. Also, the human-caused wildfire has burned more than 10,000 acres on Santa Rosa Island, forced the island to close and sent smoke drifting into parts of Southern California. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Richard McGirr talks about how his firm crushed their previous fundraising record with $6.1 million, but the real secret lies in how they're turning this momentum into a repeatable pipeline. He explains how a strategic cross-sell campaign, tapping into existing relationships, generated over a quarter-million dollars in commitments overnight, all by leveraging personalized Loom videos and exclusive tier-based perks. Discover the step-by-step behind the scenes, including how personalized outreach and complex concepts like "relationship balance" can unlock new capital without chasing cold leads. Book your free demo today at bill.com/bestever and get a $100 Amazon gift card. Visit https://m1.com/ for more info.  Podcast production done by⁠ ⁠Outlier Audio⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

Send us Fan MailShe was leading her team through one of the most stressful quarters of her career. Layoffs were in the air. She was fighting hard behind closed doors to protect every person who reported to her. And in every team meeting, she said the same thing, with all the conviction she could find: everything is going to be fine.She meant it as protection. Her team heard something else entirely.In this Monday Momentum episode of Communicate to Lead, Kele Belton shares what happens when high-performing women leaders try to shield their teams from uncertainty by offering reassurance they cannot guarantee, and the one communication shift that rebuilds trust and refocuses a team in the middle of a shaky moment.What You Will LearnWhy premature reassurance, even when it comes from a place of care, creates distance with the high-performing team members you most want to keep engaged.The difference between managing your team's emotions and respecting their intelligence, and why one builds trust while the other quietly erodes it.A simple two-part communication move you can use in your next team meeting to name uncertainty directly and anchor your team in what they can own.Your Action StepBefore your next team meeting, write down three things: what you know, what you are still working to find out, and one priority your team can own right now. Open the meeting by saying those three things out loud. Close by inviting your team to come to you individually if they need more.Ready to Go Deeper?Book a complimentary Leadership Strategy Call with Kele to talk through what you are navigating with your team and identify the next move that will steady your leadership in this season.About Your HostKele Belton is a communication and leadership trainer who specializes in helping women leaders develop confidence and impact through strategic communication and practical leadership frameworks.Connect with KeleLinkedIn: https://www.linkedin.com/in/kele-ruth-belton/Instagram: https://www.instagram.com/thetailoredapproach/Website: https://thetailoredapproach.com

Mark Chapman is joined by Roy Keane and Micah Richards as the trio look back at West Ham United's costly 3-1 defeat away to Newcastle United, which sees the Hammers two points adrift from safety, with Tottenham Hotspur in 17th also having a game in hand.•You can watch the Premier League action live on Sky Sports. If you're not already a Sky customer, you can stream Sky Sports on your terms with a NOW membership. Sign up to NOW here: www.nowtv.com/membership/watch-sky-sports?DCMP=ilc_skysports_podcastlink•Listen to every episode of the Sky Sports Premier League Podcast here: www.skysports.com/podcasts/36578/11933957/sky-sports-premier-league-podcast-post-match-analysis-from-super-sunday-mnf-and-more•You can listen to the Sky Sports Premier League Podcast on your smart speaker by asking it to "play Sky Sports Premier League Podcast".•For all the latest Premier League news, head to www.skysports.com/premier-league•For advertising opportunities email: skysportspodcasts@sky.uk

The Alabama Crimson Tide's recruiting machine hits a rare snag—can Kalen DeBoer's staff fix critical gaps in the trenches before the May 29 visit bonanza? Star prospects like Mitchell Turner and John Meredith headline a must-win weekend as Alabama battles concerns over the lack of offensive tackle and defensive line recruiting dominance, shaking the foundation that powered past championship runs. Elijah Havens and Trent Seaborn lead a quality six-man commitment list, with high-upside defensive lineman Avrian Pauley deserving more attention, and versatile athletes like Colt Lumpus and Kenneth Simon II adding upside. Is this enough to offset glaring concerns at offensive line and defensive tackle? With top prospects like Monshun Sales, Hayden Step, and Malik Howard set to visit, all eyes are on whether Alabama can restore its recruiting edge—or risk falling behind SEC rivals in the race for future national titles. Everydayer Club If you never miss an episode, it's time to make it official. Join the Locked On Everydayer Club and get ad-free audio, access to our members-only Discord, and more — all built for our most loyal fans. Click here to learn more and join the community: https://theportal.supercast.com/ Support us by supporting our sponsors! Indeed Listeners of this show get a $75 Sponsored Job Credit to help give your job the premium placement it deserves at http://Indeed.com/podcast FanDuel Today's episode is brought to you by FanDuel. Right now new customers can bet just five dollars and get one-hundred and fifty dollars in bonus bets if your first bet wins. Visit https://FANDUEL.COM to get started — Play Your Game. FANDUEL DISCLAIMER: 21+ in select states. First online real money wager only. Bonus issued as nonwithdrawable free bets that expire in 14 days. Restrictions apply. See terms at sportsbook.fanduel.com. Gambling Problem? Call 1-800-GAMBLER or visit FanDuel.com/RG (CO, IA, MD, MI, NJ, PA, IL, VA, WV), 1-800-NEXT-STEP or text NEXTSTEP to 53342 (AZ), 1-888-789-7777 or visit ccpg.org/chat (CT), 1-800-9-WITH-IT (IN), 1-800-522-4700 (WY, KS) or visit ksgamblinghelp.com (KS), 1-877-770-STOP (LA), 1-877-8-HOPENY or text HOPENY (467369) (NY), TN REDLINE 1-800-889-9789 (TN) (KS), 1-877-770-STOP (LA), 1-877-8-HOPENY or text HOPENY (467369) (NY), TN REDLINE 1-800-889-9789 (TN) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What happens when AI stops being a feature and starts reshaping the very craft of design itself? Live from, I sat down with Charlie Sutton for a conversation that went far beyond product interfaces and pixels. As Atlassian unveiled its latest AI ambitions around agents, context, and the Teamwork Graph, Charlie offered a fascinating look at the human side of that transformation and why design may become even more important as AI becomes embedded into the way we work. Charlie shared how Atlassian approaches design at scale across products like Jira, Confluence, Loom, and Rovo, explaining why every interaction should feel intentional and cohesive, even when built by hundreds of people across dozens of teams. But this conversation quickly moved into much bigger territory. We explored how AI is changing the relationship between designers, developers, and business teams, and why the traditional barriers between idea and execution are rapidly disappearing. One of the most thought-provoking parts of the discussion centered around democratization. Charlie argued that while AI tools have dramatically lowered the floor for creativity, they have also raised the ceiling for what users now expect from software experiences. Anyone can prototype an app today, but expectations around quality, coherence, trust, and usability are climbing just as quickly. We also unpacked the growing shift from prompting AI to delegating work to AI agents. Charlie explained why assigning work to agents increasingly resembles managing human teammates, from defining goals and success criteria to understanding strengths, limitations, and context. That naturally led us into a deeper conversation about trust, transparency, and why users must always feel they can "pop the bonnet" and understand what AI systems are doing on their behalf. Another major theme throughout the episode was context. Charlie shared why Atlassian sees organizational context as one of the defining challenges of the AI era and how the Teamwork Graph is helping connect people, projects, conversations, and knowledge across the company. He compared this moment to the first time many of us used Google search and suddenly realized the scale of what was possible. We also discussed how AI adoption is unfolding differently from previous technology waves. Instead of adoption trickling down from hardcore technical users, Charlie is seeing rapid experimentation from marketing, HR, and design teams looking to reduce repetitive work and communicate ideas more effectively. Even his own mother, he joked, has become an AI power user before he has. From AltaVista nostalgia and Ask Jeeves memories to serious conversations about the future of human creativity, this episode captures a rare and honest perspective on where design, collaboration, and AI may be heading next. How will organizations balance personalization with shared experiences as AI becomes embedded into every workflow, and what role will human creativity play when everyone suddenly has access to the same powerful tools? Please check the partners of the Tech Tech Talks Network Learn more about the NordLayer Browser Visit Denodo.com

What happens when one of the most iconic teams in Formula One decides to rethink how work gets done behind the scenes completely? Last year, Atlassian Williams Racing made headlines when Atlassian entered Formula One as both title partner and technology partner. At the time, many people saw the partnership as another high-profile sponsorship deal. But over the last twelve months, something much bigger has been unfolding inside the Williams organization. At Team '26 in Anaheim, I sat down with Andrew Boyagi and Matt Harman to unpack how AI, data, workflows, and organizational transformation are reshaping life both at the factory and on the grid. This conversation goes far beyond racing. Matt explains how Williams is reducing the time between "idea to track," compressing development cycles so upgrades arrive at race weekends weeks earlier than before. One striking example involves reducing front wing lead times by a factor of three through parallel workflows and better collaboration, allowing performance gains to reach the circuit three race weekends sooner. Andrew shares how Atlassian's system-of-work philosophy is being applied in one of the most data-intensive environments on earth. We explore how tools like Jira, Confluence, Loom, Rovo, and Teamwork Graph are helping engineers, strategists, operations teams, and factory staff make faster decisions with less operational friction. We also discuss how AI is changing engineers' roles, why organizational context matters more than raw intelligence, and how Formula One teams balance human instinct with AI-driven precision in race strategy decisions. Matt offers fascinating insight into how AI helps teams process decades of historical race data in real time while still relying on human judgment in critical moments. Along the way, we explore the cultural transformation underway at Williams, including the shift away from endless meetings toward faster, outcome-focused collaboration. Matt explains how tools like Loom and Confluence are helping teams make decisions more efficiently while spreading knowledge more effectively across specialist departments. Andrew also reveals some eye-opening metrics from the partnership so far. Since rolling out Atlassian's Teamwork Collection, teams have reportedly increased throughput by 83%, while low-value meetings have been reduced by 863 hours in a single month across 200 people. Perhaps the biggest takeaway from this episode is that Formula One may actually be a perfect reflection of the challenges facing every modern business. As Andrew puts it during our conversation, Formula One is ultimately "an enterprise performance problem," just operating at 300 kilometers an hour with millions of people watching every weekend. If you've ever wondered what enterprise transformation looks like when milliseconds matter, this episode offers a fascinating look inside one of the most ambitious AI and workflow transformation journeys happening anywhere in business today   Please check the partners of the Tech Tech Talks Network Learn more about the NordLayer Browser Visit Denodo.com

Special discounts up for AIE Melbourne (LS discount) and AIE World's Fair (group discounts up to 25% - CFPs still open for Autoresearch and Vertical AI) Cya there!Abridge did not start as an “GPT wrapper”. It was founded in 2018, years before the Cambrian explosion of AI application layer companies. OpenAI launched ChatGPT publicly on November 30, 2022 and by then, Abridge had already spent years doing the unglamorous work of building trust for one of the highest context, most important workflows in healthcare: the conversation between a patient and a clinician.Abridge's original wedge was clinical documentation. Listen to the visit, generate the note, reduce the clerical burden, and let clinicians spend more time with patients instead of the EHR. By focusing on how doctors actually document, how health systems actually buy, how EHR integration actually works, how clinicians verify outputs, and how missing context during a visit turns into downstream friction across billing, prior authorization, quality, and follow-up, the adoption of LLMs became a force multiplier on a workflow already optimized for sensitive context gathering.The company has scaled fast: Abridge says it is projected to support 80M+ patient-clinician conversations this year across 250 large and complex U.S. health systems, with support for 28+ languages and 50+ specialties. It raised $300M at a $5.3B valuation in June 2025, after a $250M round earlier that year.Today, Janie Lee and Chaitanya “Chai” Asawa of Abridge join us for another crossover pod with Redpoint's Jacob Effron (who is on the board of Abridge) to dive into how Abridge is building the clinical intelligence layer for healthcare starting with ambient documentation, then expanding into clinical decision support, prior authorization, payer/provider/pharma workflows, and eventually real-time agents that act before, during, and after the patient conversation. We go inside the product, data, infra, evals, workflow, privacy, and org design choices behind bringing AI into one of the highest-stakes enterprise environments from 100M+ medical conversations and specialty-specific evals to real-time alerts, EHR integration, de-identification, clinician-scientist teams, and why healthcare may solve some of the hardest AI problems first.We discuss:* Why Abridge started with clinical documentation, “pajama time,” and saving clinicians 10–20 hours a week* The transition from ambient scribe to clinical intelligence layer: save time, save money, and save lives* Why conversations between patients and clinicians may be the most important workflow in healthcare (patient visit summary feature)* Chai's “healthcare-coded Glean” framing: context is king, but healthcare raises the stakes on safety, evals, and rollout* Why Abridge wants AI to feel like “air conditioning”: always in the background, but only interrupting when it truly matters* The prior authorization example: turning a denied MRI weeks later into real-time guidance while the patient is still in the room* Why payer policies, EHR data, medical literature, and hospital-specific guidelines make the problem hard, and also create the moat* How Abridge thinks about ambient form factors: mobile, desktop, in-room devices, nursing workflows, multimodality, and future AR* The multi-sided healthcare customer: CMIOs, CFOs, CIOs, clinicians, patients, payers, and pharma* The hardest AI problem at Abridge: high-quality, low-latency, low-cost real-time support in a high-stakes clinical setting* When Abridge uses frontier models vs proprietary models, and why its unique data from medical conversations matters* Why “every agent is a coding agent underneath,” and how the EHR can be thought of as a filesystem for healthcare agents* How Abridge approaches personalization across individual doctors, specialties, and health systems* Why “AI slop” is AI without context, and how edits, memories, and clinician preferences create a data flywheel* Abridge's eval stack: LFDs, LLM judges, in-house clinicians, third-party evaluators, specialty-specific evals, and progressive rollout* HIPAA, PHI, de-identification, one-way anonymization, customer contracts, and learning from healthcare data safely* What changes when you operate at 100M+ conversations: reliability, cost, post-training, model routing, and infrastructure optimization* Why the same clinical conversation can serve doctors, patients, payers, pharma, and future clinical-trial workflows* How Abridge works with EHRs, and why deep interoperability is table stakes for clinician adoption* Why healthcare AI has regulatory tailwinds, why 80/20 does not work here, and why high-stakes domains may drive AI forward* Why Abridge embeds “clinician scientists” into product and eval teams* What Chai learned from Glean about search, quality, and durable AI infrastructure* Why the future of AI infra may look like context layers, event-driven systems, Kafka, Temporal, sockets, CRDTs, and tools built for humans* Why Janie changed her mind on “PRDs are dead,” and why crisp written clarity matters more in complex AI products* How Abridge uses Claude Code, Cursor, and coding agents internallyAbridge:* Website: https://www.abridge.com/* X: https://x.com/AbridgeHQJanie Lee:* LinkedIn: https://www.linkedin.com/in/janiejleeChaitanya “Chai” Asawa:* LinkedIn: https://www.linkedin.com/in/casawaTimestamps00:00:00 Introduction and what Abridge does00:02:05 From ambient documentation to clinical intelligence00:04:04 Clinical decision support and context as king00:06:57 Alert fatigue, proactive intelligence, and prior authorization00:12:36 Ambient AI form factors and healthcare customers00:16:59 The hardest AI problems in healthcare00:18:26 Frontier models, proprietary data, and model strategy00:21:07 The EHR as a filesystem for agents00:24:03 Personalization, memory, and clinician preferences00:30:40 Evals, LLM judges, and progressive rollout00:36:47 HIPAA, de-identification, and privacy00:39:21 100M conversations and operating at scale00:44:10 EHR integration and the clinical intelligence layer00:46:39 Healthcare regulation, latency, and high-stakes AI00:50:11 Clinician scientists and long-tail quality00:53:04 Lessons from Glean and durable AI infrastructure00:57:03 The future of agentic healthcare workflows00:57:34 PRDs, product clarity, and building serious AI products01:03:11 AI coding tools at Abridge01:04:06 OutroTranscriptIntroduction: Abridge, Clinical Intelligence, and the Latent Space x Unsupervised Learning CrossoverSwyx [00:00:00]: Okay. This is a special crossover Latent Space Unsupervised Learning pod.Jacob [00:00:07]: Very excited to do this.Jacob [00:00:08]: At this point, we get together once a year.Swyx [00:00:10]: Once a yearJacob [00:00:11]: And this is a fun occasion to get to do it on.Swyx [00:00:13]: I really wanted to talk to Abridge but I felt very underqualified because healthcare is not something we cover very intensely. It just so happens that Redpoint's our big investors and supporters of Abridge.Jacob [00:00:27]: Anytime you want to have a portfolio company on your podcastJacob [00:00:29]: Please, by all means.Swyx [00:00:31]: So we'll introduce our guests. Chai and Janie, welcome to the pod.Janie [00:00:34]: Thanks for having us.Chai [00:00:35]: Thank you.Janie [00:00:35]: We're excited to be here.Chai [00:00:36]: Thank you.Swyx [00:00:36]: So for listeners, what do you guys do, just to situate you guys in the company?Janie [00:00:42]: Abridge is a clinical intelligence layer for health systems. We really started with documentation and building for clinicians and as we think about reducing the burden that clinicians have, they're spending 10 to 20 hours a week on documentation. There's a massive doctor shortage in the country. We also think that conversations between patients and clinicians are probably the most important workflow in healthcare. It's where care is given and received but if you think about the 20% of our GDP that goes towards healthcare, almost everything is a derivative of that conversation, whether it's the claim, the payment, the actual diagnosis given, the treatment. And we've started with a conversation to reduce the burden for doctors on documentation but we're really excited about the path ahead as we become this broader clinical intelligence layer.Chai [00:01:34]: I'm Chai. I work on clinical decision support at Abridge.Swyx [00:01:37]: Yes.Chai [00:01:37]: And so as Janie said, we're uniquely situated where we started off with the clinical note. What I'm really excited about and where we're expanding towards is what are all the things you can do before the conversation, during the conversation and after the conversation if you did have access to all the context about patients, payer guidelines, medical literature and put that together and to serve, how healthcare could look fundamentally different.Swyx [00:02:01]: And that's the context engine that you guys have?Chai [00:02:04]: Yes.Swyx [00:02:04]: Is that what it's called? Okay.Swyx [00:02:05]: So historically, as I understand it, the company started in 2018. A lot of people would be familiar with the AI voice notes form factor that doctors would be “Well, do you consent to being recorded?” It replaces handwriting and what have you. But it sounds like more recently there's been a big transition in the company. Tell me about the broader transition.From Documentation to Clinical Intelligence: Save Time, Save Money, Save LivesJanie [00:02:26]: So from a transition perspective, we really think about our journey as The first act was: how do we help save time? And that's where a lot of that original product was.Swyx [00:02:37]: By the way, one of those interesting statsSwyx [00:02:39]: On your landing page was, doctors spend time after hours.Janie [00:02:43]: They call it pajama time.Swyx [00:02:44]: Why is that pajama time?Janie [00:02:46]: Doctors after work in their pajamasSwyx [00:02:48]: In their pajamas. OhJanie [00:02:49]: At home are just writing and catching up on their notes every day.Janie [00:02:53]: Some of our favorite customer love stories, we have a Slack channel called Love Stories. We have clinicians telling us, “Abridge has helped us, from retiring early or we're now finally able toJanie [00:03:06]: go home and eat dinner with our kids for the first time.”Chai [00:03:08]: Save the marriage in some cases.Swyx [00:03:10]: One of the quotes was “We're not divorcing anymore.”Swyx [00:03:12]: I'm asking, “Why?”Swyx [00:03:14]: Because they're working too much.Janie [00:03:16]: But, in terms of where we're going and where we're expanding, we really think about our second and third acts around how do we help health systems save and make more money. Health systems are operating with record-low operating margins. It's getting harder and harder to serve patients and they have regulatory, some tailwinds but also a lot of headwinds coming their way and AI is ripe for helping on the saving and make-more-money piece. And then ultimately, how do we help save lives? The fact that our software and our product is open millions of times a week before, during and after a patient walks in the room, gives us massive opportunity with products like clinical decision support, which Chai is building but so many others to improve patient outcomes and probably one of the most important workflows and problems to be going after right now.From Glean to Healthcare: Context Is KingJacob [00:04:04]: One thing that's interesting, Chai, is you came over to Abridge from Glean and clinical decision support, which for our listeners is, in the context of a visit, helping a doctor figure out the right type of care. It's really a search problem in many ways, going through lots of different data sources. Very analogous to your previous role as one of the earliest engineers over at Glean. I'm sure a lot of our listeners are curious what's similar about the problems that you're going after now and what feels different, now that you're in healthcare.Chai [00:04:33]: Very similar. Taking a step back, with every wave, there's a lot of very similar patterns that happen across different products. A lot of social networking products look the same. A lot of credit-based products look the same. And we're seeing that very similar in the agent era with many companies, of course, in Redpoint's portfolio and so forth. And the key insight between both companies is that you have amazing models but context is king. Context is what puts them to work. So I see it in a lot of ways, a lot of similarities in this is a healthcare-coded version of Glean but the differences are really interesting. A couple things that come to mind. First and foremost, the rigor of the setting we're in. The downside risk is extremely high here in healthcare. It can be fatal in some cases. You prescribe something that the patient is allergic to for example. Whereas at Glean, it's “Oh, you got the question wrong.” It wasn't the end of the world in most cases. And so what does that mean? That shapes our evaluation strategy, both offline evaluation, progressive rollout and there's a lot more we could go into there. Second thing that comes to mind is, vertical versus horizontal. In both cases, there's a large variance but when Glean is, it's a much more horizontal company, there's a variance of personas, companies that you're working with. We also have a variance of personas, different types of specialties, different hospital systems. But the variance is a little more narrow. So from a product perspective, you're able to focus far more, especially when you have a maturing technology and you're building new products that never existed before. It lets you go after them much more easily and especially in healthcare where so many problems were solved with labor and process, that it's extremely ripe for AI to keep helping augment and enable. And the final thing that's really interesting, Abridge specifically compared to many other companies in the AI area, is the modality we started with where we're ambient and we're always listening in the background. And many more AI products will go that way but it's how we started. And that's the greatest form of AI we can create, AI that's seamless. You're not looking at your screen. It's always there. It's always helping you out and being proactive. The Jarvis vision that, every hackathon I went to over the past decade, there was always a Jarvis competitor. But Abridge very much started from the opportunity and continues to go that way.Ambient AI and Alert Fatigue: When Should the Product Interrupt?Jacob [00:06:57]: One thing that is super interesting then from a product perspective is you have this always-on seamless in the background and then you have to decide when you break the wall almost and say, “Hey, clinician, you might not have thought about X,” or whatever it is that you want to do. And in healthcare traditionally there's been this idea of alert fatigue and a million pop-ups and then a doctor just ignores all of them. It's probably a pattern that a lot of builders are thinking through now. How do you think about the right way to intervene or to pop up in a doctor visit?Janie [00:07:26]: It's such a good question. Alerts are notorious in healthcare specifically. Over 90% of alerts are ignored. The first and most important thing is context is everything, as Chai alluded to and I also think about how do we go from being reactive alerting to really proactive intelligence at the point at which it matters most. One thing we like to say is we want our product to feel like air conditioning. It should be in the background just making things better and if there is something that has great clinical risk and we're acutely aware that intervening now and not later is incredibly important, we should decide to act. But if you think about proactive versus reactive, instead of alerting a clinician during a visit when they're with their patient having a pretty serious and sensitive conversation, how do we prep a clinician before they walk into the room with that patient? And so historically, clinicians might have to manually go through charts with a patient that they've had over the course of months or years and they'll try to suss out what are the things they should be doing. You can imagine a world with Abridge. We'll summarize all of the most recent context for you, tell you based on the reason for a visit the patient is coming in for the types of things you should be discussing. And so you're going into that conversation prepped rather than walking in cold to that patient visit and then having this product interrupt you five or 10 times throughout the visit. And there might be times where it's really important to interrupt. We have a product called Prior Authorization and so this is when you may go into a doctor's office with knee pain. They'll prescribe you an MRI and so many of us have had this experience before, where in four weeks you'll get a call saying, “Hey, Sean, that MRI that you were prescribed wasn't approved and why don't you come back in? We'll figure it out.” In a world with Abridge, we might choose to quietly but still alert a doctor in that visit. And alert is probably not even the word we would want to use. Before a patient leaves, we would want to tell the doctor, “Hey, Doctor, before Sean leaves, you should ask him, has he had physical therapy and has his pain lasted for more than six weeks? Because the Aetna plan that he's on in California requires six things. We've already confirmed four of them have been met ‘cause we have all the context. But these two last criteria, if you can address with Sean before he leaves the room, we could guarantee that your MRI is approved before you leave.” And so when you think about clinical usefulness, impact to the patient, there are instances in which if we can catch a doctor while the patient is still in the room, as we think about save time, save money, save lives, we get to check all of those boxes. But when doctors have 15 minutes between visits, we have to be really thoughtful about when it matters.Prior Authorization: Reducing Latency in CareChai [00:10:23]: There's this interesting product opportunity AI has is reducing latency in the world. For example, prior authorization is an example of where care gets delayed and so great AI can reduce that. And the problem with alerts before partially is a technical problem: the quality of your alerts really matters. They're going to get ignored if you get alerts that... Similarly in engineering, where they're noisy alerts that you can't act on. But if you can make really high-quality alerts with both the context, as Janie said, and really high-quality models, then you can create a whole other game.Janie [00:10:53]: And I really like that experience because it starts to tease apart, what makes this so hard and unique. One, to make that prior authorization example possible, think about all the data that you need to have. You need to integrate with the electronic health record to know all of the patient context. Do we have access to your previous labs, previous imaging? And then to match you and to know that you're on Aetna, we have to collect all of the different payer policies and they vary by state. Some of these payer policies live on websites. Some of them live in unstructured 50-page PDF files.Jacob [00:11:31]: I thought this episode wasJacob [00:11:31]: To make sure we didn't scare people from healthcare.Janie [00:11:34]: But when you think about the things that make it hard, it also gives you the moat.Janie [00:11:39]: And then the second is the AI and the model quality we need to be able to hang our hat on. And so the bar, similarly when I worked at Opendoor, I worked on pricing models. Every outlier wiped out the margins of 30 and so similarly here in healthcare, the bar for accuracy is so high. And then I'd say the last is workflow is everything. If insurance companies deploy AI, it typically happens too late and this is when you have the notorious comical examples of AI just fighting each other when it's too late. But if we can pull forward the use of both the AI but also the ability to solve problems when the patient's in the room, you can start to collapse what typically takes weeks or months after your visit, ideally down to minutes or real-time. And it's where healthcare is both very difficult but also extremely rewarding if you can crack it.Product Form Factors: Mobile, Desktop, In-Room Devices, and ARSwyx [00:12:36]: Just to get some baseline on the form factors, because I've seen some videos on your website and stuff. You guys talk a lot about ambient AI. Is it primarily on the phone? Is there any other form factor that people get Abridge in? Is there an Abridge room setup where it's always on? I don't know.Jacob [00:12:55]: An Abridge podcast studio.Janie [00:12:58]: Primary form factor is mobile and desktop. UsuallyJanie [00:13:00]: Clinicians are walking in and out of rooms with mobile but at the end of the day, when they're closing out their notes or wanting to prep for the day ahead, they might use desktop. We have been having a lot of really interesting partnership conversations with a lot of these in-room device companies as you think about the power of multimodality and even more data, as you think about all of what is not captured today. It is fascinating to think about, especially even as we go into building and scaling our nursing product. It's one where nurses constantly, as they're walking in to check in on a patient for two minutes or maybe even 30 seconds,Janie [00:13:43]: Starting an Abridge experience is probably going to take longer than the visit. And so what can we do with in-room devices that are always on starts to raise really interesting and fun product questions.Swyx [00:13:54]: I was thinking, the way in tech companies we have all these Google MeetSwyx [00:13:58]: And other things, we might as well set up entire rooms with just Abridge tech.Chai [00:14:02]: Very much. AR glasses and related form factors are also relevant: how do we bring the information to the clinician in real-time without a screen, while still letting them focus on the patient?Swyx [00:14:18]: Do you think they want that? I'm skeptical of AR, but I'm curious what you've tried.Chai [00:14:26]: Admittedly, it's not a near-term product roadmapChai [00:14:29]: By any means. I'm being far-fetched.Jacob [00:14:31]: There's some sick AR stuff for surgeries.Swyx [00:14:33]: Really?Jacob [00:14:33]: When people are trying to visualize, you're about to make an incision but you want to see, what the cut might look or what the body might look like inside and they can layer in imaging.Swyx [00:14:43]: That's cool.Chai [00:14:45]: At some point in the future.Janie [00:14:46]: But there are a lot of our largest customers and at the largest health systems integrating already and so even as we think about building into it, unlocks a lot of product capabilities.Swyx [00:14:57]: And just to establish the terminology. Sorry, and I know I'm asking basic questions somewhat for myself but also for the audience who might beHealth Systems, Buyers, Clinicians, Patients, and PayersSwyx [00:15:05]: Less integrated. When you say health systems, it's like the Johns Hopkins, the Kaiser Permanentes.Janie [00:15:09]: Mayos, the Kaisers of the world.Swyx [00:15:10]: These are your customers, right? And the outcome that you deliver for them is happier doctors, reduced cost of processing, reduced mistakes. It's weird in a sense that I feel like there's also, a secondary customer, the customer of the customer and I don't know if you — do you think about it that way?Janie [00:15:28]: The other interesting and complex part of building product is we have our buyers, who are the chief medical information officersJanie [00:15:39]: The chief financial officers, the CIOs of these large health systems. Our users today are clinicians but if you think about who downstream is impacted, it's patients. And so as we build, with every product in mind, we think about who we're building for, who the secondary user is and what does that mean either in terms of experience, security compliance, ROI that we have to make tangible. And so like you said, time savings is one of them. But for CFOs, they care a lot more than just time savings. We have to show for every dollar you put into Abridge, because you have more compliant documentation or because you have fewer queries coming from your billing team, we save or add real dollars to your bottom line or top line, are things that we're constantly thinking about because of the dynamic across all three sets of users.Chai [00:16:32]: There's a whole other axis too with the payers and pharmaChai [00:16:35]: as well. Connecting all these three big stakeholders in healthcare isSwyx [00:16:39]: Do the payers ever see your data? Sorry, the payers meaning the insurers, right?Chai [00:16:44]: Yes.Swyx [00:16:44]: They also see Abridge data?Chai [00:16:47]: NoSwyx [00:16:47]: Like the direct integration to you guysChai [00:16:48]: They wouldn't see the raw Abridge data but when you're working together on something like prior authorization, whatever information they need, we'd communicate to them.Jacob [00:16:59]: That's cool. I would love to dig into the AI side. You still have a lot of problems on the AI side. And so maybe to start at the highest level, what's one of the hardest problems you have to solve in AI at Abridge today?The Hardest AI Problems: Quality, Latency, and CostChai [00:17:11]: To make things simple, let's take, building off the prior auth example. So one thing Janie talked about is okay, this data is all over the place and there's this combinatorial explosion of procedures, payer policies and even sometimes different health systems. There can be some cross-product of all of these different considerations you have to take into account. But what's really hard about this problem is doing it real-time in the conversation. So, in any AI product, usually the three KPIs you care about are quality, latency and cost. Now, what we're saying is we want you to do this real-time in the conversation, guiding the clinician. How do we do it in a way that does not break the bank? But we're using — But we also need very intelligent models because you're working with this cross-product of data and this, all this context layer as well. So you need high intelligence and high-quality because you don't want the alert fatigue but you also need to be fast and cost-effective. And so that's where a lot of clever engineering goes. It's okay, without getting into all the details here, can you model these policies in some intermediate representation or other things that you can do that can make this problem tractable? And of course, the Pareto frontier is always changing but we are also trying to do this now.Model Strategy: Third-Party Models, Proprietary Data, and Medical ConversationsJacob [00:18:26]: What implications has that had for what you take off-the-shelf and say, “ what? We don't need to be world-class at X. We'll just take this from the model providers or from some infrastructure player,” and what you're “No, this is where we spend most of our time focused on”?Chai [00:18:38]: This is, the fun challenge in AI?Jacob [00:18:42]: It changes every three months? SoChai [00:18:42]: Of course, with the shifting landscape, we try to be extremely thoughtful on predicting the trends of where third-party models are going and where we can uniquely go. And, sometimes when you talk about AI models, we're the models are just going to get infinitely better. But I don't think... It may be in the grandness of time you could say that but, within every month, every quarter, there's specific ways they're getting better. They're training on a lot more, coding data to be better coding agents, for example. And soChai [00:19:14]: We have to think about where are the things that won't — unique data that we're uniquely training on or to step back a little, where is a proprietary model bringing advantage to us is if it can give higher quality or lower cost and latency for similar quality, very similar to many other companies. And when we can do that is when we have proprietary data. So, for example, we have on the order of eighty million or hundreds of millions now getting close to of medical conversations.Jacob [00:19:44]: It's insane.Chai [00:19:45]: This is a unique data set. And this data set, it's very interesting because this data set is effectively a large part of the trace between the patient and the provider. That's where the quote-unquote debugging happens in healthcare. We have these traces at scale, as in as, our CEOs even called it, an exhaust that comes out of our product. And so when you have these traces, that's how you can train better agents on certain use cases, whether it's your transcription diarization use cases or so on or like note generation models and we can do that much cheaper and faster. But we're always also working with these third-party model providers. We closely collaborate with them and that's how we predict where the trends are going. The thing that I think about a lot is that, I know that the model providers are going to train much more on agentic workflows and so forth, so that's great, so that you have a better agentic harness. But the other thing that's interesting is that the model providers, because a large class of the consumer model providers is healthcare queries, that they might, optimize to train a lot of healthcare data to encode the knowledge in its weights. And this is just a great thing for us as well, where the off-the-shelf models can keep bett-getting better at general healthcare information, such that what our strategy is, we have a constellation of models, we can use something for this, that and, we only care about, at the end of the day, the best product experience.EHR as File System: Agentic Workflows and Real-Time InterfacesJacob [00:21:07]: And, you have, overall capabilities improving. I'm curious, as these models get better, is there something you look at and you're “, three months ago, we really couldn't do that but God, the the latest models really allow us to do it”?Chai [00:21:19]: So here's something interesting that I've, been toying with. So all models are... This wasn't super obvious a year ago but now it's become clear and clear that almost every agent is a coding agent underneath the hood? So you give it whatever file system, it can write its own code and so forth. So when you think about within healthcare and the use case that we have, you can think of the EHR effectively like a file system. It's just — it's a storage of all this information. It's a lot of information there that cannot fit into the context window, at least of today's models and you want to use that context effectively for all these product use cases we're talking about. And so if you have better agents that can, manipulate data, read that data, treat it as a file system as we see they're going and we know model companies are investing this way, then that very directly benefits us.Swyx [00:22:09]: Yeah. Okay, cool. Again, just establishing basic things. But we're going back to the model stuff. I'm really interested in double-clicking more on the real-time, element, which is pretty important for both of you. Is it — Is real-time just batches of every one minute, every five minutes? Is that how we do it? Or is there some more native, genuinely real-time in the sense that OpenAI has a real-time API or Gemini has a real-time API?Chai [00:22:35]: Yeah. Yeah. So today it is more on the on the batch basis but there's interestingChai [00:22:41]: Prototypes that we have that we're still not fully, full time, voice in text out or in that sense. But, can you trigger your models, your agents or agentic workflows, depending on the right times in the conversation?Chai [00:22:58]: And so you can imagine, different techniques to bring this latency down and, you want to bring the feedback loop down as much as you can. And so a lot of clever engineering there without fully... Maybe one day we'll do full voice in and text out, train a model to do something like that.Swyx [00:23:15]: You do — People don't want voice in voice out?Chai [00:23:18]: Now we aren't creating experiences that are, during the conversation, inter — It's almost likeSwyx [00:23:25]: Might be too disruptiveChai [00:23:26]: Too disruptive until, who knows, maybe eventually you could have full voice agents once we — the quality and we improve the comfort of the technology. But right now gra — that change is much more gradual and it's more text focus, text out.Janie [00:23:42]: And so much of currently what our product is trying to do is allow a clinician to focus on their patient and maybe at some point but right now patients, clinicians don't want a third voice, at least in a literal voice in that room. And so how do we be there with all the contacts and information ready at hand when there's the right moment?Personalization: Individual Doctors, Specialties, and Health SystemsJacob [00:24:03]: Jenny, one thing I'm curious about is how you think about, personalization in the product. I imagine, every doctor is a special snowflake in their own way, has their own way they like to do things. There are probably a bunch of different approaches you could take to doing that, both within the model layer itself but then also just with clever prompting or engineering. How do youJacob [00:24:20]: Deliver on that?Janie [00:24:21]: It's such a good question. Personalization is massive for us. We think about personalization at three levels. The first is at the individual, the second is at the specialty level and then the third is at the health system or the organization level. To your point, there are a lot of individual preferences. You-When a note is produced, it almost is a reflection that is so deeply personal of a doctor's work and how they give care. And so do they have preferences on things like style? They might want bullets versus paragraphs, really concise versus comprehensive. They also might have phrases that they really like to use or the templates that they want every note to be structured. And, we see it in our feedback all the time. We want two spaces in between sentences or I refuse to use this tool. And so that's something that we've had to build in. And the tricky part is how do you make sure that stylistic preferences don't interrupt accuracy and quality and that's something that we've really had to refine and hone over time. Second is at the specialty level. A cardiologist note or workflow is going to look very different from a dermatologist workflow.Jacob [00:25:32]: I assume cardiology notes are the highest stakes for you guys, given your CEO is a cardiologist.Jacob [00:25:36]: It's “Oh my God, make sure we get this one.”Janie [00:25:37]: Shiv, our CEO, is still a practicing cardiologist. He rounds once a month. And so, first call when we want just quick and easy user feedback too.Janie [00:25:46]: But, specialties require a lot of personalization, both in terms of what does the product look and so we make sure that as new users onboard, we catch that and the product proportionally reflects that. But also on the back end, evals at the specialty level, they are hard-earned to calibrate and get. What does a really great dermatology note look like? What makes it complete? What makes it compliant and billable is very different than a primary care doctor. And so it's not just about what does the product experience look but on the back end tuning and really deepening our understanding for the specialists. What does great output look like? And that's, a problem that we need to calibrate internally, externally, online, offline but, takes lots of cycles but is necessary in a high-stakes environment. And then at the health system level, for products like clinical decision support, you have health systems who've spent years or decades refining their best practices and they want to know, “Hey, we love your clinical decision support product but how do we embed our own hospital guidelines into them to inform clinicians before, during or after a visit what brest — best practices should look like?” And as you think about, deepening moats as well, when health systems, trust us with that data, allow us to productize it and directly into the clinical workflow, makes us a really great partner to health systems who want to build something that truly meets their needs, their practicing guidelines.AI Slop, Memory, and Product Data FlywheelsChai [00:27:23]: And I want to add onto that. The for the clinical documentation problem, it's very similar to AI writing that doesn't feel like your own and then we call that slop. But the way I describe one framing of slop is like AI without context. But we have all that context and both the clinicians, can have it and can guide it. And so part of the other interesting exhaust for us is, memory is, one of these new systems recordsChai [00:27:49]: Almost.Janie [00:27:50]: And we also have all the edits people make on our product and when you think about a data flywheel and how we get better over time becomes really powerful as a mechanism to just going deeper in personalization.Jacob [00:28:04]: It's interesting. I love this idea of working with systems on the guidelines they built up over a long time. I feel like so many of the best AI app companies today are... The question is: How do you take the expertise that a law firm or a bank has built up over many years and then add that as context and also a special sauce over, a an AI tool? And so seems like y'all are really doing that very effectively.Janie [00:28:24]: We're now starting to have our customers ask, “What are other customers doing?”Janie [00:28:28]: “And how are they doing it?”Janie [00:28:30]: And as we think about having visibility across such a large set of care being delivered right now, a really interesting place we could also partner.Swyx [00:28:40]: I'm just curious. I — This may be a nothing question but, how different are health system guidelines from each other? Don't they all converge to the same thing? And if not, where do they differ?Chai [00:28:52]: At a really high level, they're going to talk about very similar things but the difference is probably in some more of the details. “Oh, you should refer to specialists only when XYZ conditions are met,” or so forth and maybe different organizations have different practices and guidelines around that. But high level, talking about similar things but the details are what, of course, that shapes the context and the decisions you make.Swyx [00:29:15]: And this all goes into the context engine and it might affect the notes but maybe not.Chai [00:29:21]: The — For these local pathways, we're definitely thinking about it a little more for our clinical decision support product.Chai [00:29:26]: So yeah.Swyx [00:29:27]: Which is your stuff, yeah.Swyx [00:29:28]: And then the memory which you raised, let's just tell us more about that. What have you tried in memory? What's the structure of the memory? What works? What doesn't work?Chai [00:29:38]: There's, of course, many different ways you could do memory, where it's okay, can you bake it into the model weights or can you do it in some external store? For us, what's interesting is, of course, when you think the models are rapidly changing, whether it's in-house or third-party, baking into the model weights, sometimes you worry that it could be a little throwaway. And so, how do you... You need to find a way that you decompose the problem, the preferences from the underlying models and so forth. The thing we're right now most both that's easiest to start with and we're excited about is having, a separate store for memory, where you have, for example, a memory sub-agent that's, working in the background, figuring out what are the important parts of the clinician's actions that we want to remember for the long term. And then you can also imagine, other things where in the — you have background jobs that are running that are collating these, memories similar to Sleep, of course and what other pattern, patterns products do as well. Learning over all these action, all the action data we have, again, note edits, the conversations they did and the actual transcripts.Evals: LFD, LLM Judges, and Clinical SafetyJacob [00:30:40]: What about evals? How in the world do you... It is such a complex product surface area. We would love to hear you riff on that and also how has that evolved? I'm sure you've gotten better at it, so any learnings along the way.Janie [00:30:50]: From an evals perspective, we, from day one when we build any new product or feature, we think about, what does good look like? And there are table stakes things like clinical safety but then you start to get deeper into what does good quality look like. And when you go into something like our core product, there's stuff like style and completeness and there's things like does this note become something that can be billable, which is very high stakes for a health system. We have a number of ways in which we get confidence for this. We have, internal in-house clinicians who do what we call an LFD process to give us our very first pass at is this or isn't this a good enough output, look at the effing data.Jacob [00:31:41]: LFD?Chai [00:31:42]: That's why I was smiling. I was “Is Janie going to mention what it stands for?”Jacob [00:31:46]: I was not... There's like a million acronyms.Jacob [00:31:48]: How am I supposed to know that I don't? So “Oh yeah, of course, an LFD.”Swyx [00:31:51]: I've never heard of LFDs.Chai [00:31:53]: It's a bridge for sure.Janie [00:31:55]: I got through three days and then I had to ask someone.Janie [00:31:58]: I thought it was just me that didn't knowJanie [00:32:01]: It's our internal process.Swyx [00:32:02]: But look at the data as a meme in ML, ‘cause you tend to not look at it. You just want to look at number go up.Chai [00:32:06]: Exactly.Swyx [00:32:07]: But yes.Janie [00:32:08]: But so, we make sure we look at the data and then as we think about all of the components of good output, we, one, create LLM judges across all of these and we make sure with annotated data and either internal or external evaluators, we feel like these judges are calibrated. And then depending on the stakes, we also work with in-house and third-party evaluators across all of these before we ship any big change. And the goal is, in terms of evolution, how do you go from this process taking months, down to weeks, down to days? Some of it is, a true science and ML problem. A lot of it's also just, hard operational work. Have you planned ahead in terms of what you need? Have you really optimized the capacity that you need across all of the different specialties you need? Have you gotten a really good sense of which third parties are great to work with for what use cases? This takes a lot of domain, expertise and, lots of mistakes and errors in figuring that out. And so as much of it is an ML problem, so much of it has also been operational gains that are hugely important, where domain-specific expertise is everything.Specialty-Level Evaluation and Progressive RolloutsJacob [00:33:23]: But it's funny, ‘cause I feel like people talk about healthcare like it's one giant market and the reality isJacob [00:33:26]: It's, dozens and dozens of sub-markets. And so it feels like in your evals you have to build that up across the board, probably.Swyx [00:33:34]: And is specialization the primary cardinality at... That's the word that comes to mind.Janie [00:33:40]: Sometimes, depending on the product or the use case. And so if we're making a note improvement or feature for a particular specialty, definitely but we have products that are for nurses. We have products that, are really aimed at making the document or the output a lot more billable. And so we'll want to work with coding teams and not necessary clinicians. And so likeJacob [00:34:05]: Coding meaning healthcare coding.Janie [00:34:06]: Yes. Yes.Jacob [00:34:07]: NotChai [00:34:07]: Yes. I see you.Swyx [00:34:07]: Other kinds.Janie [00:34:09]: But is this output proportional to the work that was delivered? Is there sufficient documentation to justify the amount that a health system may end up charging? And so, specialty sometimes but also domain, very different across all of the different products that we're working for. And building out that network is, not easy and is where a lot of our operational investments have gone into.Chai [00:34:35]: And I view a lot of analogies to self-driving cars here, where, part of it is we really want progressive rollout of features to test in the real world is this useful? Is this going to work? One big difference compared to past lives is before I'd build a product, maybe I'd alpha it and then I'd like GA it the next week, ‘cause I'm “Go, move fast, ship,” and whatnot. But the mentality is like you... I want to make contact with the reality as quick as possible but I want a progressive rollout. Because as much as I get as large of an offline eval set, I want the distribution of that to match real-life distribution. And over time, by rolling out early, similar to Waymo has a tagline, “The world's most experienced driver,” another thing that can, at least linearly increase for us is, both the size of our evaluation offline and online, that and it all feeds back.Janie [00:35:25]: Something that's been earned over time, speaking of evolution, is just the trust we've gotten with customers. Historically, a lot of these health systems, when they bring on new vendors, their release cycles are quarters, sometimes twice a year. We've gotten our customers onto monthly release cycles, which is pretty fast for health systems but what is more exciting over the last, call it, few quarters, has been, a subset of our customers have said, “We want to innovate with you. We trust you,” and we have a pretty, decent chunk of our customers who say, “We'll develop with you outside of these monthly release cycles. We have a higher tolerance. We know that the stakes are very high but we want to be the first ones using these products, giving you feedback.” And so for a pretty substantial set of our customers, we've been able to convince them to be able to ship, in this gradual way before GA. Something we talk about a lot internally is, trust is earned in drops, earned in buckets and so we still can't do what I used to do when I worked at Loom. We had 30 million users. I'd just be, rolling out experiments left and. The bar is still quite high for iterative rollout but because of the trust we've earned, we're able to learn at pretty high volume very quickly.Privacy, HIPAA, and De-IdentificationSwyx [00:36:45]: Your scale is still pretty huge.Swyx [00:36:47]: One thing I want to... We were going to go into scale? In a sec. One thing I wanted to call up, follow up on evals, which, again, just coming from a generalist engineer point of view, just thinking through what would people be scared of in doing this, the privacy and HIPAAJacob [00:37:00]: Elements of this. I have zero experience in that. What do you have to do? What is surprisingly not that bad?Chai [00:37:06]: So one thing that's really important here from a compliance perspective is very much that any of the data we use needs to be de-identified, any real-world data we use as a basis of online eval sets we're learning from. And so you have to — And there's, very clear, government guidelines, what counts as PHI. And so we've even have built models that can take, for example, a clinical transcript and remove all the key PHI indicators and so you have a scrubbed/de-identified version. And then once you... And so one thing that's important is first you've got to get confidence in that model in the first place? And prove that out. Because, now you have, multiple probabilistic systems on top of each other.Chai [00:37:46]: But once you have that, then you can train on it use it for evaluation and so forth, provided one of the cool things also that you can do from a business side is the right data contracting as well with your partners.Jacob [00:37:57]: Is the anonymization one way? Once it's done, you cannot undo it? Or is there someoneChai [00:38:01]: YesJacob [00:38:02]: Who holds the master key that can... Yeah, okay. So it's one way.Chai [00:38:05]: It's one way. Yeah.Jacob [00:38:06]: That's how it works. I just wanted to... Because, there's a lot of this, learning from feedback and everything that, you would want to debug more but you can't because you just physically don't allow yourself to.Janie [00:38:17]: Some of it's also written in our customer contracts in terms of who can or can't access PHI data, how long do we retain it,Jacob [00:38:27]: Very goodJanie [00:38:27]: Before it gets de-identified. And so we have a pretty high bar for who can access that PHI data, just to make sure that we always respect our customer data and privacy. But that's something that we partner with our customers on too, to make sure that as we want full, as close to precision as possible in that qualityJanie [00:38:48]: We can still use it.Jacob [00:38:50]: But it'll be fascinating to see how that space evolves? Because you think about, I used to work at a company that, did a lot of healthcare data in the cancer space and if you asked, the average cancer patient, “Hey, do you want people, do you want other patients to be able to learn-”Chai [00:39:03]: Take it.Jacob [00:39:03]: “... Learn from your experience?”Chai [00:39:04]: Take it all.Jacob [00:39:05]: They're “Please.”Jacob [00:39:06]: “I'd love, nothing more than for other people to be able to learn fromJacob [00:39:10]: The experience that I had.” And so in the past it was a lot harder to do that learning. But with this technology, that might really be practical and so it'll be fascinating to see how that continues to evolve.Chai [00:39:21]: There's so much in our data set of 100 million conversations.Chai [00:39:26]: You can imagine things like insights that you can give to the clinician. How could you, oh, how could you have reacted to this? In coaching or insights around, which treatments are effective or, like... Because you have this, again, this data source that was never captured before but that's, where, intuition or experience is created from, going back to this idea that the conversation is the agent of truth.Operating at Scale: Reliability, Cost, and Token EfficiencyJacob [00:39:46]: Back to the 100 million conversations, I feel like you have this insane scale that maybe only a few other AI app companies have and everyone else dreams of. So not everyone has had to confront this yet but maybe just talk about some of the challenges of operating at that scale and what, our listeners have to look forward to if they ever get to this level of scale.Chai [00:40:05]: At large and larger in scale, so of course there's a general, infrastructure reliability. When you... In any given startup, you're building the plane while it's flying. So there's some notion of that. But what gets interesting on the AI and ML side for sure is this, as you get at more and more scale, so one, you have the data to first and foremost do this. But, you start thinking about costs or infrastructure in a whole different way at scale versus, a prototype.Chai [00:40:34]: You can use the most expensive model, you can burn as many tokens as you want but when you're doing 100 million conversationsJacob [00:40:41]: Token max on leaderboards are less upsetting than that context.Chai [00:40:45]: . When you're doing that and so that comes for we have the data and we also have the team that's able to post-train based on this and you can optimize for efficiency, especially in areas where you believe that maybe a lot of the quality headroom is less so and you don't expect the other off-the-shelf models to go that way, such that you want to do, efficiency maximization, in terms of compute and tokens.Jacob [00:41:08]: I feel like you guys live in the future in some way where most use cases today are really just in use case discovery mode, where it's “God, I really hope I can find something that can get to scale,” and so you're always going to use the most powerful model. And then the few things that do get to this level of scale, you start to do those optimizations.Chai [00:41:22]: It's a natural trajectory where it's like zero-to-one, we're not talking about any of these optimizations.Chai [00:41:26]: But when maybe we're in the one-to-100 or so forth, then we're in optimization mode and, what works out really well is you've got all this data from zero-to-one that lets you do this.What Comes Next: The Conversation as the Shared Healthcare PlatformJacob [00:41:36]: That's fascinating. I feel like one thing that's so interesting about the Abridge footprint is that you're in the doctor-patient visit in real-time. I always like to say, there's like probably 50 years' worth of product you could build on top of that. What gets each of you, I don't know, what are you most excited about building, either in the short term or medium term or even, long down the line?Janie [00:41:53]: Something that I get really excited about is that the same conversation can serve so many stakeholders. If you think about the conversation, a doctor needs to know what is the documentation, how do I make sure that this fully represent the care I gave? A patient needs to know, “What the heck just happened? This was really overwhelming. What are my next steps?” A payer needs to know, was this the proper and appropriate care given? A pharma company might want to know why isn't this drug being properly used or is there a good candidate for this clinical trial that I'm about to run? And where I get excited is that our product and our platform and our infrastructure can be the same product across all of those things and start to what's today, separate, very expensive, complex systems that serve each one of these stakeholders in very different ways, start to collapse all of that into a singular platform that enables not just more efficiency across the board but also better outcomes for everyone. And, all of us experience healthcare in probably very painful ways and knowing that there is a world in which we can simplify a lot is really exciting to me and it all starts with the conversation.Chai [00:43:15]: It's interesting. Of it very similar to going back to the KPIs that any AI product cares about. How do you increase quality of care? How do you reduce latency to care? And how do you reduce costs? Which is a huge, in healthcareJacob [00:43:28]: They call it the triple aim in healthcare.Chai [00:43:30]: But very similar to building AI products and the thing that really excites me is when we talk about that latency piece, we talked about one example earlier of prior authorization, can you reduce the latency to care? But you can imagine so much more. Oh, as soon as the lab value gets updated, do you have like a background agent that, kicks off and uses all the context to be “Oh, hey, the patient should do this next,” for example. And of flagging that to the clinician who's always in the loop but reducing that latency, to care. And then you can imagine this is much further down the road but it's like even connecting that to the direct patient and the consumer. And so how can you, how can you build a bridge to all of these things?EHR Partnerships and the Clinical Intelligence LayerJacob [00:44:10]: Very cool. The connections piece is just an ever-growing thing. And one of the key partners is the EHR and I wonder what that relationship is like. Will they, look at this as, something that is valuable enough that they want to own someday?Janie [00:44:29]: Our partnerships with the EHR is, we know that we have to be extremely close partners with all the EHRs who we partner with. Being able to not only pull and push all of the data into the right places is, not only table stakes, if we can't do that, health systems don't want to use us. The second and the reality of today is clinicians spend a lot of their days in the EHR. So much of what allowed us to win in the largest health systems was pretty direct and, very close partnerships with some of the largest electronic health records that allowed us to pull and push data with APIs that weren't ready out of the box. And clinicians want to save clicks. Anytime we introduce a new product that, adds two clicks for them in their day, they're “We're not going to use it.”Janie [00:45:21]: They have 15-minute back-to-back appointments with their patients. They're spending, hours during pajama time doing documentation. Every second and every minute counts and so we really think about being deeply integrated into the EHR as also table stakes to getting real usage and adoption. And anything that we build or introduce, we really talk about earn the right internally a lot, which is we have to provide so much value or save so much time that people will use us. But those are the two things that are close to us, is we know that the product won't be used unless it is deeply interoperable.Chai [00:46:01]: And strategically, to your point, it's like what does EHR want to own versus us? EHRs are really focused on the clinical workflows and so forth but some of the things that we're talking about here, I do these traditionally are outside of the domain where it's oh, connecting pairs and providers together with provider policies or the clinical trial matching, as Janie brought up. And so these are, entirely — we position ourselves as building this entirely new intelligence, clinical intelligence layer across, again, providers, pharma and, payers.Chai [00:46:33]: And so that's a it's a whole different ballgame that we try to playChai [00:46:36]: In combination with them.Jacob [00:46:37]: But it's like a different layer of scope.Healthcare AI Regulation, Technical Depth, and What Changed Their MindsJacob [00:46:39]: I'm curious, you are both relatively newcomers to healthcare. People have these, there's lots of futuristic healthcare AI takes of “Oh, everything will look different.”, now that you've been in healthcare for a bit, you live at the edge of AI, what have you, changed your mind on around this, as you think about what healthcare looks like in ten, 20 years? Any updates to your mental model from the time being close to the problems?Chai [00:47:02]: One thing that IChai [00:47:04]: Was hesitant about before and it's a common thing when I'm trying to recruit engineers that people ask me around, is definitely oh, healthcare, heavily regulated space. And it is, rightfully so. You want to keep, the patients at the end of the day safe. But one of the interesting things that, is a that surprised me how much it is coming to the company is there's a lot of really favorable regulatory tailwinds as well. Where you think about, government really wants interoperability between all these systems that we talked about and so agents can access this information. The government just in January, the FDA released updated guidance on clinical decision support, what I work on in such a way that they used to have guidance from like 2022 that required you to have, mention all these options and do all these other things but it's a very forward and forward-looking way. And so for me, what's been really cool to work on is this, there's this very special moment both in AI in general, we all know that but there's a special moment also regulatory in healthcare as well.Janie [00:48:05]: One thing I would call out is for the very reasons things are higher stakes or, potentially considered more difficult in healthcare, it's where some of the hardest AI problems will get solved first, just because the bar is so high. When I first joined, I was “Oh, this is where we'll be on the tail end of where, all of the AI innovation will be able to be applied.” But when you think about, zero error evals or multi-step workflows that have really low tolerance, a lot of the innovation will happen here just because we have to or else we can't ship.Jacob [00:48:42]: ‘Cause like in other domains, you'd much rather just solve the 80%-is-good-enough problems firstJanie [00:48:46]: 80/20 doesn't work hereChai [00:48:48]: And building off that, traditionally, there was a bit of stigma that, oh, healthcare companies are not that interesting from a technical perspective or I've seen that or faced that myself. But these are really hard and fun problems from a pure technical perspective beyond just the impact. How do you bring the latency of this thing down and make it really high-quality?Reducing Latency: Clinical Workflows, Agents, and Implementation RealityJacob [00:49:07]: How do you bring the latency of things down?Chai [00:49:10]: Yeah. Yeah. Yeah. So okay, let's answer the latency question. And maybe hopefully not too redundant with some of the things I've said earlier but some part of it is with any latency, you have to like what is, what is really your bottleneck. In a lot of workflows, it's sometimes it's the model itself. And so that's where like our data flywheel, our post-training team and so forth come in so that can you make the models far more efficient. So that's one aspect of latency. But there's whole other aspects of latency where it's okay, on top of that, if you use a constellation of different models, can you use — can you first use like a — it's like thinking fast and slow. Can you use a cheap, fast model that triages and hands it off to a larger model where you get more intelligence and so forth and so all theseChai [00:49:56]: Clever tricks to make it work.Chai [00:49:58]: And by the way, we are totally — we also realize that the parameter frontier is changing and so these tricks will — may not get us to where we want to be in five years but we need to if we want to build a useful product right now.Jacob [00:50:11]: Should we go to the quick-fire or you want to ask more about Abridge? We can stuff everything that's not Abridge into the quick-fireSwyx [00:50:16]: I don't mind. I was — I feel like Janie was on the topic of more long tail stuff, which isSwyx [00:50:21]: Not the eighty/twenty thing and that really matters. And I'll —, if you have any tips or cool stories or just general approaches that have worked for you that's interesting to dig into.Janie [00:50:32]: One of them is even just how we staff our teams looks different than a traditional software engineering team, I'd say.Swyx [00:50:40]: Let's go.Clinician Scientists, Edge Cases, and Evals at ScaleJanie [00:50:41]: We have a bunch of folks with different roles who are clinicians and so we have this role called the clinician scientist and I heard one of our leaders refer to them as mutants recently. But they are people who've had clinical backgrounds, so MDs typically, who are also deeply technical, somewhere, on the spectrum of like a full stack engineer all the way to like extremely scrappy prompter. But having each of these people embedded within our teams instantly raises the bar for everything that we build because not only are they determining, is this product clinically useful but they're deeply embedded in our whole evals process. And so when we talk about LFDs, when we talk about what is our actual evaluation criteria, you don't want Chai or me creating what those are because we don't have clinical background. But is probably unique to Abridge but has been game changing. And when you think about where the puck is going, you have people build with clinical backgrounds who are technical and where AI tools are going, they just becomeJanie [00:51:53]: More and more, critical and like the killers of the team. And so that's one. And then the second is just the scale at which we do evals to catch that long tail up front before anything ever gets into production is something that we've pretty much like really started to fine-tune, both from a scale but when do we know we need to get several hundred versus several thousand offline responses, what helps us make that quick decision and make this less of an art and as much of a science as possible. But that's also been something we've had to tune over time.Swyx [00:52:27]: And you have partners who opted in to give you those evals.Janie [00:52:31]: So we work either internally or with third-party for offline evals and then we have customers who also agree to give us, whether it's like thumbs up, thumbs down to like choose this or that, a lot of data to get us to what is as close to fully confident as possible.Swyx [00:52:51]: The term that comes to mind isSwyx [00:52:53]: Like active learning on things where you're weak. I feel like it's a lost artSwyx [00:52:58]: Is a lot of the polish that comes into doing something like this.Janie [00:53:02]: Really.Chai [00:53:03]: Hundred percent.Lessons from Glean: Technical Foundations and AI App InfrastructureJacob [00:53:04]: Maybe, on a totally unrelated note, Chai, you had a very, storied run at Glean b

Hour 4 opens with on-air studio scramble as the show prepares for major Supreme Court rulings expected later in the morning, with discussion centered on high-stakes cases still pending and the potential national impact of upcoming decisions. Attention then shifts to Griff Jenkins reporting from a National Law Enforcement Officers Day event on Capitol Hill, where he notes the absence of any Democratic lawmakers in attendance, fueling debate over growing political divisions around law enforcement support. The hour then pivots into controversy surrounding reports that CIA officials accessed or transferred sensitive files from the Office of the Director of National Intelligence, including materials tied to JFK assassination investigations and MKUltra programs, prompting renewed scrutiny and calls for congressional oversight. The segment ties together broader themes of institutional trust, political polarization, and escalating tensions between Washington agencies and elected officials. Hashtags: #SupremeCourt #CIA #MKUltra #JFKFiles #GriffJenkins #LawEnforcement #CapitolHill #Politics #WashingtonDC #BreakingNews

Adam Creeger is the CTO of Slate and creator of iLoom (pronounced “il-LOOM”). His leadership experience at Meta, Greenhouse, and Frame.io not only informs Slate's transformation into an AI-native organization, but also shapes the way AI influences product strategy, engineering workflows, and operational models. Throughout his conversation with Sean and Dan, Adam argues that becoming AI native is not about layering AI features onto existing products. Instead, it requires companies to rethink how software is designed, built, and operated – from the ground up. His perspective offers a practical framework for product leaders navigating AI-driven transformation. Here's what else we learned: ‘AI Native' Requires Organizational Reinvention AI native organizations are willing to rethink every layer of their business, Adam says. Rather than adding AI features superficially, AI native organizations redesign workflows, team structures, and customer experiences around AI capabilities. He emphasized that AI transformation changes not only products, but also how people contribute inside organizations. “To be AI native requires this deep exercise in re-imagination and not just imagination,” Adam continues. “In an AI native company – from the day-to-day operations to the ‘who does what' – the roles and the owners of things are going to look very different.” AI is expanding participation across teams, enabling designers, support teams, and non-engineers to contribute directly to product delivery. That shift signals a major change for modern software organizations. AI and the Future of the Software Development Life Cycle (SDLC) Our conversation then turned to an exploration of how AI is already changing the traditional software development lifecycle. Years ago, Agile development emerged because humans had historically struggled to fully reason through complex systems before implementation. “I've realized that Agile was really a mitigation of a few things, mostly that we humans are limited in our abilities to reason through abstract concepts,” Adam says. “So when we thought about a software project, we didn't have the ability to see around corners and understand the problems we'd face – until it was real, until you really started playing with it. Turns out that many of those challenges are very solvable by AI, allowing us to go much deeper into the problem space without ever writing a line of code. In addition, AI-assisted planning allows teams to revisit some waterfall-style thinking, but with dramatically faster iteration and validation cycles. Product Managers’ New Role: Communicate Context Importantly, AI is actually elevating the role of product managers, Adam offers. Rather than acting primarily as tactical decision-makers, product leaders can (and should) focus on providing context that enables teams to make informed decisions independently. “More than ever, the product manager has become a role about providing context,” he adds. “PMs should be elevated to a much more strategic role, understanding the long-term vision and helping to translate that to engineers.” Adam also feels that PMs should be using AI to communicate ideas about the product vision much more effectively. That evolution creates a faster and more collaborative product environment. Teams can evaluate real implementations earlier, gather customer feedback sooner, and align around outcomes instead of specifications alone. [05:54] What it means to be ‘AI native’. Conceptually, it’s same as digital native from when the internet was born many years ago. In the abstract sense, I see AI native being about the folks and the companies that are either just starting in the age of AI where everything they do is shaped by the existence of AI and their ability to use AI. [15:08] Is waterfall making a comeback? Oh man, this is one of my favorite topics. Growing up in the industry, waterfall was always like the evil thing. But with AI-assisted coding or agentic coding, you can go really deep, create a much bigger scope, and deliver it much more quickly…and it resembles more of a waterfall mentality. [21:51] The PM’s primary role: providing context. The product manager more than ever has become a role about providing context. The most powerful thing PMs can do in an organization is provide context to other people. [25:49] Exploring Adam’s iloom tool, and how it can help. Hear a quick story from Adam about how he used his iloom tool to create — and demo — a new product feature during a call with his customer success team. [28:47] Swarms. What are they, and how do they work? A swarm is a number of AI agents working together in a very collaborative way with the potential of real-time communication between them. [35:03] Avoiding ‘AI slop’ to defend and elevate a brand’s quality bar. Slate is creating a tool that makes it very difficult to create AI slop. This is a valuable proposition to brands that care deeply about what gets produced in their name. The post 187 / AI Native: Reimagining Product Roles and Development Cycles, with Adam Creeger appeared first on ITX Corp..

Big careers aren't built on titles, they're built on decisions. This week on I Am Home, Jeff Cohen - Chairman of six Berkshire Hathaway companies and CEO of three, including Fruit of the Loom, Star Furniture, and Larson-Juhl - joins the conversation to unpack a career that spans some of the most influential companies in business. He shares the moments that shaped his leadership style, the realities of running and transforming businesses, as well as the tradeoffs that come with operating at the highest level. It's a thoughtful, behind-the-scenes look at what it means to build, lead and evolve over time. Resources: nfm.com/podcast

Nick agreed to personally set up your Orgo in a 15 min call: https://startup-ideas-pod.link/orgo_ai I sit down with Nick from Orgo to break down exactly how to run a one-person AI agent business that can realistically clear a few million dollars a year. Nick walks through the offer, the verticals worth chasing, the full software stack, and the live setup of an agent that manages other agents. We focus on tactics over theory, with specific tools, pricing, and the playbook for landing customers as a solopreneur. By the end, anyone with solid AI fluency will have a clear path from offer design to fulfillment. Timestamps 00:00 – Intro 02:54 – Designing the AI Agent Business Offer 06:38– Selling an AI Employee, Not an Agent 07:26 – Industries to Target (and Two to Avoid) 14:54 – Content Is Overpowered and How to Get Customers 17:51 – The Customer-Facing Tool Stack 20:49 – Building Agents Stack 25:51 – Model Picks: GPT 5.5, GLM 5.1, Kimmy, Opus 4.7 27:08 – Nick's Stack 28:14 – Why Obsidian Is the Second Brain Layer 30:22 – Live Walkthrough: Spinning Up a Cloud Computer in Orgo 33:53 – Cloud Computers vs. Mac Minis 38:37 – Building Agents and Structuring Workspaces for Customers 43:56 – Watchdogs, Observability, and Reliability 45:28 – Closing Thoughts on the Solopreneur Era Key Points Sell unlimited agents, unlimited usage, and unlimited support to remove friction; most customers actually use one to three agents. Avoid healthcare and finance to start; focus on legacy verticals like marketing, law, insurance, manufacturing, wholesale, and real estate. OpenClaw agents go for around 5K a month; Hermes agents can go for 10K a month. The full stack: Granola, Trello, Loom, Superhuman, Asana, Codex, Hermes, Orgo, Composio, Agent Mail, and Obsidian. GPT 5.5 is the recommended default model for tool calling; GLM 5.1 and Kimmy work for lighter tasks; Opus 4.7 fits long-horizon coding. Use agents to set up other agents — pair Cloud Code or Codex with MCPs like Perplexity, Context7, and X MCP for live docs. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND NICK ON SOCIAL Youtube: https://www.youtube.com/@nickvasiles Instagram: https://www.instagram.com/nickvasilescu/ Personal Website: https://www.nickvasilescu.com/

Mea Culpawelcomes back Rick Wilson, longtime Republican political strategist, infamous negative ad-maker, and commentator. Since 2015, he's been a leading conservative critic of Donald Trump. His regular column with The Daily Beast is a hilarious and spot-on must-read in the political community. He is also a founding member of the Lincoln Project. Rick's been published in The Washington Post, Politico, The Hill, The London Spectator, Rolling Stone, The New York Daily News, USA Today, The Bulwark and beyond and he's constantly called upon for sharp political insights on the national news networks, including CNN and MSNBC. He's also a fan favorite on Real Time with Bill Maher. A 30-year veteran of politics, Rick got his start in the 1988 Presidential campaign of George Herbert Walker Bush. Rick is also a best-selling author, his latest book is “Running Against the Devil” and his #1 New York Times, best-seller, “Everything Trump Touches Dies” which quintessentially defined the Trump and Michael and Rick dig deep into Clarence Thomas, Fox News, and all of Trump's pending cases and DeSantis.

How can upgrading your verbs transform flat writing into vivid, page-turning prose? Why do so many writing problems turn out to be verb problems — and how can you fix yours? Sarah Kaufman explores the art of the verb and shares practical tips for making your writing stronger, clearer, and more alive. In the intro, writing as a caregiver and grief [Stark Reflections; The Creative Penn episode]; Beyond Bookshops — Bulk Sales, Gifting and Alternative Distribution [Self-Publishing Advice]; list of money books; London walk along SouthBank; Bones of the Deep: AI-Assisted Artisan Author webinars. Today's show is sponsored by ProWritingAid, writing and editing software that goes way beyond just grammar and typo checking. With its detailed reports on how to improve your writing and integration with writing software, ProWritingAid will help you improve your book before you send it to an editor, agent or publisher. Check it out for free or get 15% off the premium edition at www.ProWritingAid.com/joanna This show is also supported by my Patrons. Join my Community at Patreon.com/thecreativepenn Sarah Kaufman is a Pulitzer Prize–winning critic, an award-winning author, and a writing teacher. Her latest book is Verb Your Enthusiasm: How to Master the Art of the Verb and Transform Your Writing. You can listen above or on your favorite podcast app or read the notes and links below. Here are the highlights and the full transcript is below. Show Notes Why verbs are the most versatile and underrated tool in a writer's toolkit How to replace flat, explanatory sentences with vivid, action-driven prose The power of physical and metaphorical verbs to show emotion instead of telling it When passive voice works, and when it's hiding something Balancing beautiful language with the demands of storytelling and deadlines How to broaden your writing expertise into a sustainable portfolio career You can find Sarah at SarahLKaufman.com. Transcript of the interview with Sarah Kaufman Jo: Sarah Kaufman is a Pulitzer Prize–winning critic, an award-winning author, and a writing teacher. Her latest book is Verb Your Enthusiasm: How to Master the Art of the Verb and Transform Your Writing. Welcome to the show, Sarah. Sarah: Thank you so much. I'm delighted to be with you. Jo: This is such a great topic, but first up— Tell us a bit more about you and how you got into writing. Sarah: I got into writing in a backwards way, I guess. The romantic, wonderful thing about writing is the freedom that it gives you, right? That's what we all think about—this freedom to address the world. Then the practical, wonderful thing about writing is developing a focal point, which I had to do in order to write in the first place. I'll explain a little bit about that. I became a dance critic, which is what I did at the Washington Post for 27 years, to have something to write about. That was necessary because, though I've always known that I wanted to be a writer ever since earliest childhood, I just didn't really find things to write about when it came time to actually try to make a living at it. As I was approaching leaving college as an English major, I was getting very anxious about what I was actually going to do, and I didn't have this burning desire to write about any certain thing. I happened to be working as a full-time secretary at a ballet school because I had been a ballet nerd all through my youth. I knew quite a bit about doing ballet, about the steps and about the lingo, so I was a suitable candidate to work at a ballet school. I was learning so much from the teachers there—who had all been professional dancers—about the aesthetics of ballet and how you shape the steps into art and into a performance. I was getting more and more interested in dance. One day the director took me out to lunch and she said, “You should write about dance.” I had seriously never considered that before, but she knew that I was an English major, that I wanted to write. She said, “Look, you know so much,” and she really encouraged me. So I said, “Well, okay, I'll give it a go,” because I had been reading dance criticism. I just started picking it apart and seeing how critics put their reviews together, called up a local paper, took on some freelance assignments, and did a lot of freelancing for years and eventually landed at the Washington Post. So the point I want to make is that I had that thing to write about. Now I had a focal point, and my books grew out of that. The first book I wrote is The Art of Grace: On Moving Well Through Life. That was an exploration of aspects of grace stemming from physical grace, which I knew about from dancers, and looking at connections there with social grace and spiritual grace. Then this verbs book likewise grew out of my work as a dance writer because my goal in writing about dance was to capture the experience of it. I didn't want to be a scholarly type of critic, though I do love that kind of criticism and I read it and learn so much from it, but I knew that was not going to be my style. I wanted more to primarily recreate the experience for the reader, as well as then coming in with analysis of it. I was just so fascinated by the look and the feel of what I was seeing on the stage. I wanted to be able to share that with the reader. So I had to lean on verbs to capture the action, and people occasionally would say, “Oh, you're so good with verbs, Sarah,” which I thought was kind of interesting. It's like, oh, so this is a strength I had developed. I didn't really realise it. Then that, coupled with my teaching experience, is what led me to think I have some things to talk about regarding verbs. I'd like to share with the world because, as a teacher, I often see that writing issues my students have are actually verb issues. They get into a corner with a lot of explanation or clauses on top of clauses, and they get lost. Where is the point that you want to make here? What is the meaning? What is it you want me to take away from your work? Well, if we pare that back and look at the verbs and try to get some direction in the sentences, that often brings clarity. Suddenly the student will say, “I was thinking more about adjectives and nouns. I didn't realise that verbs were really something to focus on.” I thought that would be an interesting challenge to bring that out. Jo: It's so fascinating. I love how your career has emerged and that you've leaned into different things. It has a kind of dance to it itself. We're going to come back to your career, but let's start with that, because you mentioned that with many of your students you are reading their work and you think, “Oh, we can fix this with some verbs.” Let's get into that because you talk about weeding and this verb-first editing process. Most of the listeners will have some kind of writing already—either they've got a lot of books or they've got a draft in progress. This is the kind of thing we struggle with: how do we make our work stronger? Talk about why you are so obsessed with verbs some tips for making our work stronger. Sarah: Yes, I am obsessed with verbs. I will cop to that. They're so interesting and I felt like they were a little underrated as a writing tool. Verbs, as we learned in school, drive your sentence forward. They're the engine. Really, I feel like they are the secret soul of language, because they're so versatile, they're so essential. First of all, they hold it all together. They're the only part of speech that in itself is a full sentence. You can have a full sentence that's a verb. “Watch.” “Look.” “Continue.” You could go on and on. That is a full grammatical sentence. You can't do that with any other part of speech. They're so essential. The word “verb” itself comes from the Latin verbum, which means “a word.” So verbs became that name for all words. Our literary ancestors understood this—that they're really the beginning and the end as far as words go. They can add to your work when you start thinking about verbs in this way, and you start thinking about how can I elevate my writing—well, verbs are very efficient and very evocative. They can add not only clarity to your work, but a kind of elegance. They can say so much in such a little amount of space. For example, say you have something like this: “The cook was facing the dinner rush, and so she decided to put together something quick and easy so no one would know how nervous and unprepared she was.” In that sentence, I'm doing a lot of explaining and describing. I'm just explaining to you the situation, but I haven't really brought it to life much. A better way to do it might be something like this—and you can see it comes a little bit more active: “The dinner rush pressed upon her. To hide her nerves, she whisked eggs and milk into omelettes, shredded parsley with her bare hands and flung it all onto plates like Jackson Pollock splashing his canvas.” I show you what her nerves and the pressure resulted in. I show that manifesting. Or you could even shorten it and just say: “Dinner rush loomed. She whisked and whipped, chopped and dripped and masked her nerves with glistening omelettes.” There are stylistic differences there, but it's just to give an example of how you can take something that, on the face of it, sure, it makes sense—it's perfectly fine as a sentence—but it just lies there. It's flat. Maybe it's not very exciting. It doesn't really move the story forward. You can bring it to life by showing us. You show us with the action. Jo: You haven't really specifically said what a verb is in that sentence you just had around “whisked” and all of those things. Those sentences were actually quite different in a lot of the different words you used. You didn't just swap out for stronger verbs. Could you just point out what the verbs were, in case people are confused about which words are which? Sarah: Right. Great. In the first, inferior example I have: “The cook was facing the dinner rush.” So then I amended it to: “The dinner rush pressed upon her.” I'm giving the dinner rush itself a verb—”press.” It weighed on her, it pressed on her. Also, in the third example—”the dinner rush loomed”—so that's even shorter. “Loom” is a wonderful verb. I love it because it conveys a sense of threat. That's what I mean by verbs being so efficient and evocative in one word. “A storm loomed.” “The dinner rush loomed.” You convey the emotion around the whole event. “To hide her nerves, she whisked eggs and milk into omelettes, shredded parsley.” So “hide”—she's hiding her nerves rather than just saying she felt nervous. You give it a little bit more action, you give her a little bit more character by saying she's doing this to hide her nerves. Then whisking the eggs, shredding the parsley, flinging it onto plates—that shows how she's being creative and surmounting this problem, right? Instead of simply describing—”So she decided to use her expertise and create a nice dinner”—you show that in motion with things like whisking and shredding and flinging it onto plates. That's an example of how you can slide in upgraded verbs to lend a sense of energy and life. Jo: I think this idea of motion is so great, and you tie this in a lot to your work. You've written a lot about physical action, and in the book there is a chapter on physical action. I think this is so important because many authors will say, “Use the word ‘said'” without thinking about dialogue within a pattern of action. Your chef there could say something as she flung the parsley on the plate, rather than “the chef said this.” Get moving as she flung the stuff onto the plate. The action verbs are so important. Could you talk a bit more about [action verbs] and the physical action side of it? Sarah: Yes, and that's so right. When you have a scene really rolling, you don't need to do so much explaining about the way a person says something with those dialogue tags. It's very interesting. I feel like words are alive—they're living, breathing things—and the more that we let them come to life on the page, the more you can draw your reader into the story. The reader gets a sense of that life and wants to come into the story with you. You've really created a scene that your reader feels immersed in. And that's so exciting as a reader to discover. Writing about movement is part of that. Of course writing is very vast—it's hard to say, “Well, you should always write about movement.” That would be silly. If we think about movement and action and action verbs as being effective not only for the actions that we see around us, but for inner actions—the subtle feelings, thinking, non-action, but internally what's going on—that's also space for effective verbs. For churning emotions, for metaphors about fright and what that feels like in the body. Or despair. Or regret. I have a lot of examples of that in the book. It's another beautiful use of verbs where, instead of explaining what someone is feeling, you can show it through metaphorical verbs and actual physical changes—things roiling inside the body. Jo: For example, someone in their draft has “she was afraid”— How could they make that much stronger and use a lot of those things you were just talking about? Sarah: That's an excellent question. Instead of “she was afraid,” you might say something like: “She felt her chest fill with ice, freezing her lungs and choking her breath, and her heart bashed around as if to tear itself from her body.” We could get very dramatic about it, but you can play with that. What I like to encourage readers to do is open their minds and open their imaginations. When you have a pretty standard phrase like “she was afraid” or “she felt too frightened to move”—well, put yourself in that position. What does that feel like? What does that really feel like inside when you're too frightened to move? Is it an icy feeling or is it a burning? Is it a numbness? And what verbs might help with that? Is it thrashing? Is it raging? Is it paralysing? How can that type of expressiveness fill in the picture and make it palpable to the reader—what it's like to be in the room with this person? Jo: Do you recommend using a thesaurus? I try to do this myself, and I often use Power Thesaurus, which I just find so useful, because as writers, when we are writing novels or books in a similar genre, we often reach for the same words. Are you a big thesaurus user? Sarah: I am a huge thesaurus user. I have a stack of actual book-type thesauri, but I do like, as you mentioned, Power Thesaurus. I like OneLook, which is an interesting resource. I think it's OneLook.com and you can go in the other way—you can use it as a thesaurus, but you can also use it to find one verb that combines a couple of words. Like “walk clumsily,” for example. You could put that into OneLook and it would come up with lists and lists. And among them might be “hobble” and “limp” and other words to say what a weak verb plus an adverb can say. Online resources are wonderful. I like Merriam-Webster.com—that's what I rely on a lot. Cambridge too. A thesaurus is wonderful. Now, the caution with the thesaurus, however, is that I would like to urge people to be mindful about just swapping in one word for another, or one verb for another, because even though they may appear in the same groupings, there are going to be subtle differences among them. I find it fascinating to really investigate the subtle difference between, say, “limp” and “hobble” and “stumble.” Those all mean slightly different things. So the finishing tip is just to make sure the word you choose is going to be right for the context. Jo: And also perhaps the audience. I mean, you are a Pulitzer Prize–winning critic, which is amazing, and you were writing for an audience who wanted dance pieces. The audience for dancing in terms of the words you would use—I'm not really into it myself, but I would know the word “pirouette.” I imagine there's a ton of words that you would know and use in your writing that wouldn't be so relevant for a wider audience. So we have to think about the audience as well. Sarah: Yes, absolutely. We want to be very thoughtful in our choice of words. If you distilled my book down to one single message, it is to think carefully. Not in the first draft, perhaps, and certainly not when we're speaking, because we speak so spontaneously. But in writing, where you put your thoughts down and then—hopefully, if you're not under too much deadline pressure—you can come back, give it another look, shape it, refine it, and really make sure that you've chosen your words with care. I feel like that's really what writing is all about—communicating one mind to another through this magnificent medium of language. Language is intentional, and having that intention in mind about what you want to share and what you want to communicate and how you want your readers to approach your work—well, that's up to you. That's the freedom I hope to be able to present to people who check out my book: here are some ways, here are some suggestions, here are some techniques and tips for issues that can arise. Really, once you've taken these in, I hope to fire your imagination and inspire you with being able to communicate what it is that you really have inside that you want to share. Jo: I think it is a book for falling in love with the joy of words again. You did mention deadlines, though, and the pressure. Especially for those of us who write genre fiction series, which is a lot of people listening, sometimes we might feel that we don't have the time for that. Do our readers appreciate it, or do they want story first? Sometimes is it too much? Where do you come down on balancing getting story over words? How long can we spend on finding beautiful words when we are writing another 70,000-word book? Sarah: I think that's an excellent point. I think story comes first. That's probably what first drives you to your desk—telling a story. Although it may not. The realities of writing are so vast and unlimited that it's very hard to come out with rules, and I don't write about rules. I really want to give suggestions and examples and insights, but I do think that story is absolutely tops. And that's the power of verbs, in fact. They can help us tell the stories with clarity and with efficiency. I do want to make sure that I'm being clear. I'm not advocating that before you ever sit down and write, or you write one sentence, you then go back and check every single word, because that wouldn't make any sense at all. The idea is to free yourself, free your imagination. These are ways to open your imagination up that maybe you haven't thought about before. But storytelling is primary, and the way that you tell it is going to be individual to every writer. It's useful to bear in mind that there are a lot of avenues one can take in terms of creating a scene or building a character and even evoking the landscape and the atmosphere, and we can look at verbs to help us do that. Jo: One of the biggest problems, I think, especially for new writers, is the passive voice versus more active voice. Can you give some examples of passive voice? Often in editing we're told to get rid of passive voice, but of course you do need it sometimes. Sarah: Yes. There's understandably a lot of confusion about passive voice. Just to have a tiny tidbit of grammar nerdery here: the voice of a verb refers to a very specific construction. It doesn't simply mean that the writer is expressing something in a boring way or taking on a dull subject. The voice of the verb tells you how it relates to the subject of the sentence. When the subject does the action—when it's doing the verb—then you have a verb in the active voice. But when the subject of the sentence is receiving the action, then it needs a verb in the passive voice. Here's an example. If I said, “Hey, Jo, guess what? My grandmother walked on the moon.” That's active voice. “My grandmother walked on the moon”—it's interesting, right? But if I said, “Hey, Jo, guess what? The moon was walked on.” You might be left thinking, “What? What am I supposed to take away from that? Is there more to the story?” “The moon was walked on”—well, that's the passive voice construction. There's no subject who did the walking. I haven't told you, and yet the subject was actually pretty important. My grandmother was the one who walked on the moon. So that's the frustration that often comes when we read the passive voice. We don't know the full story, and we might suspect: are they hiding something? Do they not really know who did the thing? It brings up a lot of questions. Especially in official situations. The classic example is “mistakes were made.” Officials love to say that because it puts nobody on the hook. Nobody is responsible. “Mistakes were made.” Well, who were they made by? They're not telling us. I heard this just recently, by one of the representatives here. This phrase is still being used: “Mistakes were made.” I think most people understand there's a bit of obfuscation. There is something being hidden. Now, there are times when the passive voice is perfectly fine. It's not necessary to say who did the action. If you say, “Joe Blow was arrested and charged with murder,” you pretty much have the full thing there. You don't need to say, “The police arrested him. The prosecutor filed the paperwork.” It's kind of assumed. If you just want to get to the point—he was arrested and charged with murder—that's sufficient. Maybe further down in the story you'll explain the circumstances, but you don't need them right there. Or say, “Fires are still being reported throughout the region.” In a news story, that's perfectly fine. We just need to know that fires are still happening. We don't necessarily need to know who's reporting it. More details may come later in the story, but right then it's perfectly fine. In news reports, in historical situations when we're giving a history, in scientific data and scientific reports, you often see the passive voice. It can be a perfectly good and oftentimes even more efficient way to tell something, but you don't want to lean into it and overuse it because it becomes very dull. When you don't have someone doing an action, it becomes very dull. Jo: As you've mentioned the legal side of things, and I'm reading a lot of academic papers at the moment. I'm doing another master's degree, and goodness me, I feel like sometimes it's designed to turn you off. Sarah: You are exactly right. I've come to that feeling too, and especially in seeing student work, where I feel like there is so much of that in academic writing, which students are reading and digesting. It naturally comes out of them, and it's a kind of cycle that's hard to break. Jo: Do you think it's a form of hedging? “Mistakes were made”—or anything legal—you are hedging it so it can be ambiguous. Whereas a strong verb—and you mentioned “your grandmother walked on the moon”—you are really making it very clear. If you want to hedge things, then using passive voice might be more appropriate. If you want to make it stronger, the activeness is important. Sarah: Yes. And it makes such a difference. I discovered this in my own work. I would read other critics, for example, and I would think, “I feel like the piece I've just written is kind of flat. It doesn't really have the effect I want, doesn't have any zip.” I would go and read other critics—not just dance critics, but other critics. It's so useful to just read other people in any type of writing that you're doing. I advocate doing a lot of reading. I would see that the pieces that really touched me, that really inspired me, had a lot of active voice constructions. They're not turning things around passively, which I think, as a young critic, I may have been doing because I was a little bit afraid to take a stand. Jo: Mm. Sarah: I think I see that in student work, that sometimes we don't want to take a stand, and so we hedge. But writing is intentional, and readers can pick up on that hedging. If you don't intend to hedge—in many cases it can be perfectly appropriate to be fuzzy for an effect that you want, or something like that in the context—but if you are hedging and you're trying to get away with it, like you don't want anyone to notice that you don't really want to give an opinion on this matter, it's going to be very clear. So it's better to address something directly. Jo: And make it stronger. I also wanted to ask you more about the writing career, because I, perhaps like many people listening, was like, I didn't even know you could make a career as a dance critic. Now I know you are not at the Washington Post any more, and it's possible that that role no longer exists—like a lot of writing roles. How has your writing career changed over the years? Do you have these various aspects of a portfolio career? We often talk about multiple streams of income on this show and how, as writers, we can't necessarily rely on one thing. Sarah: Yes, exactly. It's true, there is no longer a dance critic at the Washington Post. The position was eliminated. It's a shame, and it's happening to critics in all fields, in all media organisations, sadly. That's where, for me at least, having that focal point was very key. A thing that I became comfortable writing about, that I could then spiral out and use the eyes and the brain that I had developed from writing about this certain focus for a while. Where can I take that? Oh, athletes. They also move. I began writing stories and pieces and essays about athletes that moved beautifully, beyond racking up statistics about winning. They were just gorgeous to look at, just so pleasurable to watch. I started writing about the body language of political candidates in debate situations and so forth. Using my focal point to then widen my lens, to mix a metaphor, I guess. Having that subject matter and then broadening it out beyond the limits of the actual subject matter, broadening it out imaginatively into where I could find other places to use this perspective. That was really key for me. Say you are writing historical fiction or you're writing thrillers. I would imagine that you would develop a kind of expertise in things that I would find very difficult. Suspense, maybe, or political or police procedure, or what exactly was the weaponry in seventeenth-century France. How can you take that expertise and use it either in an aesthetic way or an actual factual way to address other topics? I think there are so many people that would be interested in what writers who have knowledge and expertise in anything can then use to show us something that we've overlooked. Something we always thought we knew, but that really, when you look at it this way, is reminiscent of how the scabbard was used in seventeenth-century France—or whatever it is, in whatever way. People are craving a new perspective on something they've overlooked or taken for granted. And that's where writers who have a body of work, or are interested in pursuing a certain topic. That's the promise that they have. They can work towards being able to enlighten us on so many other things that maybe only have a tangential connection, but they can make that connection for us. Jo: Fantastic. Where can people find you and your books online? Sarah: I am at SarahLKaufman.com. That's my website. My books are available on any website or bookshop that you want to order them from. Verb Your Enthusiasm comes out April 28th. I am not much on social media at the moment, but I do enjoy hearing feedback from readers, and there are ways to do that on my website. Jo: Well, thanks so much for your time, Sarah. That was great. Sarah: Thank you very much. I've enjoyed it.The post Verb Your Enthusiasm: Transform Your Writing With Stronger Verbs With Sarah Kaufman first appeared on The Creative Penn.

00:00 - a DRUBBING 03:56 - Tyrese Maxey 11:36 - Sixers bench woes 15:00 - Joel Embiid 19:20 - What is Joel Embiid's legacy? 23:11 - Josh Hart's snide comments 26:05 - Offseason discussions loom  

An old woman weaves the weather of the world from a tiny house at the edge of everything — drought and rain, joy and grief, all of it intentional, none of it mistake. When a young woman named Mira arrives lost and searching, she finds not answers but something older and more useful.You can get my new book, Awaken Your Myth, at https://awakenyourmyth.com/book/. Please leave a review on Amazon here: https://www.amazon.com/Awaken-Your-Myth-Discover-Purpose/dp/1797235257/ref=tmm_hrd_swatch_0#averageCustomerReviewsAnchor To leave a review on GoodReads, click here: https://www.goodreads.com/book/show/238747993-awaken-your-myth#CommunityReviewsYour support is the cornerstone that allows me to continue crafting tranquil stories and meditations for you. For less than the price of a cup of coffee, you'll unlock an oasis of over 500 ad-free Listen To Sleep episodes, including 8 subscriber-only full length sleepy audiobook classics like Winnie the Pooh and Alice in Wonderland. To pledge your support, visit⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://listentosleep.com/support⁠⁠ or subscribe right in Apple Podcasts and get a 7 day free trial. Want to change your story? Take the free Path Assessment at https://jointhecabin.org. In two minutes, you'll see your personalized journey and know exactly where to start. To join my email group and get a bunch of goodies, go to ⁠⁠https://erikireland.com Sleep well, friends.

26+ actionable passive income ideas for 2026 and beyond in this lively and interactive episode with Favour Obasi-ike, MBA, MS and a panel of guests. Drawing inspiration from a viral Instagram post by Business Bounce, the conversation moves far beyond a simple list—delving into real experiences, mindset, and strategies for creating true wealth streams.Listeners are guided through proven paths like dividend stocks, selling digital courses, high yield savings accounts (HYSA), rental real estate, affiliate marketing, and innovative digital ventures such as podcasting and blogging.Our guests share personal stories, cautionary tales, and practical recommendations. The episode emphasizes the importance of research, updating your skills, the power of community, multiple income streams, and maintaining the right money mindset.The dialogue covers everything from global economic nuances, risk tolerance, automation, and leveraging data, to optimizing your online presence for long-term recurring income.Practical tools and resources are mentioned, such as Google AdSense, Cap.so, and tips for leveraging couponing apps or optimizing SEO for passive returns.Real-life examples and community questions bring depth and high value to listeners at any stage of their wealth-building journey.Ready to Rank? Book Your SEO & Web Dev Services Today

In this episode of the Ecomm Breakthrough podcast, host Josh Hadley shares a powerful weekly habit for CEOs: a 15-minute asynchronous video newsletter sent every Monday. Drawing from his ecommerce experience, Josh explains how this tool combats team misalignment, competing priorities, and the "founder's trap." The newsletter follows a four-part structure: celebrating weekly wins, identifying the key business constraint, recognizing core value exemplars, and reinforcing the company vision. Josh also highlights common mistakes to avoid, such as inconsistent messaging and vague praise. His core message is that consistent, structured communication transforms scattered teams into aligned, motivated, and proactive organizations.Bullet Points:Importance of consistent leadership communication for team alignmentIntroduction of a weekly CEO newsletter as a communication toolChallenges of team misalignment and competing prioritiesThe "founder's trap" and its impact on team understandingBenefits of asynchronous communication over live meetingsStructure of the CEO newsletter: wins, current constraints, core values, and visionCelebrating team wins to boost morale and motivationIdentifying and addressing key business constraintsRecognizing team members who exemplify core valuesReinforcing the company's mission and vision to maintain engagementTimestamps:00:00:00 Introduction to the CEO's #1 Weekly HabitJosh Hadley introduces the concept of a weekly CEO newsletter to improve leadership, clarity, and team performance.00:01:50 The Problem: Team Misalignment and Lack of CadenceDiscusses why teams feel scattered and reactive, highlighting a cadence problem, not a communication problem, in leadership.00:03:40 Why Teams Get ScatteredExplains that teams lose focus because they forget the mission, have competing priorities, and lack the CEO's full perspective.00:06:22 The Solution: The Weekly CEO NewsletterIntroduces the asynchronous weekly newsletter, recorded via Loom, to maintain clarity and momentum without adding more meetings.00:07:19 The Power of Asynchronous CommunicationAdvocates for asynchronous updates over meetings to avoid wasted time, task switching, and to increase team agility and output.00:08:58 How to Create the Newsletter ContentDetails the process of using Loom's transcription feature and an AI tool like Claude to draft the email content.00:11:05 The Four-Part Newsletter AgendaOutlines the four key sections of the weekly update: wins, the primary constraint, core value shout-outs, and the vision.00:12:45 Agenda Part 1: Sharing WinsExplains the importance of sharing wins to build morale and make the team feel like they are winning.00:16:42 Agenda Part 2: Stating the ConstraintFocuses on naming the single most important bottleneck to align the entire team's energy and focus weekly.00:21:05 Agenda Part 3: Core Value Shout-OutsDescribes how to use specific examples of employees living the core values to embed and reinforce company culture.00:25:00 Agenda Part 4: The Vision ReminderEmphasizes connecting daily work back to the company's long-term mission to create meaning and build endurance.00:26:00 The CEO Update FlywheelSummarizes how wins, vision, constraints, and core values work together to create belief, meaning, focus, and culture.00:26:40 Five Mistakes to AvoidLists common pitfalls that can kill the newsletter's effectiveness, such as brain dumps and only sharing problems.00:27:48 Your First CEO Update PromptProvides a simple, four-part prompt for creating the first newsletter, covering a win, a constraint, a value, and the vision.00:28:20 The Leadership LessonConcludes that leadership is about creating a rhythm and clarity, not just more meetings, to magnify team output.Links and Mentions:Tools and Websites"Loom": "00:06:22""Claude": "00:09:51"Key Concepts and Practices"Weekly CEO Newsletter": "00:01:50""Asynchronous Communication": "00:07:19"Leadership Principles"Core Values": "00:21:05"Summary of the Four-Part Agenda for the Newsletter"Wins from the Previous Week": "00:11:31""Identifying the Constraint": "00:17:20""Core Value Shout Outs": "00:21:05""Vision Reminder": "00:25:34"Mistakes to Avoid"Random Brain Dump": "00:27:27""Only Sharing Problems": "00:27:27""Generic Praise": "00:27:27""Changing the Message Weekly": "00:27:27""Making it About Yourself": "00:27:27"Transcript:Josh Hadley 00:00:00  If your team is always busy, they're a little scattered and unclear the direction the business is heading. They don't need more meetings. They need you to step up to be the true CEO and the leader that you are meant to become. In today's episode, I'm going to share the number one weekly habit that CEOs need to implement to be able to ten x their leadership output, increase the clarity inside the business, and get everybody rowing in the same direction so that your team maximizes their performance and output in the overall business. Welcome to the Ecomm Breakthrough podcast, I'm Josh Hadley. I've scaled my own ecommerce brand from 0 to 8 figures, and I'm actively building towards nine figures in sales. This podcast is where I document that journey and share the systems, the strategies, and the lessons learned in real time so that you can learn what actually matters and scale your own business. Who am I? My name is Josh Hadley. First and foremost, I'm a man of faith. I'm a father of four and a husband to a beautiful wife.Josh Hadley 00:00:56  I've been selling in the e-commerce space for over a decade now, doing over $20 million in revenue annually. And I'm selling multi-millionaires in three different sales channels Shopify, TikTok shop and Amazon. And I'm also the host of the number one business strategy podcast for ecommerce entrepreneurs. And that's E-com breakthrough. So let's face it, your team is busy, they're scattered, and they're unclear with the direction that the business is heading and specifically the role that they play inside the overall direction that your business is heading. They don't need additional meetings. What they do need from you is they need you to actually lead. So today, that's exactly what we're going to be diving into. And I'm going to share with you the number one habit that you need to adopt every week as the CEO. And that is the weekly CEO newsletter. Let's talk a little bit more about this. This is a 15 minute habit that you can do at the very beginning of every single week. So this is something that I've implemented in my own business every single Monday.Josh Hadley 00:01:50  It's a 15 minute habit that keeps your team aligned, focused and connected and moving in the same direction, making sure that we are all building to achieve that overall mission and vision that you have established for the business. So let's talk about what the problem actually is. The problem isn't necessarily just like a lack of communication, because hopefully you already have existing meetings and you've been communicating with these team members. But what's happening is your team feels scattered. They're quiet. Maybe they're a little reactive. You wish they would be more proactive in solving problems in the business. They feel a little disconnected from the overall mission. Or maybe they even question like, why are we in business? Maybe they just feel like they're just there to collect a paycheck for you, and they're not really tied into the overall purpose and mission that your company is servi...

9. Gregory Copley describes the intractable situation in the Strait of Hormuz as ceasefire deadlines loom. He identifies IRGC leader Ahmed Vahidi as a hardliner who will not negotiate. Copley argues that only decisive military action against IRGC leadership can resolve the conflict and secure international waters. 91910

The fragile Iran-U.S. ceasefire is being tested, the Artemis II crew is expected to splash down to Earth tonight, and President Trump steps in to help save college sports. Get the facts first with Morning Wire.- - -Ep. 2726- - -Wake up with new Morning Wire merch: https://bit.ly/4lIubt3- - -Today's Sponsors:Goldbelly - Go to https://goldbelly.com and get 20% off your first order + free shipping with promo code WIRE.Zoc Doc - Go to https://Zocdoc.com/WIRE to find and instantly book a doctor you love today.Comcast - Learn more about how Comcast is investing in a more connected America at https://ComcastCorporation.com/investment- - -Privacy Policy: https://www.dailywire.com/privacymorning wire,morning wire podcast,the morning wire podcast,Georgia Howe,John Bickley,daily wire podcast,podcast,news podcast Learn more about your ad choices. Visit podcastchoices.com/adchoices