Podcasts about Open Door

What does it look like to open a door that changes everything?In this episode of Undercurrents, we trace the remarkable story of how Canada became a world leader in refugee welcome — and why that legacy matters more now than ever.Host Ken Ogasawara sits down with Mike Molloy, retired Foreign Service officer and one of the architects of the world's first private refugee sponsorship program, to hear how a small clause buried in a 1976 immigration act became a lifeline for hundreds of thousands of people fleeing the Indo-China wars. And how MCC became a foundational partner in making it all work.We also hear from Kaylee Perez, MCC's Global Migration and Resettlement Strategic Initiatives Lead, who brings both professional expertise and deeply personal roots to this work. Her insight: the antidote to fear is proximity.Together, their stories remind us that welcoming the stranger isn't a radical idea, it's foundational to our faith expression.In this episode:Why Bill Janzen's "drop the rope" approach to government negotiation built something extraordinaryWhat Hearts of Freedom — 170+ interviews with former refugees — reveals about gratitude, belonging, and Canadian identityWhy 66% of Canadians still support refugee welcome, even if you'd never know it from the comments sectionHow the We're Better Together campaign is equipping everyday people to shift the conversation in their own communitiesThe data is clear. Refugees strengthen Canada's workforce, arrive ready to contribute, see their incomes grow, and become citizens at remarkable rates. But as Kaylee reminds us — this was never just about economics. It's about who we want to be.Ready to act?Learn about refugee sponsorship at mcc.orgJoin the We're Better Together campaign at the Canadian Council for Refugees: https://mcc.org/better-togetherExplore the Hearts of Freedom project: heartsoffreedom.orgUse the discussion guide on our website to bring this conversation to your church or community groupSend us a note at podcast@mcco.ca — we'd love to hear from youTranscription is here.Discussion guide here.Undercurrents is sponsored in part by Kindred Credit Union.Credits:Production support from Christen KongLogo artwork by Jesse BergenTheme song by Brian MacMillanExecutive produced by Sandra Reimer.

A sermon on Colossians 4 

Title: Spreading Good News Passage: Acts 8 Speaker: Pastor Ken Stodola Listen/watch us live on Rumble: https://rumble.com/user/ODBaptist Don't forget to share and subscribe Listen/watch us on sermons at https://www.sermonaudio.com/source_detail.asp?sourceid=odbaptist Follow us on Facebook: https://www.facebook.com/Open-Door-115705998459103 1128 Oates Road Prattville, AL 36066 United States

In the first installment of Through Art's Open Door,  I chatted with Broadway actress Jennafer Newberry Peery, who plays Glinda in Wicked on Broadway.  Jennafer shares what it's really like to perform in one of the most beloved musicals in the world while balancing family life, motherhood, and the demands of eight-show weeks. We explore art as a spiritual practice, the courage it takes to remain tender in a world that rewards efficiency, and why changing our minds may be one of the bravest acts of justice available to us. Jennafer reflects on the works of art that have become thin places in her own life–from film and poetry to sunsets, theater, and holding her daughter in her arms. Whether you're an artist, a parent, a person of faith, or simply someone longing to reconnect with wonder, this conversation offers an invitation to notice the beauty that is already speaking to you. Works of Art Mentioned Arrival (2016) Hamnet "There Is Something" poem by Ted Loder "On the Nature of Daylight" by Max Richter Resources & Links Preorder Art Is How God Loves Us  Follow Jennafer Newberry Peery on Instagram: Instagram  Sacred Salon: An Evening of Music and Conversation in New York City Other launch events I'd love to hear about the works of art that have become thin places in your own life. In fact, we are doing a call for guest-post submissions over on Substack. You can learn more and submit yours by visiting: https://artistsforjoy.org/artsopendoor  

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The RBI is offering NRIs tax free dollar deposits that, with leverage, can deliver equity-like returns, part of a wider push to steady the rupee. US firm Opendoor is shutting its India operations and betting on AI instead, reigniting the debate over the future of back office work here. MetLife wants majority control of PNB MetLife now that India allows full foreign ownership in insurance. A weak El Nino monsoon threatens hydropower as power demand hits records. And the European Central Bank has hiked rates for the first time in three years, with the Fed up next. Top of the Morning with Nelson John is your daily briefing on Indian business, markets, policy and the global stories that move them. New episode every morning. #IndianEconomy #RBI #FCNR #Opendoor #ECB #Hydropower #BusinessNews Learn more about your ad choices. Visit megaphone.fm/adchoices

In "This Is My Door," Apostle Jim Raley continues the Aftershocks series with a powerful word from Acts 9:32-43. Acts 2 was the epicenter, and everything that follows is the aftershock still rumbling along the fault lines of Pentecost. This message takes us to two people most preachers treat as separate stories. A paralyzed man named Aeneas in Lydda and a beloved disciple named Dorcas in Joppa. One frozen. One dead. Two cities, two miracles, and one fault line running through both. Through their stories, Apostle Raley reminds us that frozen is not finished, that the same Pentecostal power still breaks every destructive cycle, and that God wants to raise what we have stopped fighting for. Joppa means "the door." The Holy Spirit has been searching you out, and this is your door. Stop washing what God wants to raise, get a "yet" praise in your mouth, and walk through into your new beginning. Acts 9:32-43 | Psalm 42:11 | Ezekiel 37:3 Stay connected at https://calvaryfl.com

What happens when nurses are empowered to practice at the top of their license? In this episode, Amanda sits down with Maria Durazo, RN and Isabelle Lunsford, RN, PHN, MSN, of Open Door Community Health Centers in CA, to discuss how they transformed the nursing role to improve access, support providers, and strengthen patient care in a highly rural environment. Learn how Open Door built a Tactical Nursing model, developed nurse-led flip visits, created career pathways for nurses, and more than doubled the number of patients served through nurse visits through innovative nursing workflows.Whether you're a clinical leader, nurse manager, or healthcare executive, this episode offers practical lessons on change management, workforce development, and maximizing the impact of your nursing team.Guests: Maria Durazo, RN, and Isabelle Lunsford, RN, PHN, MSNHost: Amanda LaramieThanks for listening!  Check us out on: FacebookInstagramLinkedInOur WebsiteTikTokTwitterYouTube 

Listen/watch us live on Rumble: https://rumble.com/user/ODBaptist Don't forget to share and subscribe Listen/watch us on sermons at https://www.sermonaudio.com/source_detail.asp?sourceid=odbaptist Follow us on Facebook: https://www.facebook.com/Open-Door-115705998459103 1128 Oates Road Prattville, AL 36066 United States

Morning Worship Sermon with Rev. Bud Hance Scripture reference Revelation 22:17 17 And the Spirit and the bride say, “Come!” And let him who hears say, “Come!” And let him who thirsts come. Whoever desires, let him take the water of life freely.

Revelation 3:7-13

Title: Church Life in Hebrews 10:24-25 Passage: Hebrews 10:24-25 Speaker: Pastor Ken Stodola Listen/watch us live on Rumble: https://rumble.com/user/ODBaptist Don't forget to share and subscribe Listen/watch us on sermons at https://www.sermonaudio.com/source_detail.asp?sourceid=odbaptist Follow us on Facebook: https://www.facebook.com/Open-Door-115705998459103 1128 Oates Road Prattville, AL 36066 United States

Message: Holy Ground/Open Door Series: The Tabernacle: Holy Ground/Open Door Original Date: June 7, 2026 Click HERE for Message Outline Click HERE for Discussion Guide Shortly after the Ten Words, God laid out plans for a tent. Not just any tent — a one-of-a-kind tent where heaven and earth would overlap. Where Holy God could meet with less-than-holy people. A place called the Tabernacle. In this 4-part message series — The Tabernacle: Holy Ground/Open Door — we will discover how God was pointing to Jesus all along.

In today's conversation, Brett sits down with CMO of Figma, Sheila Joglekar Vashee. Previously the second marketing hire at Dropbox, where she helped scale the company past $1 billion in revenue, she now leads marketing at Figma fresh off its IPO. In an industry that has spent a decade trying to turn marketing into something closer to hedge fund trading, Sheila argues the art was always the point — we just stopped talking about it. She unpacks how to run marketing as a portfolio of moonshots, why giving teams different goals breeds dysfunction, how to scale taste across an organization, and why old playbooks are obsolete, even as the fundamentals hold. In today's episode, we discuss: How to run marketing like a portfolio of moonshots The value of disruptive energy for senior marketers Why "Ubiquity is the opposite of cool" How to actually scale taste across an organization What great marketing looks like in the AI era Referenced: Apple: https://www.apple.com/ Dennis Woodside: https://www.linkedin.com/in/dennis-woodside-341302/ Dropbox: https://www.dropbox.com/ Dylan Field: https://www.linkedin.com/in/dylanfield/ Figma: https://www.figma.com Francoise Brougher: https://www.linkedin.com/in/francoise-brougher-341a72/ Gap: https://www.gap.com/ Google Chrome: https://www.google.com/chrome/ Harley-Davidson: https://www.harley-davidson.com/ HubSpot: https://www.hubspot.com/ Notion: https://www.notion.com/ Opendoor: https://www.opendoor.com/ Pinterest: https://www.pinterest.com/ Square: https://squareup.com/ The Web Is What You Make of It (Dear Sophie): https://www.youtube.com/watch?v=pzOBOuyr-EU Urban Outfitters: https://www.urbanoutfitters.com/ Yamini Rangan: https://www.linkedin.com/in/yaminirangan/ Where to find Sheila: LinkedIn: https://www.linkedin.com/in/sheilavashee/ X: https://x.com/sheilavashee Where to find Brett: LinkedIn: https://www.linkedin.com/in/brett-berson-9986644/ X: https://x.com/brettberson Where to find First Round Capital: Website: https://firstround.com/ First Round Review: https://review.firstround.com/ Twitter/X: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast Timestamps: 00:00 Introduction 00:07 What excellent marketing actually is in 2026 01:36 Why giving teams different goals creates dysfunction 02:36 The most important decision Sheila made as CMO last year 04:26 The real difference between an SVP and a CMO 06:05 Marketing is one engine - not separate pieces 07:15 The tension between brand and growth 09:25 The decisions a CMO should never be making 09:55 Running marketing like a portfolio of moonshots 12:46 "Ubiquity is the opposite of cool" 15:11 Why a few companies get a flywheel of momentum 16:44 The Silicon Valley clock and irrational perception cycles 19:25 How to actually scale taste across an org 21:09 What changes for a CMO in a post-LLM world 23:15 Why the artistic side of marketing never really left 26:05 Whether taste can ever be encoded in software 27:15 Telling an optimistic, yet realistic story about AI 30:50 You need to make people care 32:11 What surprised Sheila about being a public-company CMO 33:46 Why Figma won enterprise where Dropbox couldn't 35:25 Sheila's favorite campaign ever 37:10 Why announcement videos full of humans, lack humanity 38:55 Playbooks are obselete, but the fundamentals are not 40:25 Why marketing in 2026 demands disruptive energy 41:54 How Sheila architects her week 48:55 Where corporate politics actually come from 53:55 "Sheila, are you going to change the world in this job?" 58:09 What's unique about the CMO and CEO relationship

In this episode of the Microsoft Threat Intelligence Podcast, host⁠ ⁠⁠Sherrod DeGrippo is joined by Allie Luhrs and Mario Samolis from Microsoft Security to explore the growing threat of open source software supply chain attacks. They discuss how malicious NPM packages, compromised developer ecosystems, AI-generated attacks, and software dependency risks are reshaping modern incident response, while sharing insights from their recent presentation at BlueHat IL 2025.   In this episode you'll learn:       How attackers are targeting open source software ecosystems at scale  Why AI is accelerating both cyberattacks and threat detection  What was uncovered during their BlueHat presentation on modern software supply chain attacks  Some questions we ask:      What patterns did you uncover in NPM attack campaigns?  Should developers rely on dependencies or build everything themselves?  Why should organizations pay closer attention to open source security risks?  Resources:   View Allie Luhrs on LinkedIn   View Mario Samolis on LinkedIn   View Sherrod DeGrippo on LinkedIn     Related Microsoft Podcasts:                    Afternoon Cyber Tea with Ann Johnson  The BlueHat Podcast  Uncovering Hidden Risks        Discover and follow other Microsoft podcasts at microsoft.com/podcasts     Get the latest threat intelligence insights and guidance at Microsoft Security Insider    The Microsoft Threat Intelligence Podcast is produced by Microsoft, Hangar Studios and distributed as part of N2K media network. 

The AI stock rally just got even crazier.After Nvidia CEO Jensen Huang suggested that Marvell could become the next trillion-dollar company, investors wasted no time piling in. The result? A massive surge that added billions in market value almost overnight. But here's the real question: is Marvell still a buy, or is this another case of investors chasing the latest hot stock too late?In this video, we break down Marvell's explosive move, what the latest OVTLYR signals are showing, and why some of the biggest names in tech are starting to flash warning signs despite their incredible gains.You'll also see how market breadth, fear and greed levels, and sector rotation could impact the next major move in stocks.✅ Why Marvell surged after Jensen Huang's comments✅ Key OVTLYR buy and sell signals explained✅ Warning signs appearing beneath the AI rally✅ Stocks like Micron, Broadcom, Dell, and OpenDoor in focus✅ What sector rotation could mean for investors right nowThe biggest story may not be Marvell itself. Money appears to be moving away from high-flying AI names and into defensive sectors like utilities, consumer staples, and energy. That shift could have major implications for the broader market.Are we watching the next leg higher in AI stocks, or the early stages of a market cooldown? Share your thoughts below.Subscribe to OVTLYR for disciplined trading strategies that actually make sense.

Title: What Does it Mean to "Fall Away" in Hebrews 6:4-6? Passage: Hebrews 6:4-6 Speaker: Pastor Daniel Weierbach Listen/watch us live on Rumble: https://rumble.com/user/ODBaptist Don't forget to share and subscribe Listen/watch us on sermons at https://www.sermonaudio.com/source_detail.asp?sourceid=odbaptist Follow us on Facebook: https://www.facebook.com/Open-Door-115705998459103 1128 Oates Road Prattville, AL 36066 United States

Over the past two weeks in the Coaching Café we have been privileged to focus on CEOs who are leading the way with coaching.The series features conversations with CEOs, who are not only supporting coaching in their organisations, but actively role modelling a coaching approach—whether through undertaking coach training themselves, embedding coaching into leadership practice, or enabling a broader culture of coaching. The intention of this series is to share practical insights from leaders who are “walking the talk”.This week we are pleased to welcome Pat Cooper, CEO of HVCCC and former Group Captain Air Force, to share a unique perspective that spans over 10 years (since his coach training with Open Door) and across two very different organisations.Join Dr Natalie Ashdown as she interviews Pat to explore topics such as:✔️ How coaching forms part of your leadership style ✔️ Why coaching matters in your organisation ✔️ What you've observed in terms of impact, performance, and engagement ✔️ Other insights/observations you would like to share about coaching in the workplaceJoin us for this inspirational conversation as we consider what becomes possible when coaching is championed at the very top of an organisation.Transcripts can be found here: Thanks for listening! If you enjoyed the podcast please leave us a 5 star review wherever you listened to us! It helps promote the podcast to streaming services and other listeners. Also drop the podcast a follow! Watch the webinar of this episode on YouTube or read the blog by visiting our website.Want to join us live every Friday? Register Here!  Engage with The Coaching Café PodcastStay up to date on our socials InstagramFacebookLinkedInEmail us at learn@opendoorcoaching.com.auThanks for listening!

God often opens doors of opportunity for us, but walking through them won't always be easy. Paul walked through a door God had opened for him in Ephesus even though the Corinthians were begging Paul to come back. In this message, Pastor Duane Brooks uses Paul's calling to the church in Ephesus to show how we should put the important over the urgent and trust God's perfect timing. Message based on 1 Corinthians 16:5-9. To discover more messages of hope, go to tallowood.org/sermons/.Follow us on X and YouTube @tallowoodbcFollow us on Instagram @tallowood.baptistFollow us on FaceBook @tallowoodbaptist

Title: Which Soil Are You? Passage: Luke 8:4-15 Speaker: Pastor Daniel Weierbach Listen/watch us live on Rumble: https://rumble.com/user/ODBaptist Don't forget to share and subscribe Listen/watch us on sermons at https://www.sermonaudio.com/source_detail.asp?sourceid=odbaptist Follow us on Facebook: https://www.facebook.com/Open-Door-115705998459103 1128 Oates Road Prattville, AL 36066 United States

As the S&P 500 (SPX) hits a record high, Charles Schwab's Joe Mazzola believes there's room for a higher run. A surge in call options activity, backed by strength in key sectors, serve as key arguments to Joe's bullish thesis. He notes a hot PCE print later this week will become a roadblock should it manifest. Michelle Gibley says semiconductor stocks remain in a cyclical trend not just in the U.S., but also overseas in economies like Taiwan and South Korea. Those countries also face similar concerns as the U.S., particularly in rising inflation. ======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

In this episode of The Open Door, panelists Thomas Storck, Andrew Sorokowski, and Christopher Zehnder talk with Richard Spinello, a professor at Boston College, on the relationship between philosophy and theology, particularly within the Catholic tradition.Spinello emphasized the importance of philosophy in theological education, highlighting the need for a solid philosophical foundation, especially in ethics and metaphysics. The conversation also touched on the decline of Thomism in modern academia and the influence of modern philosophy on theology, particularly the challenges posed by relativism and postmodernism. The panelists agreed on the necessity of a metaphysical dimension in Catholic philosophy and the need for a revival of Thomistic studies.For more on this point, see Spinello's Four Catholic Philosophers: Rejoicing in the Truth (Jacques Maritain, Edith Stein, Dietrich von Hildebrand, Karol Wojtyła) This book unfolds the intersecting life stories of four important Catholic philosophers of the 20th century, namely, Jacques Maritain, Edith Stein, Dietrich von Hildebrand, and Karol Wojtyla, and examines the salient themes of their respective philosophies. Exploring the lives of these four individuals will unlock for the reader the nature of Catholic philosophy, which always aspires to a higher wisdom and the discovery of the hidden harmony of the universe. The spiritual itinerary of these faithful scholars is part of a larger story, therefore, of the intimate relationship between faith and reason that is at the heart of Catholic intellectual life. https://enroutebooksandmedia.com/fourcatholicphilosophers/

Celebramos el centenario del nacimiento de Miles Davis con once trompetistas de primer nivel internacional: Ambrose Akinmusire, Adam O'Farrill, Sam Joris, Palle Mikkelborg, Julien Bertrand, Yazz Ahmed, Gerald Bailey, James Davis, Kirk Knuffke, Theo Croker y Thomas Marriott. Temas que suenan en el programa: 01 2025 Ambrose Akinmusire Mary Halvorson - Slo-Mo Neon Luminate Hoverings – Blood & Sand (6' 14'') 02 2024 Adam O'Farrill - Elephant 04 Sea Triptych, Pt. 3 Iris Murdoch - Yvonne Rogers Walter Stinson Russell Holzman (3' 25'') 03 2022 Sam Joris & Wout Gooris - Kleinood 02 Emerge From the Gloom - Method In the Madness (5' 29'') 04 2024 Palle Mikkelborg - Light 09 Stille, Hjerte, Sol Gar Ned - Jakob Bro (5' 06'') 05 2022 New Fly - Waxman 07 Fear and Healing - Julien Bertrand Liam Szymonik Etienne Deconfin François-Régis Gallix Arthur Declercq (5' 03'') 06 2025 Yazz Ahmed - A Paradise In The Hold 06 Dancing Barefoot - Alba Nacinovich Brigitte Beraha Naadia Sheriff George Crowley Ralph Wyld Martin France Corrina Silvester (6' 59'') 07 2025 Gerald Bailey - Gross Means 01 Bench Seat - Chris Geddes Kyle Hodges Jake Vinsel Brad Wagner David Ageo Dan Bailey Harry James (2' 05'') 08 2024 James Davis' Beveled A- rc and Edge 04 Open Door, Closed Door - Chad McCullough Geof Bradfield Michael Salter Daniel Thatcher Juan Pastor (4' 42'') 09 2025 Kirk Knuffke - Window 10 Heavy Times - Stomu Takeishi Bill Goodwin (3' 31'') 10 2025 Theo Croker - Dream Manifest 05 Light as a feather - Gary Bartz Natureboy Flako (3' 46'') 11 2024 Thomas Marriott - Screen Time - Orrin Evans Robert Hurst III Mark Whitfield (4' 15'')

In this episode of the Dudes and Dads Podcast, Andy, Mark, and Joel discuss the challenges of raising teenage boys and guiding them toward adulthood. After Mark shares his new hobby of collecting ancient biblical coins, the conversation shifts to navigating the “pre-launch” phase of parenting. The dads explore the different paths their kids are...

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

Conflict in the Middle East has drawn attention away from other devastating wars, including in Sudan, where millions of civilians have been displaced and forced to flee to neighboring countries. It comes as nations have reduced refugee assistance, leaving humanitarian agencies scrambling. Special correspondent Fred de Sam Lazaro reports from Uganda, one of the region's destinations for refugees. PBS News is supported by - https://www.pbs.org/newshour/about/funders. Hosted on Acast. See acast.com/privacy

Send us Fan MailWhat do you do when you're standing in front of a decision and you're not sure if it's God opening a door — or if you're forcing one open yourself? In this episode, Pastor Jess and Pastor Gabe unpack a framework for discerning God's will that has shaped Westside's biggest current decision as a church, and works just as well for parenting, marriage, career, and the everyday moments where you're asking, "Is this from the Lord, or is this just me?"Discover:The "painted doorway on a brick wall" picture and what it reveals about forcing God's handThe 5-filter framework for discernment: Word, Spirit, Counsel, Circumstances, Spiritual UnityWhy God's will never contradicts God's Word — and why that has to be filter number oneHow to tell the difference between the Holy Spirit's confirmation and His convictionThe "rudder vs. rowing against the current" picture for Spirit-led livingWhy every believer needs a Paul, a Barnabas, and a Timothy in their cornerThe "squeeze the lime" principle — stewarding what you already have before asking for moreWhy favorable circumstances alone aren't enough to confirm an open doorHow spiritual unity protects big decisions in marriage, family, and the churchReal examples from parenting school choices, waiting on a spouse, and Westside's current building decisionMost of us have tried to muscle our way through a wall we painted to look like a door. It hurts, it doesn't work, and it leaves us exhausted. The good news is that God isn't hiding His will from you. He's already given you His Word, His Spirit, godly people, real-life circumstances, and a community to walk with. When you slow down enough to let those five things speak together, what felt foggy starts to feel clear — and when an actual door opens, you'll recognize it because you won't have to break it down.Key Takeaways:God's will never contradicts God's Word — if it fails filter one, you don't pass goThe Holy Spirit is your rudder; peace and dissonance both have something to teach youCounsel that never challenges you isn't counsel — it's an echo chamberDon't mistake favorable circumstances for confirmation; run them through the other filters firstSteward what's already in your hand before you ask God for moreWhen the wind is in the sail, you know it — stop trying to blow into your own sailsQuestion for you to think about: What's a decision in front of you right now where you've been forcing a door — and what would change if you ran it through all five filters this week?Calls to Action:Subscribe so you don't miss next week's episodeDrop a comment with the decision you're discerning right now — we'll pray for youShare this with someone in a season of big decisionsConnect with us at Westside Community ChurchLINKS & RESOURCES: SUBSCRIBE to always see our content and let us reach more people for Jesus: https://www.youtube.com/westsidecommunitychurchpdx?sub_confirmation=1 Give to support this ministry and help us reach people all around the world: https://www.westsidecommunitychurch.com/giveSTAY CONNECTED: Website: https://www.westsidecommunitychurch.com Instagram: https://www.instagram.com/westsidecommunitychurch Facebook: https://www.facebook.com/westsidecommunitychurchpdx#MidweekMotivation #WestsideCommunityChurch #GodsWill #Discernment #OpenDoors #HolySpirit #ChristianPodcast #FaithDecisions #HearingGod #ChristianLiving #BiblicalWisdom #WalkingWithGod #ChristianCommunity #FaithAndLife #SurrenderToGod

Conflict in the Middle East has drawn attention away from other devastating wars, including in Sudan, where millions of civilians have been displaced and forced to flee to neighboring countries. It comes as nations have reduced refugee assistance, leaving humanitarian agencies scrambling. Special correspondent Fred de Sam Lazaro reports from Uganda, one of the region's destinations for refugees. PBS News is supported by - https://www.pbs.org/newshour/about/funders. Hosted on Acast. See acast.com/privacy

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In this episode, we explore the hidden downsides of open-door leadership and how it can quietly impact productivity, focus, and team performance. While the intention is to create accessibility and strong communication, constant interruptions can derail priorities and create unintended bottlenecks. Drawing on research from UC Irvine, I share how frequent disruptions affect deep work, along with a real case study of a CEO who found himself overwhelmed by team dependencies. You'll hear how he restructured his leadership approach by setting clearer boundaries, empowering independent thinking, and implementing focused one-on-one meetings. The result was more time, stronger team confidence, and improved overall performance. If you're a leader looking to support your team without sacrificing focus, this episode will help you rethink how accessibility and accountability can work together. Episode Highlights & Time Stamps 1:07 The Reality of Open Door Policies 2:47 Hidden Costs of Open Door Leadership 4:52 Strategies for Better Leadership 7:01 Conclusion and Key Takeaways

Join Pastor Marco to study the letter writen to Philadelphia from the book of Revelation.You can connect with Moriel in more locations than just YouTube!Check out all our official links on the About page: https://www.youtube.com/c/MorielTVministries/about.The U.S. Copyright Office protects this video and its contents under section 107 of the Fair Use Copyright Act 1976 which can be found here: can be found here:https://www.copyright.gov/title17/92chap1.html#107.While we do encourage comments, all are held for review before posting. We ask that you please focus your posts on the video and it's topic. Keep it relevant to the message; and of course showering us with love is always welcome. We do appreciate you and thank you for caring enough to speak up and speak out.Please note: Posts that are longer than a short paragraph, contains hate, or disrespectful comments, or links to websites or other videos will be deleted. Comments determined to be inappropriate, obscene, disrespectful or with links to pornographic material, will get you banned.All decisions on comments are at our discretion.

Today, we are breaking down Opendoor, and this is a unique episode. We recorded with Kaz Nejatian, the CEO of Opendoor, shortly after the company reported its first quarter 2026 earnings, and we covered both what is happening inside the business right now and how he is thinking about Opendoor from the seat after coming over from Shopify.  The core of the conversation is how Kaz frames the company. He argues that Opendoor is a market maker rather than a prop desk or an asset manager, and that the model only works when you optimize for velocity instead of spread. Buying lots of homes and selling them quickly gives Opendoor a live information advantage over the rest of the housing market that no other participant has, and that advantage compounds as the customer base broadens beyond people who simply need to move fast. Please enjoy this Breakdown of Opendoor. For the full show notes, transcript, and links to the best content to learn more, check out the episode page⁠⁠⁠⁠⁠⁠⁠ here.⁠⁠⁠⁠⁠⁠⁠ ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- This episode is brought to you by⁠⁠⁠⁠ ⁠Portrait Analytics⁠⁠⁠⁠⁠ - your centralized resource for AI-powered idea generation, thesis monitoring, and personalized report building. Built by buy-side investors, for investment professionals. We work in the background, helping surface stock ideas and thesis signposts to help you monetize every insight. In short, we help you understand the story behind the stock chart, and get to "go, or no-go" 10x faster than before. Sign-up for a free trial today at ⁠⁠⁠⁠⁠portraitresearch.com⁠⁠⁠⁠⁠ ----- Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps (00:00:00) Welcome to Business Breakdowns (00:02:24) Thesis Since Joining OPEN (00:04:49) OPEN is a Market Maker, not a Prop Desk (00:04:53) Opendoor's Advantages (00:07:37) Spread vs. Velocity (00:11:25) Customer Base (00:13:16) Attachment Profit Pool (00:15:45) Order of Product Rollouts (00:18:47) Friction from Attachments? (00:19:03) Lessons from Shopify: Solving for Friction (00:21:45) Investing vs. Profitability Balance (00:23:58) AI Inside Opendoor

https://teachhoops.com/ Building a team is a continuous process of alignment, friction, and refinement. It is the difference between having a collection of talented individuals and having a cohesive "unit" that operates with a single heartbeat. Whether you are building a high school program, a digital marketing team, or a youth roster, the fundamentals of human connection remain the same. To build a team that survives the "mid-season grind," you must move past the surface-level icebreakers and move into Architectural Culture Building. You aren't just looking for players; you are looking for "Energy Givers" who can amplify the standard of the person standing next to them. True bonds aren't formed during the victory celebration; they are forged in the "muck and grind" of shared struggle. This is why "Hell Week," early morning conditioning, or high-stakes business deadlines are so effective. When people suffer together toward a common goal, they develop a level of Resilience Equity that cannot be manufactured in a classroom. The Lesson: Don't shield your team from hard things. Use the struggle to define who you are. The Result: A group that doesn't point fingers when things go sideways, because they've already survived the worst together. In any team, you have people who fill the bucket and people who drain it. Building a team requires a ruthless commitment to the Standard of Energy. The Action: Publicly reward the "invisible" acts of team-building—the player who picks up a teammate, the assistant who stays late to clip film, or the employee who offers a hand before being asked. The Logic: You don't get the team you want; you get the team you tolerate. If you tolerate "Energy Takers," they will eventually become the dominant culture of your program. A team needs a "DNA"—a set of behaviors and traditions that belong only to them. These act as the "Glue" for the program. Small Wins: A specific hand-clapping sequence after a free throw, a team-only "victory dinner" at a local pizza spot, or a "Next Play" bell in the gym. The Why: Rituals provide a sense of belonging. They signal to the members: "This is how we do things here." This identity is what players will fight to protect when the pressure is highest. Most leaders say they have an "Open Door" policy, but true team-builders practice the "Active Reach." Don't wait for a team member to come to you with a problem. By the time they walk through your door, the problem has likely already started to rot the culture. The Strategy: Spend 5 minutes a day with a different person in a "Non-Task" conversation. Ask about their family, their goals, or their interests outside of the gym or office. The Impact: This builds Relational Capital. When you eventually have to coach them hard or deliver a "truth," they will listen because they know you care about the person, not just the performance. Team building strategies, basketball program culture, leadership development, athletic leadership, high school basketball coaching, youth sports mentorship, "The Villanova Way," Jay Wright leadership, character development, championship habits, energy givers vs takers, relational capital, coach unplugged, teach hoops, basketball success, mental toughness, program building, coaching legacy. Show Notes1. Curating "Shared Adversity"2. The "Energy Giver" Audit3. Creating Rituals and Traditions4. The "Open Door" vs. The "Active Reach"Team-Building Framework: The 4 PillarsPillarFocusManifestationVulnerabilityAdmitting mistakes.A coach apologizing for a bad tactical call in a film session.ClarityDefining roles.Every member knows exactly what "Winning" looks like for them.ConsistencyThe "Steady Hand."The standard remains the same, whether you win by 20 or lose by 2.AppreciationGratitude as a tool.Writing "Thank You" notes to players or parents for their sacrifices.SEO Keywords Learn more about your ad choices. Visit podcastchoices.com/adchoices

Alan Gardner is joined by Andrew Miller and Vithushan Ehantharajah to discuss potential comebacks for Ollie Robinson and Mason Crane as the Test summer draws closer Learn more about your ad choices. Visit podcastchoices.com/adchoices

Pastor Jim explores the biblical narrative of Lot in Sodom, contrasting his compromised morality with the steadfast righteousness of his uncle, Abraham. He argues that Lot's choice to reside in a wicked city led to a contextualized faith where he eventually viewed himself as virtuous simply by being less depraved than his neighbors. This gradual spiritual decay is presented as a warning to modern believers against the allure of luxury and the dangers of cultural assimilation. He emphasizes that Lot's rescue from the city's destruction was not earned through his own merit but was a result of unmerited divine grace and intercessory prayer. Ultimately, the story serves as a metaphor for the Gospel, portraying Jesus as the only door to salvation for a fallen humanity. Through this lens, Pastor Jim urges the audience to remain spiritually set apart while actively interceding for those lost in modern-day "Sodom."Support the showThanks for listening! Follow us on Facebook or Instagram more info colonialkc.org

This week's Department of Know is hosted by Rich Stroffolino, with guests Janet Heins, CISO, ChenMed, and TC Niedzialkowski, Head of IT & Security, Opendoor. Missed the live show? Check it out on YouTube. The Department of Know is live every Friday at 4:00 p.m. ET. Join us each week by registering for the open discussion at CISOSeries.com. Get the show notes here: https://cisoseries.com/cybersecurity-news-critical-cpanel-zero-day-swiss-black-axe-arrests-hhs-data-center-questions/ Thanks to our episode sponsor, Guardsqaure Attackers are treating your mobile app like an open book. Sixty-three percent of security leaders recently detected app tampering, cloning, or unauthorized modifications. When your code runs in an untrusted environment, you need runtime self-protection and code hardening to keep attackers out. Address tampering before it starts. Learn more at Guardsquare.com. 

In this episode of The Open Door, panelists Thomas Storck, Christopher Zehnder, and Andrew Sorokowski talk with Fr. Richard O Connor on Dialectics.

Hour three of DJ & PK for April 29, 2026: What will make you a NHL or hockey fan? Who will be the Big 12 favorite this fall? Does Brendan Sorsby situation help BYU and Utah?

This week's Book Picks comes from Drew Broussard and Nora Taylor from Rough Draft Bar & Books in Kingston, New York and Lily Bartles from Open Door Bookstore in Schenectady, New York.

Season 6, Episode 5: The No Cap Podcast continues with hosts Jack Stone and Alex Gornik diving into the high-stakes world of proptech with Brendan Wallace, co-founder and CEO of Fifth Wall. Managing billions for the world's largest real estate owners, Wallace explains his transition from a New York real estate family to bridging the gap between massive physical assets and cutting-edge technology. The conversation breaks down why real estate has historically been a "luddite" industry and how Fifth Wall's unique strategy, using major industry players as LPs, turned a "bug into a feature" for tech adoption. From backing unicorns like Procore and Open Door to the strategic acquisition of Industrious by CBRE, Wallace shares the inside track on what actually drives returns in the built environment. Wallace predicts a total revolution where venture firms don't just build tools, they become the industry players themselves. If you want to know where real estate and AI are colliding, this is the episode to watch. Shoutout to our sponsor, Appfolio. The growth engine transforming how firms handle investor relations and distributions. TOPICS 00:00 – Intro to Brendan Wallace and Fifth Wall 01:28 – Career Origins: From Times Square to Goldman & Blackstone 09:12 – First Successes: Workday Acquisition and Founding Cabify 12:35 – Founding Fifth Wall: Filling the Proptech Gap 17:00 – Why Real Estate is a Historically "Luddite" Industry 19:27 – Winning Bets: Consumer Fintech, Procore, and Unicorns 24:43 – Industrious vs. WeWork: The Durable "Flag" Model 28:44 – The Future of Multifamily: Aspirational Brands like Sakra 33:54 – AI Revolution: Shifting to a "DIY" Internal Tech Model 42:58 – The Big Pivot: Why a Lack of Legacy Tech is now a Feature 50:15 – VC Evolution: Moving from Building Tools to the Industry Itself For more episodes of No Cap by CRE Daily visit https://www.credaily.com/podcast/ Watch this episode on YouTube: https://www.youtube.com/@NoCapCREDaily About No Cap Podcast Commercial real estate is a $20 trillion industry and a force that shapes America's economic fabric and culture. No Cap by CRE Daily is the commercial real estate podcast that gives you an unfiltered ”No Cap” look into the industry's biggest trends and the money game behind them. Each week co-hosts Jack Stone and Alex Gornik break down the latest headlines with some of the most influential and entertaining figures in commercial real estate. About CRE Daily  CRE Daily is a digital media company covering the business of commercial real estate. Our mission is to empower professionals with the knowledge they need to make smarter decisions and do more business. We do this through our flagship newsletter (CRE Daily) which is read by 65,000+ investors, developers, brokers, and business leaders across the country. Our smart brevity format combined with need-to-know trends has made us one of the fastest growing media brands in commercial real estate.

Advanced Placement exams represent some of the most challenging subject-specific standardized tests a high schooler might ever take. Amy and Mike believe that every test warrants smart, serious preparation, so we invited educator Leann Westin to share valuable strategies, insights, and resources for getting ready for the AP Biology exam. What are five things you will learn in this episode? What is tested on the AP Biology exam? How is the AP Biology exam structured and scored? What are the highest priority topics on the tests? How should students prepare for the AP Biology exam? What are the best prep materials for AP Biology? MEET OUR GUEST Leann Westin is a Master Tutor at Open Door Education in Massachusetts, where she also serves as the Tutor Success Coordinator. Leann earned a BS in biology with a minor in Spanish from Wake Forest University, and she specializes in biology, environmental science, statistics, SAT/ACT prep, and organizational coaching. Leann has over a decade of full-time experience helping students prepare for the AP Biology exam through both one-on-one tutoring and small group classes. Her favorite AP Biology topics to teach are evolution and ecology. Outside of her work at Open Door, Leann has been an education volunteer at her local zoo for almost a decade, and she enjoys helping people better understand the natural world.  Leann can be reached at https://opendoor.education. LINKS AP Biology Exam AP Biology Exam – AP Students AP Biology (Pearson Education AP) by Fred W. Holtzclaw; Theresa Knapp Holtzclaw AP Biology — bozemanscience RELATED EPISODES BIG CHANGES TO AP TESTS IN 2025 THE RISE IN AP TESTING CHOOSING BETWEEN AP AND IB PROGRAMS ABOUT THIS PODCAST Tests and the Rest is THE college admissions industry podcast. Explore all of our episodes on the show page. ABOUT YOUR HOSTS Mike Bergin is the president of Chariot Learning and founder of TestBright, Roots2Words, and College Eagle. Amy Seeley is the president of Seeley Test Pros and LEAP. If you're interested in working with Mike and/or Amy for test preparation, training, or consulting, get in touch through our contact page.  

Keith Rabois was an early executive at PayPal (part of the famous PayPal Mafia), COO at Square, VP of Corporate Development at LinkedIn, and an early investor in Stripe, DoorDash, Airbnb, YouTube, Ramp, and Palantir. Currently he's managing director at Khosla Ventures. Also, he hasn't touched a computer since September 2010 (he does everything from an iPad).In our in-depth conversation, Keith shares:1. The barrels vs. ammunition hiring framework (and how to spot barrels)2. Why talking to customers is actively harmful for consumer products3. How to identify undiscovered talent4. Why the PM role is dying5. The three traits of the best-performing companies right now6. The specific interview question he asks every senior candidate7. Why CMOs (not engineers) are becoming the #1 consumer of tokens—Brought to you by:WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUsVanta—automate compliance, manage risk, and accelerate trust with AI—Episode transcript: https://www.lennysnewsletter.com/p/hard-truths-about-building-in-the-ai-era—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Keith Rabois:• X: https://x.com/rabois• LinkedIn: linkedin.com/in/keith• Website: https://www.khoslaventures.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Keith Rabois(01:59) Why Keith hasn't used a computer since 2010(04:52) The team you build is the company you build(07:40) How Keith learned to identify talent at PayPal(10:05) Tactics for getting better at hiring(15:31) The barrels vs. ammunition framework(18:52) What makes someone a barrel(22:36) How to attract the best talent(26:18) Building companies on undiscovered talent(27:53) Why better performance requires more pressure(32:36) Career advice in the age of AI(35:14) The future of the product triad(41:03) Why design and code are merging(49:35) What practicing law taught Keith about entrepreneurship(51:22) Contrarian takes on customer feedback(1:02:33) Identifying great AI opportunities(1:05:13) Advice for evaluating statrups (1:12:36) Criticizing in public vs. private(1:15:05) Failure corner(1:17:29) Lightning round—Referenced:• Square: https://squareup.com• Jack Dorsey on X: https://x.com/jack• Head of Claude Code: What happens after coding is solved | Boris Cherny: https://www.lennysnewsletter.com/p/head-of-claude-code-what-happens• Simon Willison's Weblog: https://simonwillison.net• Vinod Khosla on X: https://x.com/vkhosla• Peter Thiel on X: https://x.com/peterthiel• Max Levchin on X: https://x.com/mlevchin• David Sacks on LinkedIn: https://www.linkedin.com/in/davidoliversacks• Tony Xu on X: https://x.com/t_xu• David Sze on X: https://x.com/davidsze• Faire: https://www.faire.com• Max Rhodes on X: https://x.com/MaxRhodesOK• Jeffrey Kolovson on LinkedIn: https://www.linkedin.com/in/jeffreykolovson• Uncapped | Comparative Advantages w/ Keith Rabois: https://www.khoslaventures.com/posts/uncapped-comparative-advantages-w-keith-rabois• Lattice: https://lattice.com• Taylor Francis on LinkedIn: https://www.linkedin.com/in/taylor-francis-4ba49640• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• The art of hiring: insights from Khosla Ventures, Airbnb, Ramp and Traba: https://ramp.com/velocity/the-art-of-hiring-insights• Eric Glyman: Seek out super individual contributors (ICs): https://ramp.com/velocity/the-art-of-hiring-insights#Eric-Glyman:-Seek-out-super-individual-contributors-(ICs)• Eric Glyman on X: https://x.com/eglyman• Mike Moore on LinkedIn: https://www.linkedin.com/in/mike-moore-802223177• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• Why you should work much harder RIGHT NOW: https://marginalrevolution.com/marginalrevolution/2026/03/why-you-should-work-much-harder-right-now.html• Opendoor: https://www.opendoor.com• The Craft of Early Stage Venture | Peter Fenton, General Partner at Benchmark | Uncapped with Jack Altman: https://www.youtube.com/watch?v=vRiblwiXt-Q• Lovable: https://lovable.dev• The rise of the professional vibe coder (a new AI-era job) | Lazar Jovanovic (Professional Vibe Coder): https://www.lennysnewsletter.com/p/getting-paid-to-vibe-code• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (co-founder and CEO): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• Marc Andreessen: The real AI boom hasn't even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom• Jeremy Stoppelman on X: https://x.com/jeremys• The design process is dead. Here's what's replacing it. | Jenny Wen (head of design at Claude): https://www.lennysnewsletter.com/p/the-design-process-is-dead• Andy Warhol: https://en.wikipedia.org/wiki/Andy_Warhol• Curation and Algorithms: https://stratechery.com/2015/curation-and-algorithms• Ernest Hemingway: https://en.wikipedia.org/wiki/Ernest_Hemingway• William Shakespeare: https://en.wikipedia.org/wiki/William_Shakespeare• Evan Moore on X: https://x.com/evancharles• Andrew Mason on X: https://x.com/andrewmason• Read Taylor Swift's Full Viral Speech After Record-Breaking Awards Sweep: https://www.newsweek.com/entertainment/read-taylor-swift-full-acceptance-speech-record-breaking-awards-sweep-11745941• The Chainsmokers: Stories Behind the Songs, AI's Impact on Music, and Venture Investing | Uncapped with Jack Altman: https://www.youtube.com/watch?v=9GMSC-2pYnw&list=PLtpH7YnTL8ihy0nR2BV32n5VkRtqlDAS1&index=16• How to spot a top 1% startup early: https://www.lennysnewsletter.com/p/how-to-spot-a-top-1-startup-early• David Weiden on LinkedIn: https://www.linkedin.com/in/davidweiden• Alfred Lin on LinkedIn: https://www.linkedin.com/in/linalfred• Keith's post about vertical integration on X: https://x.com/rabois/status/870673635375104000• Jon Chu on X: https://x.com/jonchu• Kanu Gulati on X: https://x.com/KanuGulati• Rogo: https://rogo.ai• Profound: https://www.tryprofound.com• Basis: https://www.getbasis.ai• Spellbook: https://www.spellbook.legal• Roelof Botha on X: https://x.com/roelofbotha• Delian Asparouhov on LinkedIn: https://www.linkedin.com/in/delian-asparouhov-87447742• Lessons From Keith Rabois, Essay 1: How to become a Venture Capitalist: https://delian.io/lessons-1• Velocity over everything: How Ramp became the fastest-growing SaaS startup of all time | Geoff Charles (VP of Product): https://www.lennysnewsletter.com/p/velocity-over-everything-how-ramp• Nuremberg on AppleTV+: https://tv.apple.com/us/movie/nuremberg/umc.cmc.3sg4y0382byupy76bfy7307k4• Eight Sleep: https://www.eightsleep.com• “NO DAYS OFF”—Bill Belichick on X: https://x.com/SNFonNBC/status/829036279069364224—Recommended books:• Creativity, Inc.: Overcoming the Unseen Forces That Stand in the Way of True Inspiration: https://www.amazon.com/Creativity-Inc-Overcoming-Unseen-Inspiration/dp/0812993012• The Jordan Rules: The Inside Story of One Turbulent Season with Michael Jordan and the Chicago Bulls: https://www.amazon.com/Jordan-Rules-Sam-Smith/dp/0671796666• The Upside of Stress: Why Stress Is Good for You, and How to Get Good at It: https://www.amazon.com/Upside-Stress-Why-Good-You/dp/1101982934—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

THE PACE IS QUICKENING. YOU HAD TO BE THERE TO BE HERE.WATCH.

Pray the Divine Mercy Chaplet with me for the 3PM hour... the moment the veil was torn. He expired so that we could enter.WATCH TODAY'S VIDEOS! HEADING OUT TO WALK AND RECORD NOW!The Divine Mercy Chaplet PrayersThe Our Father Our Father, who art in heaven, hallowed be Thy name; Thy kingdom come; Thy will be done on earth as it is in heaven. Give us this day our daily bread; and forgive us our trespasses as we forgive those who trespass against us; and lead us not into temptation, but deliver us from evil. Amen. (x1)The Eternal Father Eternal Father, I offer you the Body and Blood, Soul and Divinity of Your Dearly Beloved Son, Our Lord, Jesus Christ, in atonement for our sins and those of the whole world. (x1)The Sorrowful Passion For the sake of His sorrowful Passion, have mercy on us and on the whole world. (x10)Repeat the Eternal Father and Sorrowful Passion prayers for a total of five decades.The Holy God Holy God, Holy Mighty One, Holy Immortal One, have mercy on us and on the whole world. (x3)The Conclusion Jesus, I trust in You! (x3)

Years ago, during my clinical internship at a VA hospital, I worked with a man who had spent most of his adult life in prison. When he was finally released, the vastness of his freedom terrified him so much that his only desire was to go back to his cell. In this episode, we are going to explore why human beings are so deeply wired to choose familiar misery over the terrifying unknown, and how to finally step out of the invisible cages we build for ourselves. New Episode of the Happiness Podcast with Dr. Robert Puff, Ph.D.

Years ago, during my clinical internship at a VA hospital, I worked with a man who had spent most of his adult life in prison. When he was finally released, the vastness of his freedom terrified him so much that his only desire was to go back to his cell. In this episode, we are going to explore why human beings are so deeply wired to choose familiar misery over the terrifying unknown, and how to finally step out of the invisible cages we build for ourselves. New Episode of the Happiness Podcast with Dr. Robert Puff, Ph.D.