Podcasts about 250m

MrBeast's valuation has jumped from $1.5B to around $5B, with Feastables alone bringing in roughly $250M a year. The guys debate whether a creator‑led giant like this goes public, spins off brands like Feastables to players like Hershey, or keeps compounding privately as the ultimate distribution‑first business.

MrBeast's valuation has jumped from $1.5B to around $5B, with Feastables alone bringing in roughly $250M a year. The guys debate whether a creator‑led giant like this goes public, spins off brands like Feastables to players like Hershey, or keeps compounding privately as the ultimate distribution‑first business.

Looking to escape the 9-to-5 grind and build true wealth? In this episode of the Jake & Gino Podcast, we sit down with Jens Nielsen, who immigrated from Denmark in 1996 and successfully transitioned from a 25+ year IT career to full-time real estate investing and high-performance coaching. Today, Jens is a direct owner or General Partner in over 2,000+ apartment units and 100,000+ square feet of industrial assets valued at over $250M. Discover how Jens started with a single $117,000 fourplex in Albuquerque, ran out of his own money, and used creative financing, joint ventures, and syndication to scale a massive commercial real estate portfolio. He also breaks down his recent pivot into industrial real estate, explaining the massive benefits of Triple Net (NNN) leases and small-bay flex spaces. As a Certified High Performance Coach, Jens also dives deep into the 5 pillars of success (Clarity, Energy, Courage, Productivity, and Influence) and shares how a near-fatal mountain bike crash completely shifted his perspective on taking immediate action in life. If you want to decouple your time from your income, master your entrepreneurial mindset, and learn how to navigate today's shifting real estate market, this episode is a must-watch!

How the 90s favorite $4 billion bookstore chain sleepwalked into bankruptcy...

In this episode of The Cannabis Conversation, we sit down with Finn Age Hänsel, Founder and Managing Director of Sanity Group, one of Europe's most influential cannabis companies.Finn shares the remarkable journey behind building Sanity Group into a leader in the European cannabis market, from raising some of the industry's largest investment rounds to navigating Germany's rapidly evolving medical cannabis landscape and ultimately securing a strategic investment from British American Tobacco (BAT) and a landmark acquisition by Organigram.We discuss:

What if the next five years of your career isn't defined by which AI you use, but by who you're working with?In this episode of KP Unpacked, KP Reddy and Nick unpack the quiet revolution happening in management consulting. OpenAI just launched a deployment company and acquired a consulting firm. Anthropic is backing enterprise AI consultancies. PE firms are partnering with AI-enabled consultants and offering equity instead of hourly fees. The result? Three tiers of value capture emerging: billable hours (worst talent), risk-based fees (middle tier), and equity models (where the best people go). If you're still getting paid by the hour to do AI transformation work, you're in the bottom tier.But the deeper insight is about career trajectory. KP argues the next five years aren't defined by how good your Claude skills are. They're defined by who you're sitting next to. Are you in a firm where Opus 4.8 launching makes everyone's Slack light up with memes and excitement? Or are you somewhere people still think AI is a threat? The gap between those two environments is the gap between relevance and obsolescence. The conversation also unpacks skills files as potentially employee-owned IP (not company-owned), why structural engineers still double-check software calculations in Excel despite working for billion-dollar firms, and why Zero's training program spends two-thirds of its time on mental models and thinking frameworks, not AI mechanics.Key questions answered:Why are OpenAI and Anthropic launching consulting practices and partnering with PE firms?What are the three tiers of value capture in AI consulting (billable hours, risk fees, equity)?Where does the best consulting talent go: hourly billing or equity models?Do you own your skills files, or does your company?Should companies make employees sign IP agreements for marketing coordinators building AI workflows?Why do structural engineers still double-check software calculations in Excel?What's Zero's training curriculum focused on: AI tools or thinking frameworks?Why does ambition and optimism matter more than technical AI skill?How should you choose between working at a forward-leaning AI firm versus a traditional one?What happens when Opus 4.8 launches: does your team's Slack light up or stay silent?Why would you sell a $250M/year AI consulting firm when you're banking $50M annually?What's Ramp tracking now: token spend by industry?If you're deciding between firms based on AI adoption, wondering whether your skills files are actually your IP, or trying to figure out whether billable hours still work in an AI-enabled consulting world, this episode will make you realize the technology matters less than the ambition and optimism of the people around you.Listen now.

BONUS S6E7 8 retail trends for 2026 including AI-assisted shoppers, why people are the new luxury, and the grey swans most retailers are ignoringCasey Golden and Ricardo Belmar spent two days at The Lead Summit in New York City with the operators, founders, and analysts actually running retail right now, and they walked out with a clear read on the retail trends 2026 will be built on. Instead of a session-by-session recap, this bonus episode pulls out the eight cross-cutting themes that showed up no matter whose stage they were on, from Anthropologie and Talbots to Hey Dude, Olaplex, Loop, and Coterie.The headline: every AI experiment built to replace people was a failure story, and every one built to extend people was a winner. From there the conversation runs through the rewired store, the rise of the AI-assisted shopper, why human connection is becoming the new luxury, and the grey swan events most retailers can see coming but refuse to plan for. If you want the retail trends 2026 leaders are quietly betting on, plus what to do about it Monday morning, this is the episode.In This Episode, You'll Learn•       Why AI augmentation beats AI replacement, and the customer service "40% ticket deflection" stat that fell apart under real measurement•       How the AI-assisted shopper is already changing product discovery, and why generative engine optimization (GEO) is getting 80% of the attention on 5% of the traffic•       Why "people are the new luxury" may be the one theme still defining retail trends 2026 a year from now•       What Talbots' 35-of-100 transactions stat says about store KPIs beyond sales per square foot•       How community beat audience for breakout brands, and why your brand story now has to teach the LLMs who you are•       The grey swans hiding in plain sight: GLP-1, the aging of America, and single-geography supply chain risk•       The Monday-morning move to make before the AI-assisted shopper takes a bigger bite of your holiday trafficNotable Moments & Quotes•       "AI won't sit down and have a cigarette with me." The line that summed up why people still matter.•       "Listening is a capability, but hearing is a skill."•       Rainbow Shops: a vendor's 40% ticket deflection collapsed because customers just hung up and called back for a human.•       Talbots' Concierge clienteling went from reaching 300,000 of 750,000 eligible customers to all of them, while keeping the calls human. AI does the volume, people do the moments.•       Loop Earplugs grew from $1M to $250M in five years, obsessing over one question: where did you first hear about us?•       MoMA Design Store: "We're not Amazon, and we don't want to be."•       Randa Apparel's grey swans: GLP-1 (roughly 8M users today, potentially 100M by 2030), more Americans over 65 than under 18 by 2028, and the warning that "a business built around a single geography isn't lean, it's exposed."Subscribe & FollowIf you enjoyed this episode, please leave us a 5‑star rating and review on Apple Podcasts, Spotify, or Goodpods. Subscribe on YouTube so you never miss an episode and check out the other shows in the Retail Razor Podcast Network: Retail Transformers, Blade to Greatness, and Data Blades.Subscribe to the Retail Razor Podcast Network: https://retailrazor.com/Subscribe to our Newsletter: https://retailrazor.substack.comSubscribe to our YouTube channel: https://go.retailrazor.com/utubeChapters00:00 Teaser01:01 Show Intro03:18 The BIG Recap - Our 8 Themes form The Lead Summit05:49 Theme 1 - The Augmentation Imperative09:49 Theme 2 -  People are the New Luxury14:17 Theme 3 - The Rewired Store18:40 Theme 4 - Get Ready for the AI-Assisted Shopper24:19 Theme 5 - Community Over Audience30:57 Theme 6 - Brand Discipline and the Power of Saying No35:22 Theme 7 - Multiplatform & Multigenerational Reality40:23 Theme 8 - Grey Swans: The Conversations Most People Aren't Having45:39 Key Take Aways: What Should Listeners Do Monday Morning?48:53 Show CloseMeet your hostsHelping you cut through the clutter in retail & retail tech:Ricardo Belmar is an NRF Top Retail Voice for 2025 and a RETHINK Retail Top Retail Expert from 2021 – 2026. Thinkers 360 has named him a Top 10 Thought Leader in Retail, a Top 25 Thought Leader in AGI and Careers, a Top 50 Thought Leader in Agentic AIand Management, and a Top 100 Thought Leader in Digital Transformation and Transformation. Thinkers 360 also named him a Top Digital Voice for 2024 and 2025. He is an advisory council member at George Mason University's Center for Retail Transformationand the Retail Cloud Alliance. He was most recently the partner marketing leader for retail & consumer goods in the Americas at Microsoft.Casey Golden, is the North America Leader for Retail & Consumer Goods at CI&T, and CEO of Luxlock. She is a RETHINK Retail Top Retail Expert from 2023 - 2026, and Retail Cloud Alliance advisory council member. After a career on the fashion and supply chain technology side of the business, Casey is obsessed with the customer relationship between the brand and the consumer and is slaying franken-stacks and building retail tech! MusicIncludes music provided by imunobeats.com, featuring Overclocked, and E-Motive from the album Beat Hype, written by Heston Mimms, published by Imuno.

TaylorMade golf swaps to a 2 cycle to focus more on design, production, and performance. Will it work? Only time will tell! Cleveland Golf has some of the best wedges in the game, but which ones should you play? Aaron Rai won with an interesting set of clubs to say the least. Last but not least, would you save LIV Golf for 250M? Cleveland Golf: https://bit.ly/4dvrPuQ 00:00 Welcome back 02:55 Aaron Rai - WITB 12:47 TaylorMade's 2 year cycle 24:09 Bridgestone's New "Black Ball" 28:23 Tilteist GTS 49:20 Giving LIV 250M?

The zero-human company with the $10 million run rate has a lot of skeptics online. I collected all the skeptics' challenges and asked the founder about each one. This is my explosive second interview with Ben Cera, founder of Polsia, the company that will build you an AI-run company. Ben Cera is the founder of Polsia, an AI platform that helps users launch businesses and software products using autonomous agents. Before Polsia, Ben built and sold startups in the creator and consumer internet space, and later raised significant venture funding to pursue AI-native products. Today, Polsia combines AI agents, infrastructure partners, and automation tools to make entrepreneurship accessible to non-technical users. Sponsored byZapier More interviews -> https://mixergy.com/moreint Rate this interview -> https://mixergy.com/rateint

Stord offers a network of physical warehouses and inventory management software for e-commerce. It bills itself as a sort of anti-Amazon, giving brands "the speed to compete" while still owning their customer relationships. Also, OpenRouter has raised a $113 million Series B led by CapitalG. Its 5x growth in usage over six months indicates the multi-AI-model future is here. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Plus - Amazon fulfillment competitor Stord raises $250M at $3B valuation Learn more about your ad choices. Visit podcastchoices.com/adchoices

Polsia (AI Slop spelled backwards) just announced a $30M raise at a $250M valuation with one human employee. David thinks it's less a company, more performance art. Plus: Uber, Microsoft and NVIDIA all admit AI compute is too expensive, and Tether is launching what looks like a CBDC with the government of Georgia. Enjoy! TIMESTAMPS: (00:00) Intro (01:28) Polsia (06:22) Nexo Ad (06:57) Polsia (Cont.) (16:10) Nexo Ad (17:04) Polsia (Cont.) (18:29) AI Compute Costs (27:15) Tether FOLLOW THE SHOW › David — https://x.com/dcanellis › The Breakdown — https://x.com/TheBreakdownBW SPONSORS › NEXO Nexo is the premier digital wealth platform. Receive interest on your crypto, borrow against it without selling, and trade a range of assets. Now available in the U.S with 30 days of exclusive privileges. Get started at http://nexo.com/breakdown Get top market insights and the latest in crypto news. Subscribe to the Blockworks Daily Newsletter: https://blockworks.co/newsletter/ DISCLAIMER As always, remember this podcast is for informational purposes only, and any views expressed by anyone on the show are solely their opinions, not financial advice.

In this episode, we kick things off by examining a massive late-stage funding round that's positioning a fast-growing logistics specialist to take on Amazon's e-commerce dominance. Atlanta-based Stord announced it has raised $250 million in Series F venture capital funding that values the company at $3 billion, doubling its valuation in just twelve months. The new funds will go towards launching Stord Labs, a development hub aimed at rapidly building and deploying agentic AI, robotics and advanced automation by leveraging data from real orders coming through the company's live operating system. Meanwhile, a Texas jury has handed down a staggering nuclear verdict against a trucking company that may no longer even be in business. Last week in Ector County, Texas, a jury awarded $49 million against Texas-based carrier OPG Logistics and driver Biorkys Sanchez Fernandez following a January 2025 crash that killed 29-year-old Steffan Mick. The attorney for OPG reportedly said the company was no longer in business even as a defense was mounted, and with a defendant whose very existence is in doubt, the massive question remains just how much the Mick family will ultimately be able to collect. Finally, we cover a major leadership move at a smart trailer technology company that signals the freight industry's fundamental shift toward connected and autonomous operations. California-based Phillips Connect announced that Mark Wallin, the principal architect of its technical roadmap and customer strategy, has been named president and general manager. Wallin joined Phillips Connect in January 2024 as general manager and senior vice president of product, and has spent the past eighteen months reshaping how the company approaches the market by expanding platform capabilities while lowering barriers to adoption. Follow the FreightWaves NOW Podcast Other FreightWaves Shows Learn more about your ad choices. Visit megaphone.fm/adchoices

El episodio 117 llegó con números que no se pueden creer y drama en las grandes ligas del tech. Leopold Aschenbrenner tiene 24 años, convirtió 250 millones en 5.5 billones en un solo año apostando a la infraestructura de AI. Ahora hizo el giro que nadie esperaba: apostó contra Nvidia, Oracle y TSMC con puts masivos. Su mensaje es claro — el mercado está a punto de explotar. SpaceX presentó su S1. Musk se declaró CEO de por vida con el 85% de los votos y solo pone el 5% de la compañía en el mercado. El IPO más esperado de la historia se viene en junio. Anthropic está cerca de los 50 billones de revenue este quarter, camino a ser rentable, y acaba de reclutar a un co-founder clave de OpenAI. Mientras tanto, la CFO de OpenAI se niega a falsificar los números para su propio IPO. Y de yapa: Peter Thiel jugando ajedrez en un club de barrio de Buenos Aires y la bomba legal de Anthropic contra los SPVs de secundarios que tiene a medio mercado en pánico. __Links del episodio:Peter Thiel:https://x.com/somoscorta/status/2056064226033127752?s=20https://x.com/lex_node/status/2053845294731641076?s=20The price of time: www.goodreads.com/book/show/61241469-the-price-of-time__Tenes alguna pregunta? Escribinos y seguinos en:Twitter: @CristobaPerdomo y @llopatinLinkedin: Lucas Lopatin y Cristobal Perdomo yVisitá:Indie BuildWollef

Subscribe to DTC Newsletter - https://dtcnews.link/signupCharlie Cole watched FTD go from a $1.8 billion publicly traded company to a $60 million bankruptcy auction in eight months. His first day as CEO was March 23, 2020, the first day of national lockdown.Before that he ran digital at Tumi, Samsonite, Lucky Brand, and Shift Nutrition. Today he's interim Chief Digital Officer at Thuma.This episode is a tactical sit-down on what actually drives growth right now in a Meta + AI world.In this episode:Why "creative is the new targeting" is only half the answerThe exact death spiral most DTC brands follow on the way to margin collapse (no sale, semi-annual sale, sale page, sitewide 20%, Amazon, done)How Charlie engineered personas at FTD across customer, consumer, and eventThe florist's choice insight: highest NPS in the category, by 20-40%The 2011 Dr. Oz campaign that nailed funnel congruency before anyone called it thatWhy personalization was a misnomer until about two years agoThe three "swimsuit for vacation" shoppers who should never see the same pageWhy YouTube is still massively underutilized, and why most brands run it wrongThe product question that decides whether any of this mattersWho it's for: DTC founders and operators scaling from $10M to $250M who want to grow without turning their brand into a discount machine.What to steal:Build acquisition around your highest-LTV segments, not your lowest CACTreat creative and landing pages as one system, not two teamsStop letting platforms grade their own homework on attributionAudit where you sit on the discount death spiral before it owns youTimestamps:0:00 Career Journey Into Ecommerce2:48 Inside the FTD Turnaround14:20 How Customer Behavior Changed During COVID23:18 Creative Is The New Targeting36:05 AI's Biggest Ecommerce Unlock43:02 Why Most Brands Test Creative WrongSubscribe to DTC Newsletter - https://dtcnews.link/signupAdvertise on DTC - https://dtcnews.link/advertiseWork with Pilothouse - https://dtcnews.link/pilothouseFollow us on Instagram & Twitter - @dtcnewsletterWatch this interview on YouTube - https://dtcnews.link/video

On today's episode, Andy & DJ break down President Trump moving to oust Republican Thomas Massie, Vickrum Digwa telling the court he was racially abused by Henry Nowak before the fatal stabbing, and the shocking case of a Midwest mother tied to a massive $250 million Somali fraud scheme receiving her prison sentence.

What happens when AI marketing moves faster than the technology itself? In this episode, we unpack Apple's proposed $250 million settlement over claims that it overstated the availability of “Apple Intelligence” features tied to the iPhone 16 launch, including ads suggesting advanced Siri capabilities were “Available Now” even though some features would not arrive until later software updates. The case—following both an NAD challenge and multiple consolidated class actions—highlights the growing legal scrutiny around AI advertising, substantiation, and product availability claims, sending a clear warning to companies eager to promote future-facing AI capabilities before they are fully market-ready. Hosted by Simone Roach. Based on a blog post by Gonzalo E. Mon.

BE HARD TO CONVICT if you're ever compelled to use force in defense of yourself, your family, or your property! FREE WEBINAR! Saturday, April 25! FREE but you MUST REGISTER NOW: hardtoconvict.comFor complete Medicare guidance, dial (617) 644-0093 to speak with my trusted partner, Chapter.All @TheBrancaShow mugs! https://tinyurl.com/k778wj2kJOIN OUR COMMUNITY! Exclusive Members-only content & perks! Only ~17 cents/day! $5/month! YouTube: https://tinyurl.com/hn32rfz9 Locals: https://tinyurl.com/yck4w9kfFOUNDING FATHERS SPEED DIAL: Founding Fathers SPEED DIAL: https://tinyurl.com/3f7pc8nzTODAY's MEMBERS-ONLY SHOW: “DOJ Insider Exposes 16 Years of Political Takeover”YouTube: https://tinyurl.com/sd6n4bwjLocals: https://tinyurl.com/mrx49dbrFBI Director Kash Patel has filed a $250 million defamation lawsuit against The Atlantic over a hit piece packed with explosive claims — excessive drinking, missed meetings, a security team unable to wake him — and sourced almost entirely by anonymous officials hiding behind the reporter's promise of confidentiality. The article cites "more than two dozen" people, grants all of them anonymity, and names exactly zero of them. Not one person willing to put their name behind what they told the journalist. If the story is true and Patel is the disaster they're describing, you'd think at least one of those two dozen people would stand up and say so publicly. Instead, we get a wall of shadows. That's not journalism. That's a drive-by.Now, I want to be straight with you about what Patel is actually up against, because this lawsuit — however satisfying it may feel — faces a serious legal obstacle. Patel is a public official, which means he can't win a defamation case just by proving the story is false. Under the New York Times v. Sullivan standard, he has to prove actual malice — that The Atlantic either knew the claims were false when they published them, or acted with reckless disregard for whether they were true or false. That is a brutally high bar, and it's the bar that has killed more defamation suits against media organizations than almost anything else.So here's the question we're going to dig into today: does the complete absence of named, accountable sources — combined with the FBI's on-record denials before publication — give Patel enough to argue reckless disregard? We'll walk through the lawsuit, the legal standard, and what it's actually going to take for Patel to win this thing.Join me LIVE at 11 AM ET as I break it all down!Episode #1297.

Recording artist and Broadway sensation Kelsie Watts joins The I Dare You Podcast for a candid conversation about what it really takes to build a career that lasts—onstage and online. Kelsie is making waves again with new original music, including her latest release “Made for Your Love,” and has become a viral singing phenomenon with 250M+ views and 3.5M+ followers across TikTok and Instagram. In this episode, she takes us behind the curtain on her journey from Lubbock, Texas (singing in church and studying music) to Belmont University in Nashville, to grinding through the “unseen years” that most people never hear about. We talk about: Why “overnight success” is a myth The creative story behind “Made for Your Love” and Kelsie's Whitney Houston inspiration How understanding the business of music matters as much as talent The Broadway reality: Kelsie's run as Queen Jane Seymour in SIX! The Musical (including her iHeartRadio Music Award nomination for Favorite Broadway Debut) and what it's like to step into high-pressure roles live The message behind her acclaimed single “Fit In”—and why comparison is “the thief of joy” The power of authenticity, preparation, and staying coachable after hearing “no” Plus, Kelsie shares her simple “I Dare You” challenge—one small act that can change someone's day. Follow Kelsie: @kelsiewatts (TikTok) | @kelsiewattsmusic (Instagram) Listen to her music everywhere you stream. Remember, as discussed in E218, grab your FREE, custom-designed PDFs (inspired by Start With Why by Simon Sinek) at idareyoupod.com: 5 “Why discovery” questions Daring Purpose Tool (Belief → Action → Results → One sentence) Start With Why Visual Synopsis (WHY / HOW / WHAT + trust + consistency)

Anthony Perera is a South Florida-born serial entrepreneur who transformed a single HVAC truck into a $200M+ national home services empire, earned Ernst & Young's Entrepreneur of the Year® Florida award, successfully scaled and sold a majority stake in his tech company Inspected.com to a private equity fund managing over $600M, and now leads a family office overseeing a portfolio valued at more than $250 million. Here's some of the topics we covered: From off-road magazines to serial entrepreneurship Turning one HVAC truck into a $250M powerhouse Building a family office around buying businesses The hidden opportunity in retiring baby boomer companies Transforming outdated businesses into private equity targets How AI and social media are changing growth forever The playbook for buying businesses and scaling wealth   To find out more about partnering or investing in a multifamily deal: Text Partner to 72345 or email Partner@RodKhleif.com    For more about Rod and his real estate investing journey go to www.rodkhleif.com   Please Review and Subscribe  

Pre-show: Project Hail Mary Reconcilable Differences #286: Ain’t Nothin’ Gonna Break My Stride Setlist Bandcamp Luke Bloom — Bad D. H. T. — Listen to Your Heart Apocalyptica Vitamin String Quartet Johnny Cash — Hurt Follow-up: CapEx vs. OpEx (via Andrew Leahey) Bloomberg “Hot lot” (via Anonymous & Matt Jones) Ultra/Neo/etc Is the “iPhone Ultra” the 20th anniversary iPhone? (via Janne Ojaniemi) Did we forget about “Studio”? (via Karan J) What’s the ∆ between an iMac Neo and a Studio Display? (via Zoran Nešić) Time Machine …with lots of small files (via Jon Wilson & Andrew Hathaway) Asimov …with spinning disks (via Ben Mattison & Carlos Pereira) …period (via David Fokkema) lsof Apple agrees to pay iPhone owners $250M for fumbling AI Siri Apple is flirting with Intel and Samsung Apple’s Newsroom post about US manufacturing Apple and Intel have reached an agreement? (Apple News+ link) Ask ATP: How do we actually move files around our Macs? (via Brandon Whichard) Yoink MD5 Do we use a profile/theme for Terminal windows? (via Chris Harper) Prompt 3 Do we use any other IDEs? (also via Chris Harper) LSP Intelephense Post-show: .nofollow Apple developer forum post Symlink .nosync, .noindex, .nobackup Hopper MJ Tsai Apple open-source Swift SE-0529: Add FilePath to the Standard Library Safe Path Handling: Why Secure Filesystem Operations Are Harder Than You Think Members-only ATP Overtime: Non-developers building apps Ben Dansby Sponsored by: Squarespace: Save 10% off your first purchase of a website or domain using code atp. Zapier: Put AI to work across your company—for real. Quince: Elevated essentials and staples that last. Become a member for ATP Overtime, ad-free episodes, member specials, and our early-release, unedited “bootleg” feed!

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

If you purchased an iPhone between June 2024 and March 2025, you could receive a payment from the $250 million settlement over Apple's intelligence features on iPhones! Apple could be using Intel chips again in future Apple products. More Mac mini and Mac Studio models are no longer available on the Apple Store. And Apple is now requiring verification for education discounts. US Supreme Court declines to pause order holding Apple in contempt in Epic Games lawsuit. iPhone users could get up to $95 per device as Apple reaches $250M settlement over Siri delays Apple reportedly has a deal to use Intel-made chips again. Intel's stock jumped 13% today over Apple chip manufacturing report Additional Mac mini and Mac Studio models cut from the Apple Store website as AI data centers strain available RAM, SSD supplies Apple requires verification for education discounts, ENDS discounts for k-12 unless you're homeschooled. Tim Cook among CEOs confirmed for President Trump's China trip. More refunds possible for Apple as Trump's 10% global tariffs found illegal too. Apple releases tvOS 26.5, HomePod 26.5, and visionOS 26.5. Apple to make design changes in macOS 27 to address Tahoe quirks. Here's how I finally got Google's uninvited 4GB AI model off my Mac. macOS 27 threatens to bury Time Capsule, FOSS brings a shovel. Apple kicks off new run of A18 Pro chips as MacBook Neo demand exceeds expectations. Not dead yet: Apple Vision still has a future. visionOS 27 will bring these new Vision Pro upgrades. The $1 Steve Jobs coin. Google denies copying Apple's Liquid Glass design for Android. You can purchase Apple's Mac Pro wheels kit for $699. Picks of the Week Leo's Pick: whatcable Christina's Pick: Obsidian's Plugin Site Andy's Pick: Snapseed Photo Editor Jason's Picks: Indigo & Gnome Hosts: Leo Laporte, Andy Ihnatko, Jason Snell, and Christina Warren Download or subscribe to MacBreak Weekly at https://twit.tv/shows/macbreak-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zocdoc.com/macbreak scribe.how/macbreak

If you purchased an iPhone between June 2024 and March 2025, you could receive a payment from the $250 million settlement over Apple's intelligence features on iPhones! Apple could be using Intel chips again in future Apple products. More Mac mini and Mac Studio models are no longer available on the Apple Store. And Apple is now requiring verification for education discounts. US Supreme Court declines to pause order holding Apple in contempt in Epic Games lawsuit. iPhone users could get up to $95 per device as Apple reaches $250M settlement over Siri delays Apple reportedly has a deal to use Intel-made chips again. Intel's stock jumped 13% today over Apple chip manufacturing report Additional Mac mini and Mac Studio models cut from the Apple Store website as AI data centers strain available RAM, SSD supplies Apple requires verification for education discounts, ENDS discounts for k-12 unless you're homeschooled. Tim Cook among CEOs confirmed for President Trump's China trip. More refunds possible for Apple as Trump's 10% global tariffs found illegal too. Apple releases tvOS 26.5, HomePod 26.5, and visionOS 26.5. Apple to make design changes in macOS 27 to address Tahoe quirks. Here's how I finally got Google's uninvited 4GB AI model off my Mac. macOS 27 threatens to bury Time Capsule, FOSS brings a shovel. Apple kicks off new run of A18 Pro chips as MacBook Neo demand exceeds expectations. Not dead yet: Apple Vision still has a future. visionOS 27 will bring these new Vision Pro upgrades. The $1 Steve Jobs coin. Google denies copying Apple's Liquid Glass design for Android. You can purchase Apple's Mac Pro wheels kit for $699. Picks of the Week Leo's Pick: whatcable Christina's Pick: Obsidian's Plugin Site Andy's Pick: Snapseed Photo Editor Jason's Picks: Indigo & Gnome Hosts: Leo Laporte, Andy Ihnatko, Jason Snell, and Christina Warren Download or subscribe to MacBreak Weekly at https://twit.tv/shows/macbreak-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zocdoc.com/macbreak scribe.how/macbreak

If you purchased an iPhone between June 2024 and March 2025, you could receive a payment from the $250 million settlement over Apple's intelligence features on iPhones! Apple could be using Intel chips again in future Apple products. More Mac mini and Mac Studio models are no longer available on the Apple Store. And Apple is now requiring verification for education discounts. US Supreme Court declines to pause order holding Apple in contempt in Epic Games lawsuit. iPhone users could get up to $95 per device as Apple reaches $250M settlement over Siri delays Apple reportedly has a deal to use Intel-made chips again. Intel's stock jumped 13% today over Apple chip manufacturing report Additional Mac mini and Mac Studio models cut from the Apple Store website as AI data centers strain available RAM, SSD supplies Apple requires verification for education discounts, ENDS discounts for k-12 unless you're homeschooled. Tim Cook among CEOs confirmed for President Trump's China trip. More refunds possible for Apple as Trump's 10% global tariffs found illegal too. Apple releases tvOS 26.5, HomePod 26.5, and visionOS 26.5. Apple to make design changes in macOS 27 to address Tahoe quirks. Here's how I finally got Google's uninvited 4GB AI model off my Mac. macOS 27 threatens to bury Time Capsule, FOSS brings a shovel. Apple kicks off new run of A18 Pro chips as MacBook Neo demand exceeds expectations. Not dead yet: Apple Vision still has a future. visionOS 27 will bring these new Vision Pro upgrades. The $1 Steve Jobs coin. Google denies copying Apple's Liquid Glass design for Android. You can purchase Apple's Mac Pro wheels kit for $699. Picks of the Week Leo's Pick: whatcable Christina's Pick: Obsidian's Plugin Site Andy's Pick: Snapseed Photo Editor Jason's Picks: Indigo & Gnome Hosts: Leo Laporte, Andy Ihnatko, Jason Snell, and Christina Warren Download or subscribe to MacBreak Weekly at https://twit.tv/shows/macbreak-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zocdoc.com/macbreak scribe.how/macbreak

If you purchased an iPhone between June 2024 and March 2025, you could receive a payment from the $250 million settlement over Apple's intelligence features on iPhones! Apple could be using Intel chips again in future Apple products. More Mac mini and Mac Studio models are no longer available on the Apple Store. And Apple is now requiring verification for education discounts. US Supreme Court declines to pause order holding Apple in contempt in Epic Games lawsuit. iPhone users could get up to $95 per device as Apple reaches $250M settlement over Siri delays Apple reportedly has a deal to use Intel-made chips again. Intel's stock jumped 13% today over Apple chip manufacturing report Additional Mac mini and Mac Studio models cut from the Apple Store website as AI data centers strain available RAM, SSD supplies Apple requires verification for education discounts, ENDS discounts for k-12 unless you're homeschooled. Tim Cook among CEOs confirmed for President Trump's China trip. More refunds possible for Apple as Trump's 10% global tariffs found illegal too. Apple releases tvOS 26.5, HomePod 26.5, and visionOS 26.5. Apple to make design changes in macOS 27 to address Tahoe quirks. Here's how I finally got Google's uninvited 4GB AI model off my Mac. macOS 27 threatens to bury Time Capsule, FOSS brings a shovel. Apple kicks off new run of A18 Pro chips as MacBook Neo demand exceeds expectations. Not dead yet: Apple Vision still has a future. visionOS 27 will bring these new Vision Pro upgrades. The $1 Steve Jobs coin. Google denies copying Apple's Liquid Glass design for Android. You can purchase Apple's Mac Pro wheels kit for $699. Picks of the Week Leo's Pick: whatcable Christina's Pick: Obsidian's Plugin Site Andy's Pick: Snapseed Photo Editor Jason's Picks: Indigo & Gnome Hosts: Leo Laporte, Andy Ihnatko, Jason Snell, and Christina Warren Download or subscribe to MacBreak Weekly at https://twit.tv/shows/macbreak-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zocdoc.com/macbreak scribe.how/macbreak

Genspark went from AI search startup to autonomous AI agent platform, hitting $250M ARR in 12 months with no paid ads until they bought a Super Bowl spot. Co-founder and COO Wen Sang joins Corey and Grant to explain what "AI employee" actually means, demos Genspark Claw live (including buying us coffee mid-interview), and lays out his big thesis: legacy software is becoming infrastructure while AI agents become the new interface between humans and work. We get hands-on with Workspace 4.0, Claw, and a custom agent built live for the show.• Genspark Workspace 4.0 announcement: https://www.genspark.ai/blog/genspark-ai-workspace-4• Genspark sb-git: https://genspark.ai/sb-git/intro• OpenAI's customer story on Genspark: https://openai.com/index/genspark/• Forbes AI 50 (2026): https://www.forbes.com/lists/ai50/• Marc Benioff on Salesforce Headless 360 (referenced by Wen): https://x.com/Benioff • Andrej Karpathy's "wiki for agents" idea (referenced as inspiration for sb-git): https://x.com/karpathy• Wen on the DealMaker Show: https://alejandrocremades.com/wen-sang/Try Genspark for free: https://genspark.aiSubscribe to The Neuron newsletter: https://theneuron.ai

If you purchased an iPhone between June 2024 and March 2025, you could receive a payment from the $250 million settlement over Apple's intelligence features on iPhones! Apple could be using Intel chips again in future Apple products. More Mac mini and Mac Studio models are no longer available on the Apple Store. And Apple is now requiring verification for education discounts. US Supreme Court declines to pause order holding Apple in contempt in Epic Games lawsuit. iPhone users could get up to $95 per device as Apple reaches $250M settlement over Siri delays Apple reportedly has a deal to use Intel-made chips again. Intel's stock jumped 13% today over Apple chip manufacturing report Additional Mac mini and Mac Studio models cut from the Apple Store website as AI data centers strain available RAM, SSD supplies Apple requires verification for education discounts, ENDS discounts for k-12 unless you're homeschooled. Tim Cook among CEOs confirmed for President Trump's China trip. More refunds possible for Apple as Trump's 10% global tariffs found illegal too. Apple releases tvOS 26.5, HomePod 26.5, and visionOS 26.5. Apple to make design changes in macOS 27 to address Tahoe quirks. Here's how I finally got Google's uninvited 4GB AI model off my Mac. macOS 27 threatens to bury Time Capsule, FOSS brings a shovel. Apple kicks off new run of A18 Pro chips as MacBook Neo demand exceeds expectations. Not dead yet: Apple Vision still has a future. visionOS 27 will bring these new Vision Pro upgrades. The $1 Steve Jobs coin. Google denies copying Apple's Liquid Glass design for Android. You can purchase Apple's Mac Pro wheels kit for $699. Picks of the Week Leo's Pick: whatcable Christina's Pick: Obsidian's Plugin Site Andy's Pick: Snapseed Photo Editor Jason's Picks: Indigo & Gnome Hosts: Leo Laporte, Andy Ihnatko, Jason Snell, and Christina Warren Download or subscribe to MacBreak Weekly at https://twit.tv/shows/macbreak-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zocdoc.com/macbreak scribe.how/macbreak

What does it actually take to build a 3M+ personal brand while running a $250M company? In this episode, Natalie sits down with Leila Hormozi - COO of Acquisition.com - to break down the playbook for personal brand: how Leila built one of the top personal brands without making it her full-time job, why deprioritizing content was the move that finally made her brand compound, and the practical content systems (including how she really uses AI) that let her ship without burning out. Expect specific numbers, a counter-discourse case for personal brand in the AI era, and a content "double dip" framework you can install this week. If you've ever wondered whether building a personal brand is even worth it in 2026, or you're a founder trying to figure out how to ship content without it taking over your life, this episode is the operating system. Time Stamps: 00:00 - The personal brand strategy that grew 3M+ followers  01:43 - Why content compounded after she stopped trying so hard 06:24 - The mentor's "ham and garlic" rule for packaging 09:35 - Why your niche is "one of one" — the anti-niching case 15:36 - The AI rule that separates real brands from AI slop 18:50 - Why personal brand is MORE valuable in the AI era 24:15 - Inside the first 100% AI-driven sale at Acquisition.com 29:17 - The doubling-constraint scaling lens for personal brand 35:51 - The newsletter she built without writing a single word Resources + Links: Follow Leila Hormozi On Instagram: https://www.instagram.com/leilahormozi  Leila's Letters Newsletter: leilahormozi.com Pre-Order The Freedom-Based Business Method. Sign Up For Our Free Weekly Newsletter & Get Insights From Natalie Every Single Week On All Things Strategy, Motherhood, Business Growth + More. Drop Us A Review On The Podcast + Send Us A Screenshot & We'll Send You Natalie's 7-Figure Operating System Completely FREE (value $1,997).

Spencer Vickers began his career at Invesco Real Estate, working across industrial, retail, and multifamily assets on their U.S. platform. He then moved into healthcare real estate acquisitions and development for a group in Dallas before serving as senior analyst at D.R. Horton's multifamily platform in Central Florida. In June 2024, Spencer founded The Fractional Analyst to give independent syndicators and fund managers access to institutional-grade back office support, deal analysis, and investor reporting systems without the overhead of a full-time hire. His team serves clients ranging from individual operators to groups with up to $2 billion in assets under management.     Make sure to download our free guide, 7 Questions Every Passive Investor Should Ask, here.     Key Takeaways Build back office systems before you need them Use financial modeling to tell a clear deal story, not just present numbers Analyze new supply and absorption trends alongside any target acquisition Source market data from county permits, active brokers, and AI tools Avoid assuming that what got you to your current level will carry you to the next     Topics The Institutional Gap in Real Estate Large operators have dedicated analyst, transaction, and debt teams that most independent operators cannot afford The Fractional Analyst fills that gap by building back office systems, financial models, and investor relations infrastructure for smaller operators What Back Office Support Actually Covers Back office work includes lender reporting, investor distributions, subscription documents, and K-1 management Platforms like Cash Flow Portal and Juniper Square automate much of this, but still require setup, data validation, and ongoing upkeep Financial Modeling and Deal Presentation Many models lack formatting, clarity, and readability, making them difficult to audit or present Spencer's team cleans up models and builds pitch decks that make the deal story easy to communicate to lenders and investors Underwriting With Market Context New supply and absorption trends must be analyzed alongside any target acquisition to properly frame risk A 97% occupied deal can still carry significant risk if thousands of competing units are coming online in the same submarket Finding Market Data County permit records reveal planned new construction in any given area Active local brokers typically already have this data and are motivated to share it AI tools are increasingly useful for pulling and presenting market data, but all outputs require verification before use Who Is a Good Fit for The Fractional Analyst Ideal clients have $50M to $250M in assets under management and are actively looking to scale Operators who are not yet acquiring deals or are unwilling to do the required work are not a strong match Scaling From Syndications to Funds Spencer's team reviewed fund formation documents for a client with over 300 individual syndications preparing to launch his first fund They flagged legal risk items so the client could address them directly with his attorney    

Patrick Forquer is the Chief Revenue Officer at Legora, the fastest growing enterprise business to ever hit $100M in ARR and now on track to hit over $250M in ARR by the end of the year. They recently raised a $550 million Series D at a $5.55 billion valuation, led by Accel, note 20VC did participate and is an investor in the company.  AGENDA: 0:00 – How Jude Law Generated $50 Million in Qualified Pipeline 4:00 – Why Implementation is Your Secret Weapon to Win in AI 5:50 – Why AI Enterprise Sales Require "Legal Engineers" 7:45 – The 6-Figure Rule: When Should Humans Control Sales 12:55 – Is Legora Vastly Overvalued at $5.5BN?  15:45 – How to do global expansion in a world of AI 18:00 – How to Win Supremely Competitive Markets 24:45 – Why Giving Your Product Away for Free is a Death Sentence 33:55 – Legora's Onboarding and Training Playbook for Sales Teams 38:25 – Spotting Red Flags: How to Know if a Sales Rep Will Fail in 45 Days 46:30 – How to Structure Sales Commissions in a World of AI 49:40 – How to do Revenue Forecasting in a World of AI 1:00:30 – Will companies vibe code solutions and no longer buy a SaaS products?    

On today's MadTech Daily, we cover OpenAI expanding ChatGPT ads globally as The Trade Desk's CSO joins the company, Meta taking Ofcom to court over online safety penalties, and Apple agreeing to a USD$250m payout over Siri AI misrepresentation.

In FOLLOW UP, the guys marvel at the completely normal state of America as Amnesty International issues a travel advisory for the 2026 World Cup because apparently “visiting the United States” now comes with the same vibe as backpacking through a failed cyberpunk state. Then it's onto Dead Podcast Theory, where more than a third of all new podcasts are AI-generated “podslop,” proving Silicon Valley heard “everyone has a podcast” and responded with “what if nobody did?” Meanwhile, Ticketmaster reminds everyone that if you've purchased a concert ticket since 2010, there's probably a class action settlement with your name on it and enough compensation for half a convenience fee.IN THE NEWS is basically one long panic attack sponsored by AI. The White House is considering regulating AI models, Canada says OpenAI vacuumed up everyone's personal data like a drunk Roomba, Character.AI allegedly impersonated a licensed psychiatrist, and Mother Jones found ChatGPT still happily helping aspiring mass shooters workshop their plans. Snap's Perplexity deal died quietly in a ditch while Meta keeps assembling humanoid robots like it's building the world's most annoying version of Westworld. Then GameStop tries to buy eBay in the dumbest sentence ever typed, Ryan Cohen gets himself banned from eBay while trying to meme-finance the deal, Elon Musk settles with the SEC for pocket lint money, Coinbase fires people because “AI,” Toto accidentally becomes a semiconductor giant through toilet technology, and smart glasses officially evolve from creepy gadget to extortion accessory.MEDIA CANDY brings some relief with Daredevil: Born Again and Widow's Bay. The Academy finally decides AI-generated actors and scripts can't win Oscars, which feels like the bare minimum required to stop ChatGPT from getting Best Supporting Actor before Willem Dafoe.In APPS & DOODADS, Pornhub returns to the UK thanks to Apple's age verification system, Ask.com finally dies and takes Jeeves with it into the great dial-up tone in the sky, and Apple agrees to pay users because “Apple Intelligence” arrived somewhere between vaporware and wishful thinking.Finally, THE DARK SIDE WITH DAVE tackles the true meaning of “decimate,” AI-powered C-3PO heads, mechanical keyboards for grown men who refuse to use laptop keys, Maul: Shadow Lord, The Boys, and a reminder that Solo was a great movie, grocery store adventures, lost AirPods, and the eternal mystery of why middle-aged dudes become furries. Because at this point, why not?Sponsors:DeleteMe - Get 20% off your DeleteMe plan when you go to JoinDeleteMe.com/GOG and use promo code GOG at checkout.Private Internet Access - Go to GOG.Show/vpn and sign up today. For a limited time only, you can get OUR favorite VPN for as little as $2.03 a month.SetApp - With a single monthly subscription you get 240+ apps for your Mac. Go to SetApp and get started today!!!1Password - Get a great deal on the only password manager recommended by Grumpy Old Geeks! gog.show/1passwordShow notes at https://gog.show/745Watch on YouTube at https://youtu.be/0P9rgRrL4-QFOLLOW UP2026 World Cup Travel AdvisoryMore Than a Third of All New Podcasts Are AI-GeneratedWelcome to the Ticketmaster Fee Class Action WebsiteIN THE NEWSThe White House is considering tighter regulation of new AI modelsCanadian officials claim OpenAI violated federal and provincial privacy lawsPennsylvania sues Character.AI after a chatbot allegedly posed as a doctorEven After Two Massacres, OpenAI Still Hasn't Stopped ChatGPT From Helping Plan School ShootingsSnap's $400 million deal with Perplexity is deadMeta acquires robotics AI startup as it makes the push into humanoid machinesGameStop submits $56 billion offer to buy eBayGameStop CEO Ryan Cohen Banned From eBay After Flexing His Meme-Stock MuscleElon Musk settles with the SEC for $1.5 million after years-long dispute over his Twitter investmentCoinbase to Lay Off 14% of Workforce Amid AI Disruption and Crypto VolatilityToilet maker Toto is here to help with the RAM crisisExtortion Using Smart Glasses Is a Thing NowMEDIA CANDYDaredevil: Born AgainWidow's BayFun item for media candy?AI performances and screenplays won't be eligible for OscarsAPPS & DOODADSPornhub Expands Access in the U.K. Thanks to Apple's New Age Verification SystemAsk.com has shut down, marking the official farewell to the Internet's favorite butleriPhone users could get up to $95 per device as Apple reaches $250M settlement over Siri delaysTHE DARK SIDE WITH DAVEDave BittnerThe CyberWireHacking HumansCaveatControl LoopOnly Malware in the Building'Decimate' means much more today than it did in ancient RomeThis AI-Powered Talking C-3PO Head Lets You Feel What It's Like to Be R2-D2NuPhy Air75 V3 - Wireless Mechanical KeyboardMaul: Shadow LordSolo: A Star Wars StoryThe BoysWhy grown men become furriesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Apple cuts a $250M check over Siri's broken promises, we look at who's making Apple's chips next, OpenAI enters the media game, and SC State students go toe-to-toe with a lieutenant governor — plus a tip that'll make you never wait on hold agaiThe LowdownApple's $250M Siri Settlement — You Might Get a CheckiOS 26.5 RC: What's New Before WWDCApple Eyes Intel & Samsung for U.S. Chip Production2nd StringOpenAI Just Bought a Media CompanyFor The CultureSC State vs. The Lt. Governor: HBCUs Under FireThe HookupHow to Never Wait on Hold Again With Your iPhone

Want to build an AI side hustle? Get the free AI Side Hustle Crash Course: https://clickhubspot.com/lkb Episode 821: Sam Parr ( https://x.com/theSamParr ) and Shaan Puri ( https://x.com/ShaanVP ) talk to Replit founder Amjad Masad ( https://x.com/amasad ) about growing 100x in one year.  — Show Notes:  (0:00) 2.5M to 250M in 1 year (10:28) the darkest hour (17:00) pivot, pivot, pivot, until it hits (28:19) companies exploding with Replit (33:05) Amjad's business ideas (38:44) "we are in the singularity" (51:24) best business biography  (53:23) getting on Joe Rogan (57:00) slowing down under pressure (1:11:08) Vercel scandal (1:13:35) lifestyle upgrades of being a billionaire — Links: • Replit - https://replit.com/  — Check Out Sam's Stuff: • Hampton (joinhampton.com): My community for founders. Average member does $25m/year. Many of the guests are members. Get after it...apply: http://joinhampton.com/mfm — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com  • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC • I run all my newsletters on Beehiiv and you should too + we're giving away $10k to our favorite newsletter, check it out: beehiiv.com/mfm-challenge My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano /

Today's blockchain and crypto news Bitcoin is up slightly at $81,425.  Ethereum is up 1% at $2,338.  BNB is up 2% at $648 Federal court sentenced 20-year-old California man over role in $250M crypto conspiracy American Bitcoin reports $82M net loss TD Cowen raises Strategy price target BNY expands crypto custody business Pantera Capital says tokenization market is still immature Learn more about your ad choices. Visit megaphone.fm/adchoices

Apple's record Q2 earnings, Mac Studio RAM options are dropped amid shortage, iPhone owners may get up to $95 from a Siri settlement, Anthropic to use massive SpaxeXAI data center, Utah protesting its data center, and we're both making apps.Member Promo Code: IWANTCHAPTERS (Click above and promo will be auto applied!)Top Five Tech | Stephen's PodcastCreative Effort | Jason's PodcastWatch on YouTube!Show Notes via EmailEmail Us: podcast@primarytech.fm@stephenrobles on Threads@jasonaten on Threads ------------------------------ Sponsors:CleanMyMac - Get Tidy Today! Try 7 days free and use my code PRIMARYTECH for 20% off at clnmy.com/PRIMARYTECHNordLayer - Get up to 22% off NordLayer yearly plans plus 10% on top with the coupon code: PRIMARTYTECHNOLOGY10 at: nordlayer.com/primarytechnology ------------------------------ Links from the showCoffee Recipe Card Maker for Home Baristas | BrewCardAirPods Pro 3 Comply Tips - Affiliate LinkSpirit Airlines Article - IncNilay Shout Out on BlueskyApple announces record fiscal second quarter – Six ColorsApple's Binary BetApple Has Given Up on the Vision Pro After M5 Refresh Flop - MacRumorsDaring Fireball: On the Future of Apple's Vision PlatformApple's most powerful Mac Studio loses its last remaining RAM upgrade option - 9to5MacApple CEO warns of memory crunch. 'We'll look at a range of options'iPhone users could get up to $95 per device as Apple reaches $250M settlement over Siri delays - 9to5Mac3 things to know about Kevin O'Leary's massive proposed Utah data center - Axios Salt Lake CityKevin O'Leary's TweetUtah Meeting Protests - XHigher usage limits for Claude and a compute deal with SpaceX AnthropicAnthropic Taking Over All Capacity of xAl's First Memphis Data Center - 512 PixelsMira Murati tells the court that she couldn't trust Sam Altman's words | The VergeNetflix Rolls Out Vertical Video Feed, Blurring Lines Between Streaming and Social MediaDisney+ to become ‘super app' that goes beyond streaming service: report - 9to5MacUS Supreme Court declines to pause order holding Apple in contempt in Epic Games lawsuit | ReutersVideo on Apple Podcasts Doubled My Plays (Case Study)reMarkable Paper Pro Move | reMarkableKindle Store (00:00) - Intro (07:53) - Apple Q2 Earnings (15:22) - Is Apple Vision Pro Dead? (18:52) - RAMpocalypse (27:57) - Siri Failure Payouts (31:51) - Sponsor: CleanMyMac X (33:29) - Sponsor: NordLayer (35:08) - Utah Data Center Fiasco (43:13) - Claude SpaceXAI Deal (47:24) - Mira Murati at Elon X Altman Trial (50:50) - Disney+ Super App (52:40) - VOX May Be Acquired (55:22) - SCOTUS Apple v Epic Games (57:27) - Transistor Case Study (01:06:15) - reMarkable Paper Pure ★ Support this podcast ★

Ashley Connolly, Fórsa Trade Union, discusses the financial issues at the HSE.

Listen to a recap of the top stories of the day from 9to5Mac. 9to5Mac Daily is available on iTunes and Apple's Podcasts app, Stitcher, TuneIn, Google Play, or through our dedicated RSS feed for Overcast and other podcast players. Sponsored by Bitwarden: Make your life easier with Bitwarden, featuring a secure, open source password manager with end-to-end encryption and seamless autofill across all your devices. New episodes of 9to5Mac Daily are recorded every weekday. Subscribe to our podcast in Apple Podcast or your favorite podcast player to guarantee new episodes are delivered as soon as they're available. Stories discussed in this episode: Report: iPhone 17 ranked as world's top-selling smartphone in Q1 2026 iPhone users could get up to $95 per device as Apple reaches $250M settlement over Siri delays iOS 27 will let you choose between Gemini, Claude, and more for AI features: report Listen & Subscribe: Apple Podcasts Overcast RSS Spotify TuneIn Google Podcasts Subscribe to support Chance directly with 9to5Mac Daily Plus and unlock: Ad-free versions of every episode Bonus content Catch up on 9to5Mac Daily episodes! Share your thoughts! Drop us a line at happyhour@9to5mac.com. You can also rate us in Apple Podcasts or recommend us in Overcast to help more people discover the show.

Your body doesn't know the difference between a tiger… and an email. Every time you suppress stress, push through emotions, or ignore what you feel, it doesn't disappear. It stacks. And eventually… it breaks you. In this powerful and eye-opening conversation, George is joined by Nic Monteforte, leadership expert, high-performance coach, and author of Infinite Capacity, to break down the real reason so many entrepreneurs burn out. Nic shares her journey from managing thousands of people and leading a $250M company… to losing everything, not because she lacked strength, but because she was living in constant stress. Together, they explore how stress actually works in the body, why most people never complete the stress cycle, and how “stress debt” builds over time until it leads to burnout. This episode isn't about eliminating stress, because you can't. It's about learning how to process it, release it, and reclaim your capacity. What You'll Learn In This Episode: Why your body reacts the same to emails as it does to real danger The concept of “stress debt” and how it builds over time Why suppressing emotions is the root cause of burnout The difference between being stressed vs staying stressed What “infinite capacity” actually means How to complete the stress cycle in real time Simple tools to regulate your nervous system throughout the day How to increase clarity, energy, and performance without burnout Key Takeaways: ✔️Stress is not the problem, suppression is. ✔️Stress = suppressed emotions (energy that never got released). ✔️Stress stacks over time like layers until it collapses into burnout. ✔️You can't eliminate stress, but you can complete the cycle. ✔️60 seconds of physical movement can reset your entire nervous system. ✔️Most people stay stuck because they never process what they feel. ✔️True capacity comes from removing internal “blocks,” not doing more. ✔️Calm isn't something you chase, it's something you create internally. Timestamps & Highlights: [00:00] – Why your body treats emails like life-or-death threats [02:00] – Nic's story: success, burnout, and losing everything [06:00] – What “capacity” really means [10:00] – Stress = suppressed emotions explained [14:00] – The buildup of stress layers (stress debt) [18:00] – Why burnout happens (and how it sneaks up) [20:00] – Completing the stress cycle (practical tools) [25:00] – Physical hacks to reset your nervous system [30:00] – Why movement is the fastest way to regulate stress [35:00] – Removing internal blocks to unlock performance [40:00] – The shift from reaction → response [45:00] – Building a calm, high-capacity life   Connect with Nic Monteforte Nic Monteforte is a leadership expert, high-performance coach, and author of Infinite Capacity. With over 30 years of experience, she helps leaders and entrepreneurs reclaim energy, sharpen focus, and operate at their highest level, without sacrificing their wellbeing. After experiencing burnout firsthand, Nic developed powerful frameworks to help others move from constant stress to sustainable performance. Website: https://nicmonteforte.com/ Book: https://infinitecapacitybook.com/ Instagram: @nicmonteforte Your Challenge This Week: If this episode shifted your perspective… Share it with someone who's running on empty Tag @itsgeorgebryant  and @nicmonteforte with your biggest takeaway Ask yourself: Where am I staying stressed instead of releasing it? And most importantly, pick one tool from this episode and use it today. Live Events & Retreats Ready to step out of stress and into clarity? Join George at an immersive live experience designed to help you reset, realign, and build a business that feels as good as it performs. Explore upcoming events: mindofgeorge.com/event Join The AllianceThe Relationship Beats Algorithms™ community for entrepreneurs who scale with trust, connection, and sustainability. Apply for 1:1 Coaching If you're ready to increase your capacity, reclaim your energy, and lead at your highest level, apply to work directly with George.

Red Sox Fire Alex Cora & Most Of Their Coaching Staff… Phillies Are Historically Awful + A brand new MLB Power Rankings with a BIG change at the top! The Boston Red Sox just fired nearly their entire coaching staff... but kept the people actually responsible. We break down the messy, petty drama: Alex Cora's IG post,, the “Coaches for Hire” bus, and the awkward press conference where Breslow and Kennedy pointed fingers. Meanwhile, the Philadelphia Phillies are in total freefall! The worst record in baseball, worst run differential, worst defense (-17 DRS), and one of the worst offenses despite a $250M+ payroll. Are they living and dying by the home run too much? Plus: - Latest Power Rankings - Team of the Week highlights - Mexico City Series thoughts Timestamps: 0:00 - Intro 0:40 - Red Sox Fiasco 16:35 - Phillies Awful Start 22:54 - New MLB Power Rankings 32:18 - Team of the Week 36:11 - Mexico City Recap 38:22 - Outro What's your take — did the Red Sox fire the right people? Are the Phillies in real trouble? Drop your thoughts in the comments! Learn more about your ad choices. Visit megaphone.fm/adchoices

California is moving to criminalize investigative journalism. Nick Shirley joins Riley Gaines to expose the "Stop Nick Shirley Act" and the $250M fraud it's trying to hide. In this explosive episode, Nick Shirley returns to discuss the legislative attempt (AB 2624) to make public filming of taxpayer-funded immigrant service providers a crime. Nick recounts his recent trip to Sacramento where he confronted the bill's co-authors—many of whom didn't even realize they had signed it. We dive deep into: The $250 million hospice fraud investigation and the conflict of interest involving AG Rob Bonta's office. The personal security risks of being a "fraud hunter". Nick's recent private meeting with Elon Musk and why X is the front line for truth. The latest on Ilhan Omar's shrinking net worth and missing LLCs. Nick is risking it all to show us where our tax dollars are actually going. From $15k security bills to being called a 'psycho' by legislators, the pressure to stop him is real. Should investigating taxpayer-funded fraud be a crime? Drop your thoughts below

Erin and Alyssa check in on the latest Bravo-level drama from Trump's wack job cabinet, two recent chilling tragedies in Virginia and Louisiana, Planned Parenthood's foray into cosmetic offerings, Reese Witherspoon's suspicious call for women to use more AI, and more. Then professor Chanda Prescod-Weinstein drops by to talk about her new book, The Edge of Space-Time, what people are getting wrong about the Artemis II mission, and what Star Trek and Octavia Butler can tell us about our current political moment.For a closed-captioned version of this episode, click here. For a transcript of this episode, please email transcripts@crooked.com and include the name of the podcast.The FBI Director Is MIA (The Atlantic 4/17)FBI director Kash Patel files $250M defamation lawsuit against The Atlantic (CNN 4/20)Labor Dept. Investigates Texts Among Secretary's Family and Staff (NYT 4/15)Feud between Mace and Mills flares as the Republicans trade barbs, expulsion threats (CNN 4/21)Ex-Virginia deputy governor kills wife and himself, police say (BBC 4/17)Haunted by ‘Dark Thoughts,' Louisiana Father Kills 8 Children (NYT 4/19)The Shreveport Mass Killing Isn't Just About ‘Mental Health' by Brittany Cooper (The Cut 4/20)A Planned Parenthood Clinic, in a Pinch, Turns to Botox (NYT 3/11)The Woman Who Knows Too Much: An Interview with Amanda Ungaro (Courier 4/18)Reese Witherspoon Declares “It's Time” For Women To Embrace AI: “Want To Learn With Me?” (Deadline 4/17)We Need Space w. Dr. Chanda Prescod-Weinstein

Tuesday, April 21st, 2026 Today, Kash Patel is suing the Atlantic for $250M over excessive drinking claims; a man facing divorce kills 8 children in a shooting rampage including 7 of his own; surveillance tech giant Palantir posts a dystopian manifesto on Twitter; a Pennsylvania court rules a Medicaid abortion ban is unconstitutional; the Supreme Court will hear a case about Catholic preschools allowing children of same sex couples to attend; the Onion signs a deal to take over Alex Jones' Infowars; a pancreatic cancer mRNA vaccine showed lasting results in an early study; and Allison delivers your Good News. Thank You, Fast Growing Trees Get 20% off your first purchase  https://FastGrowingTrees.com/dailybeans Thank You, OneSkin Get 15% off OneSkin with the code DAILYBEANS at  https://www.oneskin.co/dailybeans #oneskinpod The Daily beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser Guest: Sarah FedermanCorporate Reckoning by Sarah Federman | PenguinRandomHouseSarahFederman.com Guest: Ezra LevinMAY DAY STRONG IndivisibleEzra Levin | Indivisible@ezralevin - Bluesky The Latest Breakdown:Former FBI Deputy Director Responds to Kash Patel's Alleged Drinking Problem StoriesPennsylvania court rules Medicaid abortion coverage ban unconstitutional | WGAL Supreme Court takes up Catholic objection to Colorado's preschool program | NBC News 8 children killed in Shreveport, Louisiana, shooting, police say | The Washington Post Kash Patel Sues The Atlantic for $250 Million Over Article Claiming Excessive Drinking | The New York Times Surveillance tech giant Palantir posts manifesto on X dealing with national service, post-World War II attitudes and diversity | The Independent The Onion Signs New Deal to Take Over Infowars | The New York Times Pancreatic cancer mRNA vaccine shows lasting results in an early trial | NBC News   Good Trouble MONDAY 20 APRIL - SUNDAY 26 APRIL 2026 The theme for LVW 2026 is: Health and Wellbeing.Lesbian Visibility Week - Virtual and in-person events calendar:Lesbian Visibility Week 2026 Events (North America)EVENTS | Lesbian Visibility (UK) Official instagram post - Don't see an event in your hometown? You can organise and add your own →FieldTeam6.org →Palmetto State Abortion Fund - Midland Gives  →2026 Primary Election Calendar: All the Dates Ahead of Midterms →Standwithminnesota.com →Tell Congress Ice out Now | Indivisible, Defund ICE | 5Calls →Congress: Divest From ICE and CBP | ACLU →ICE List  →iceout.org   Good Newsbravefortwayne.org →Share your Good News & Good Trouble - The Daily Beans →Beans Talk audio -beans-talk.simplecast.com Subscribe to the MSW YouTube Channel - MSW Media - YouTube Harry Dunn is running for CongressHarry Dunn for Maryland Our Donation Links The Daily beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser Pathways to Citizenship link to MATCH Allison's Donationhttps://crm.bloomerang.co/HostedDonation?ApiKey=pub_86ff5236-dd26-11ec-b5ee-066e3d38bc77&WidgetId=6388736 Join Dana and The Daily Beans with a MATCHED Donation http://onecau.se/_ekes71 More Donation LinksNational Security Counselors - Donate, ActBlue.com/donate/msw-bwc, WhistleblowerAid.org/beans Dr. Allison Gill - The Breakdown | Allison Gill, Mueller, She Wrote @muellershewrote.com - Bluesky, MSW & The Daily Beans Podcast @muellershewrote - Instagram, MSW Media - YouTube →Federal workers - email AG at fedoath@pm.me and let me know what you're going to do, or just vent. I'm always here to listen.  Dana Goldberg - Dana is on Patreon! At Dana's Dugout, @dgcomedy - Bluesky, @dgcomedy - IG, Dana Goldberg - Facebook,  DanaGoldberg.com More from MSW Media - Shows - MSW Media, Cleanup On Aisle 45 pod, The Breakdown | Allison Gill Reminder - you can see the pod pics if you become a Patron. The good news pics are at the bottom of the show notes of each Patreon episode! That's just one of the perks of subscribing! patreon.com/muellershewrote Listener Survey:http://survey.podtrac.com/start-survey.aspx?pubid=BffJOlI7qQcF&ver=shortFollow the Podcast on Apple:https://apple.co/3XNx7ckWant to support the show and get it ad-free and early?https://patreon.com/thedailybeanshttps://dailybeans.supercast.com/https://apple.co/3UKzKt0 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Today's episode dives into major political and media controversies making headlines. Donald Trump shares new updates on a potential Iran deal, sparking backlash across the political spectrum—including criticism from Megyn Kelly. We break down reactions from Jesse Watters and a heated exchange involving Ro Khanna defending Barack Obama's past Iran deal.Things escalate as Cory Booker delivers a bizarre and emotional speech, while controversy grows around Kash Patel's $250M lawsuit against The Atlantic—which quietly edited a headline after publication. We also cover reactions from Brian Stelter, political drama involving Mallory McMorrow, and viral moments from Kamala Harris.Plus: updates on Savanah Hernandez, anti-ICE protests, bizarre policy debates, and the ongoing feud between Candace Owens and Laura Loomer.SUPPORT OUR SPONSORS TO SUPPORT OUR SHOW!Fast-track healthy eating with Marley Spoon—receive 45% off plus FREE shipping at https://MarleySpoon.com/offer/Chicks  That's 45% off plus FREE shipping!Refresh your skincare routine this spring with a skincare upgrade from Bon Charge. Visit https://BonCharge.com/chicks and use code CHICKS for 15% off sitewide. Achieve better sleep this spring with REM Sleep from Healthycell.  Go to https://Healthycell.com/Chicks with code CHICKS20—no pile of pills needed.Lose meaningful weight healthily with LEAN—get 20% off and FREE rush shipping at https://TakeLean.com using code CHICKSSubscribe and stay tuned for new episodes every weekday!Follow us here for more daily clips, updates, and commentary:YoutubeFacebookInstagramTikTokXLocalsMore InfoWebsite

Steve Schmidt & Dean Blundell discuss Kash’s crash-out (including the $250M lawsuit he filed against The Atlantic and reporter Sarah Fitzpatrick today), Pete Hegseth’s hysterics, and the CNN story that no one is paying attention to — and everyone should be. SHOP: The "Voting is a Privilege, not a Right' tee: https://thewarningwithsteveschmidt.com/products/voting-is-a-right-tee Support The Warning and become a YouTube member today! https://www.youtube.com/channel/UC2I50t9-7Ol7AjwryRv-Fiw/join Subscribe for more and follow me here: Substack: https://steveschmidt.substack.com/subscribe Store: https://thewarningwithsteveschmidt.com/ Bluesky: https://bsky.app/profile/thewarningses.bsky.social Facebook: https://www.facebook.com/SteveSchmidtSES/ TikTok: https://www.tiktok.com/@thewarningses Instagram: https://www.instagram.com/thewarningses/ X: https://x.com/SteveSchmidtSES

Ryan Pineda and Brian Davila host Sam Taggart as he breaks down how he transitioned from door-to-door sales into building a $70M roofing roll-up, sharing deep insights on sales culture, private equity strategy, and scaling service-based businesses.⁣⁣Connect with Sam - ⁣https://www.instagram.com/thesamtaggart⁣https://thed2dexperts.com/⁣__________⁣If you want to start your real estate investing business, we'll give you 1:1 coaching, seller leads, software, & everything you need. https://www.wealthyinvestor.com⁣⁣If you're a business owner who wants to get in peak physical shape, we can help! https://www.allproceo.com⁣⁣Join our private mastermind for elite business leaders who golf. https://www.mastermind19.com⁣⁣Join free Bible studies and workshops for Christian business leaders. https://www.tentmakers.us⁣__________⁣CHAPTERS:⁣3:21 - Roll-Up Strategy Explained⁣10:27 - Why Cashless Merger⁣15:06 - Growth Targets & Exit Plan⁣19:13 - Roofing Business Breakdown⁣29:49 - Biggest Bottleneck in Scaling⁣36:16 - Short-Term vs Long-Term Wealth⁣41:32 - Starting a Roofing Company⁣59:00 - Recruiting Hidden Talent⁣1:02:07 - Sales Team Power Struggles⁣1:04:03 - Door-to-Door Conversion Math⁣1:07:26 - Craziest Door-to-Door Stories⁣1:15:28 - Why Roofing Has Opportunity⁣1:19:17 - Solar Industry Collapse⁣1:30:34 - Private Equity Risks & Strategy⁣1:32:25 - Scaling with Data & Systems

Bill O'Reilly is a veteran broadcaster, bestselling author, and one of the most recognizable voices in American media. After decades shaping the national conversation on television, he now speaks directly to millions through his hit podcast We'll Do It Live. Follow his latest commentary and behind-the-scenes updates on Instagram @billoreilly. For news analysis, books, and more, visit billoreilly.com.In The News: Chicago lawmaker ripped over 'disgusting' response to college student allegedly killed by illegal immigrant, LA to greenlight staggering $250M expansion to LAX project — up from $13M, Hochul finally admits economy-killing ‘climate' law is toxic for NY — she should end it, Gavin Newsom roasted for Patrick Bateman tweet. FOR MORE WITH BILL O'REILLY:PODCAST: We'll Do It LiveBOOK: Confronting Evil: Assessing the Worst of the WorstFOR MORE WITH ANDREW HOBSON:INSTAGRAM: @andrewfhobsonLIVE SHOWS: March 27 - Norfolk, NE (2 shows)March 28 - Norfork, NE (2 shows)March 29 - Lincoln, NEThank you for supporting our sponsors:BetOnlinefastgrowingtrees.com/adamTecovas.com/ADAMpluto.tvoreillyauto.com/adamSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.