Podcasts about mckinsey

The episode highlights a structural gap between projected AI-driven revenue in the channel and the concrete operational changes needed to capture measurable ROI. Industry surveys from Informa MSP 501, McKinsey, and PwC consistently show that while AI adoption rates among managed service providers (MSPs) are high, few organizations have restructured workflows or business models around AI. The focus remains on superficial activity tracking rather than genuine business transformation.The MSP 501 survey found 57% of providers expect significant AI revenue growth, with 91% reporting some level of adoption. However, McKinsey's analysis, as presented by IHL Group, shows only 11% of companies have comprehensively rebuilt processes around AI, with a minority of those realizing clear benefits. PwC's CEO survey aligns, with over half of respondents seeing no substantive financial returns from AI unless it is extensively integrated beyond the user level.Products like Insightful workforce analytics are now entering MSP portfolios, offering discounted access to AI usage tracking tools. Yet data from Visier and the OECD warn that monitoring software can promote superficial compliance—about half of workers admit to overstating AI usage, and most lack control over the data collected. The OECD also finds that this monitoring is often embedded in standard business software rather than dedicated AI platforms.For MSPs, the risk is prioritizing activity measurement over outcome-based change. Vendors promote usage reports, but these often reward appearances rather than operational improvement. Meaningful results depend on redesigning workflows and measuring actual process improvements—not merely collecting tool usage statistics. Before offering AI usage metrics to clients, MSPs should validate the effectiveness of workflow changes internally to avoid incentivizing unproductive patterns.00:00 Forecasting AI, Skipping The Redesign 04:06 When Usage Stands In For Results06:56 The Usage Meter Hits Your Catalog10:46 Why Do We Care? Supported by: Mailprotector Pax8NinjaOne On-Demand Webinar: https://go.businessof.tech/p/ninjaone-pod

What's the near future of private credit and where are we in the consumer credit cycle? Should individual investors look to private credit as an investment vehicle? Vervent founder and CEO David Johnson is one of the best people to ask, as Vervent helps rescue distressed loan portfolios. David is also a high school dropout who went on to a Stanford MBA and stints at Bain and McKinsey before building Vervent into a $165 billion AUM platform. In this conversation, we dive into the signals David is seeing in the credit market, and what inspired him to write his new book, Figure It the F*ck Out.    What You'll Discover In This Episode The K-shape of the credit market & how it decides which credit cards survive  Why David advises against private credit for the individual investor The dynamics behind Tricolor's historically huge Chapter 7 bankruptcy How securitization adds both liquidity & risk  What he sees in leadership today that inspired his new book   Click here to pre-order David's book, Figure It the F*ck Out.   About the Guest David J. Johnson is CEO of Vervent, one of the country's most trusted consumer credit infrastructure platforms, where he brings decades of experience at the intersection of capital markets, operations, and credit. Under his leadership, Vervent has grown into a $150B+ AUM platform serving top banks, asset managers, and specialty lenders across loan servicing, credit card and lease management, backup servicing, and capital markets support. Earlier in his career, he advised global firms on operational strategy at McKinsey & Company and Bain & Company.       About Your Host From pro-snowboarder to money mogul, Chris Naugle has dedicated his life to being America's #1 Money Mentor. With a core belief that success is built not by the resources you have, but by how resourceful you can be. Chris has built and owned 19 companies, with his businesses being featured in Forbes, ABC, House Hunters, and his very own HGTV pilot in 2018. He is the founder of The Money School™ and Money Mentor for The Money Multiplier. His success also includes managing tens of millions of dollars in assets in the financial services and advisory industry and in real estate transactions. As an innovator and visionary in wealth-building and real estate, he empowers entrepreneurs, business owners, and real estate investors with the knowledge of how money works. Chris is also a nationally recognized speaker, author, and podcast host. He has spoken to and taught over ten thousand Americans, delivering the financial knowledge that fuels lasting freedom.   Resources Private Money Guide:  https://go.moneyschoolrei.com/book-podcast Wealth Wednesday Webinar: https://go.moneyschoolrei.com/wednesday-webinar-podcast Mapping out the Millionaire Mystery:  https://go.moneyschoolrei.com/newbook-podcast    

(9.24.2026-10.1.2026) Back on an off day. Tune in.#applepodcasts⁠⁠⁠ ⁠⁠⁠#spotifypodcasts⁠⁠⁠ ⁠⁠⁠#youtube #amazon⁠⁠⁠ ⁠⁠⁠#patreon⁠⁠⁠patreon.com/isaiahnews

Micha Pfisterer ist Gründer und Geschäftsführer der Ext-Com IT GmbH in Germering bei München. Sein Team betreut kleine und mittelständische Unternehmen als IT-Systemhaus – von der Infrastruktur über IT-Security und Datenschutz bis zur Telekommunikation. Aus der Ein-Mann-Beratung von 2016 sind über 40 Mitarbeiter geworden, und das Wachstum kommt rein organisch: 40 bis 60 Prozent pro Jahr. Sein Wissen teilt er im Podcast „Systemhaus Geflüster", mit myDashboard hat er außerdem ein Monitoring-Produkt für Systemhäuser aufgebaut. In dieser Folge: Systematisch wachsen als IT-Dienstleister – der Vertriebsansatz hinter 40 bis 60 Prozent Wachstum pro Jahr. Micha Pfisterer zeigt, wie sein Systemhaus aus der Vergleichbarkeit ausbricht: ein ICP mit klaren Ausschlüssen, die Infrastrukturanalyse als Vorprodukt vor jedem Angebot, zwei Hunter fürs Neukundengeschäft und lösungsbasierter Verkauf statt Produkt-Features. Dazu: warum ein Verkäufer nur 5 bis 20 Prozent Eindringtiefe braucht, wie Account Manager und technische Experten im Tandem auftreten, warum Vertrieb nichts für schlechte Zeiten ist und weshalb der Geschäftsführer Vertrieb selbst verstehen muss. Zum Schluss: wo KI und Security die nächsten Wachstumsfelder für Systemhäuser sind – inklusive des 486-Milliarden-Potenzials, das McKinsey bis 2030 allein für Deutschland sieht.

A bizarre and disturbing story out of the Bay Area: two, 76-year-old murder suspects are in custody, accused of murdering their son-in-law at a California sports complex and playground. Police say Shouyong Zhang and Shili Chen each shot 40-year-old Jonathan McKinsey multiple times, witnesses directing police to the couple within minutes of the murder. McKinsey was the director of engineering for the games section of The New York Times and was in a contentious and complicated divorce and custody battle that included decades of domestic violence accusations and restraining orders. The couple is expected in court on Wednesday, where we hope to get more details in this shocking crime.See omnystudio.com/listener for privacy information.

A bizarre and disturbing story out of the Bay Area: two, 76-year-old murder suspects are in custody, accused of murdering their son-in-law at a California sports complex and playground. Police say Shouyong Zhang and Shili Chen each shot 40-year-old Jonathan McKinsey multiple times, witnesses directing police to the couple within minutes of the murder. McKinsey was the director of engineering for the games section of The New York Times and was in a contentious and complicated divorce and custody battle that included decades of domestic violence accusations and restraining orders. The couple is expected in court on Wednesday, where we hope to get more details in this shocking crime.See omnystudio.com/listener for privacy information.

A bizarre and disturbing story out of the Bay Area: two, 76-year-old murder suspects are in custody, accused of murdering their son-in-law at a California sports complex and playground. Police say Shouyong Zhang and Shili Chen each shot 40-year-old Jonathan McKinsey multiple times, witnesses directing police to the couple within minutes of the murder. McKinsey was the director of engineering for the games section of The New York Times and was in a contentious and complicated divorce and custody battle that included decades of domestic violence accusations and restraining orders. The couple is expected in court on Wednesday, where we hope to get more details in this shocking crime.See omnystudio.com/listener for privacy information.

 Tushar Garg is the Co-Founder and CEO of Flyhomes, a next-generation residential real estate financial solutions company that empowers agents and loan officers with exclusive buy-before-you-sell solutions, enabling buyers to move before they sell with less stress and more certainty. He has led Flyhomes through multiple funding rounds to Series D, evolved the company from a D2C model to a B2B2C platform, and expanded into innovative financial products and nationwide wholesale lending. Prior to founding Flyhomes, Tushar held roles at Microsoft and McKinsey.See omnystudio.com/listener for privacy information.

Great leaders know how to turn the temperature down when everyone else is turning it up. Roxanne Petraeus discovered that early as a U.S. Army officer, watching the leaders she most admired become calmer as situations grew more stressful. Today, as CEO of Ethena, she draws on those lessons to lead through uncertainty, develop other leaders, and create an environment where people can think clearly instead of reacting from fear. You'll hear how Roxanne responded when COVID derailed a critical fundraising effort, why she believes bad news should never be sugarcoated, and what being one of very few women in both the Army and venture capital taught her about confidence and authenticity. She also explains why your most important work as a leader may be the conversations that produce nothing tangible, how your behavior signals what you'll tolerate, and why learning something new in public—including AI—may be one of the most powerful ways to lead. Roxanne is the co-founder and CEO of Ethena, a compliance training company trusted by more than 2,000 organizations, including Pinterest, Zendesk, Notion, and Figma. A U.S. Army veteran, Roxanne served as an engineer officer in Afghanistan and later as a Civil Affairs officer supporting Special Operations. She went on to become a Rhodes Scholar at Oxford and worked at McKinsey before co-founding Ethena.  Since launching Ethena in 2019, Roxanne has raised $50 million in venture capital while building a company focused on taking workplace compliance beyond simply checking the box. Throughout her career, she has maintained a deep interest in learning about and practicing effective leadership.  You'll discoverHow your calmness changes others under pressure Why transparency builds trust during uncertainty What helps you lead without being the expert How your behavior signals what you'll tolerate Why learning publicly gives others courage Connect with Roxanne Petraeus on Social MediaLinkedIn https://www.linkedin.com/in/roxanne-bras-petraeus-2292b8109/  Website Ethena https://www.goethena.com/Check out all the episodesLeave a review on Apple PodcastsConnect with Meredith on LinkedIn

A bizarre and disturbing story out of the Bay Area: two, 76-year-old murder suspects are in custody, accused of murdering their son-in-law at a California sports complex and playground. Police say Shouyong Zhang and Shili Chen each shot 40-year-old Jonathan McKinsey multiple times, witnesses directing police to the couple within minutes of the murder. McKinsey was the director of engineering for the games section of The New York Times and was in a contentious and complicated divorce and custody battle that included decades of domestic violence accusations and restraining orders. The couple is expected in court on Wednesday, where we hope to get more details in this shocking crime.See omnystudio.com/listener for privacy information.

Ashe in America and Wednesday regular Brian Lupo tackle the AI conversation they have been promising for weeks, joined by Matt McDonagh for some genuine industry insight and a bit of referee duty. The big question on the table, is artificial intelligence steering us toward a golden age of abundance, or something closer to global imprisonment? Expect a lively back and forth on job displacement, from blue collar work to white collar middle management, the AGI to ASI progression, and whether ideas like UBI (and a certain someone's evolving feelings about it) are a real solution or a band aid. Matt brings a preview of his new show, Life in the Singularity, premiering that Thursday, and the trio picks apart corporate AI messaging from the likes of McKinsey along the way. It is part debate, part reality check, with humor woven through some genuinely big picture stakes about where this technology takes us next.  

Interest rates are still climbing, mortgage rates have crossed 7.5%, and the labor market remains tight despite signs that some workers are struggling to find new jobs.Mike Armstrong and Paul Lane discuss why the bond market remains under pressure, how the AI buildout is keeping parts of the economy running hot, and why higher rates are hitting housing and traditional businesses harder than data centers and chipmakers. They also break down long-term unemployment, McKinsey's warning that AI could force millions of workers into new roles, IRA mistakes that can be difficult to undo, Vail's weak ski pass sales, falling birth rates, and the privacy trade-offs behind Meta's Muse AI agent.

“What if we fell out with the Brits? What if the agency and the Brits started spying on each other again?” — David McCloskeyWhat if the Americans and the British started spying on each other again? That's the premise of London Station, David McCloskey's fifth novel, out today. It isn't as far-fetched as it sounds. Before the Second World War those perfidious Brits did spy on America, breaking American ciphers and running influence campaigns in New York to drag the United States into the war.McCloskey spent eight years as a CIA analyst working on Syria, then a spell at McKinsey, before writing a series of successful spy novels and co-hosting the popular The Rest Is Classified podcast. The Dallas-based author has also, he admits, become an Anglophile — which hasn't stopped him giving MI6 what the Brits would call a “good kicking” in London Station.His returning heroine is Artemis Aphrodite Procter, so named by a father obsessed with Greek mythology and raised on a Florida alligator farm. Described by another of McCloskey's characters as a competent extremist, she is short, dark, hard-drinking and equally mirthful and menacing. Probably not the type of Yank best suited to a pseudo-diplomatic posting in the capital of the former empire. Although I'm guessing there are many British fellows, both inside and outside MI6, not averse to spying on Ms Artemis Aphrodite Procter.Further Reading:• London Station by David McCloskey (W. W. Norton, September 29, 2026) — his fifth novel, after Damascus Station, Moscow X, The Seventh Floor and The Persian.• The Rest Is Classified — the espionage podcast McCloskey co-hosts with the BBC's Gordon Corera, where he and Gordon Corera have also discussed Patrick Radden Keefe's London Falling.• London Falling by Patrick Radden Keefe, a recent guest on this show — the dark-money London that runs in parallel with McCloskey's subterranean city of espionage.• Earlier this year on Keen On: Daniel Silva on Gabriel Allon — the other American spy novelist with a thing for the Brits.  Five Takeaways •       What If We Fell Out With the Brits? McCloskey never expected to set a novel in Britain, for a technical reason: the CIA–MI6 relationship is so institutionalized that it is hard to get the stakes right, and a thriller needs life or death. Then the question arrived — what if we fell out? What if the two services started spying on each other again? That is not fantasy, and the history is the reverse of what most people assume: before the Second World War the British spied on the Americans, broke their ciphers and ran influence campaigns in New York designed to pull the United States into the war. The novel imagines a new administration installing a brash CIA director skeptical of the cousins across the Atlantic, agents on both sides beginning to die, and a thriller that turns into a mole hunt. He is rude about MI6 throughout, which his British friends appear to enjoy — his theory being that Brits are self-deprecating enough to relish being picked on.•       Classified Journalism. He joined the CIA in 2006 as an undergraduate intern and left in 2014, working almost the whole time on Syria. His description of the job is the best short account of intelligence analysis you will hear: it is classified journalism. You have a question your consumer needs answered — and when your consumer is the president and the question is how long Assad can hold on, the sourcing is satellite imagery, stolen documents, intercepted calls and texts, all of it fragmentary and some of it more credible than the rest. You stitch together the what, the why and the so what, and you write it up clean and apolitical so someone can decide something. Everything he publishes now, from a novel to a résumé, still goes to the agency's publication review board — though he argues the genuinely sensitive material would make for bad fiction anyway. Afterwards came McKinsey, where the work was pricing concrete pipe and clearing a rail bottleneck through Chicago, and where he was, as far as he knows, the only McCloskey.•       Artemis Aphrodite Procter. The character began with a real colleague — short, dark curly hair, not physically imposing but with a genuine physicality, and possessed of what he calls a mix of mirth and menace: someone you can drink and gamble with who will terrify you two days later. Then, as good characters do, she started speaking for herself. Her biography is a small comic masterpiece: named by a father obsessed with Greek mythology, raised outside Kissimmee in central Florida on the family business, the nation's third largest alligator-themed amusement park, called Gatorville; university in Ohio; a first husband who didn't work out; an application to the agency made more or less on a whim. Not upper class, not really middle class, and it shows in how she dresses, eats and speaks to people — which is exactly why putting her in London was irresistible. One character calls her a competent extremist. The running question across the books, he says, is what it means to be loyal to a place that is not loyal to you.•       Can a Man Write Her? AK put the objection directly: some literary thought police would say a male former CIA officer has no business inventing a female one. Two answers. First, the same logic throws out Anna Karenina, and he would rather part company than follow it. Second, and more interestingly, he thinks the objection misunderstands what novelists do: you are not inhabiting a character's skin, you are hearing a voice and putting it on the page. His analogy is a reporter interviewing WNBA players — not sharing their background means more work, more research, more time with the subject, not a prohibition. On whether women make different spies he declines the generalization, while noting a real asymmetry: his analytical teams at the agency were at least half women, often majority, while the case officer cadre and the upper rungs of the Directorate of Operations remain heavily male. Which leaves the question he finds genuinely interesting about Procter — how much of her was always there, and how much the organization made.•       No Smiley Without Philby. On traitors, he separates the fiction from the trade. In literature they are everything, and Philby above all — not only because he turned an institution inside out but because his betrayal said something deep about the British class system that still resonates. Hence the line of the hour: you probably don't have George Smiley without Kim Philby, le Carré having essentially novelized the wound. (AK's reversal: perhaps you don't have Philby, in the public mind, without Smiley.) Inside the actual bureaucracies, though, nobody is wrestling with those ghosts day to day. And on Britain's place in all this, he refuses AK's harsher framing — a subtext to a subtext — while conceding the structural reality: the agency is much larger and much richer, and when it wants to do somet...

This episode is supported by Xero, helping businesses use AI with more control through JAX, its in-platform AI finance partner. Get 90% off your plan for your first 6 months at xero.com/highflyers. ________Venky Ganesan is a Partner at Menlo Ventures, one of Silicon Valley's oldest venture capital firms, where he has helped lead its push into AI and backed companies including Anthropic, Abnormal AI and Palo Alto Networks. He has spent 20+ years in venture capital, after starting his career as an entrepreneur and co-founding Trigo Technologies, which was acquired by IBM in 2004.In this rare public conversation, Venky joins Vidit to unpack a journey that began in India before he moved alone to rural Washington State at 16. He shares the culture shock of arriving in America, working through college, choosing a $39,000 McKinsey job over a far more lucrative offer, and eventually becoming an entrepreneur — co-founding Trigo Technologies and selling the company to IBM in 2004.They also explore Venky's 20+ years in venture capital, from backing Palo Alto Networks early in its journey to becoming a Partner at Menlo Ventures and helping drive the firm's push into AI. Venky shares what separates good founders from great ones, why “propensity for action” has become one of his strongest signals, how he thinks about position sizing and why VCs often end up with more money in their worst companies than their best. He also unpacks today's extraordinary AI market, investing in Anthropic, and why he believes the industry is moving from innovators to “imitators and idiots.” Venky reflects on the role his wife has played in his life, the stroke that nearly killed him and changed his perspective, what more than two decades of investing have taught him about ambition, and more.Please enjoy exploring your curiosity._______Get in touch with us via email at contact@curiositycentre.comJoin our stable of commercial partners including the Australian Government, Google, KPMG,, Allens, Macquarie Capital, Xero, JP Morgan and more. Show notes and more episodes hereFollow us on LinkedIn, Twitter and InstagramGet in touch with our Founder and Host, Vidit Agarwal directly hereContact us via our websiteThis episode is supported by Xero, helping businesses use AI with more control through JAX, its in-platform AI finance partner. Get 90% off your plan for your first 6 months at xero.com/highflyers. ________TIMESTAMPS01:17 — The 15-year-old who talked his way into a job03:21 — Growing up in India with big ambitions08:08 — An unexpected lesson from Nelson Mandela10:05 — Leaving India alone at 1614:10 — Why technology became his path to freedom22:41 — McKinsey, entrepreneurship and selling to IBM31:13 — From founder to venture capitalist39:57 — The signal Venky looks for in great founders44:02 — How he backed Palo Alto Networks early47:00 — Reinventing Menlo for the AI era53:14 — AI's “innovators, imitators and idiots”59:25 — The most disorienting market of his career1:06:05 — The stroke that nearly killed him1:08:20 — Rapid fire________The High Flyers Podcast features in-depth interviews with the world's most influential figures in business, tech, finance, government and sport. Launched in 2020, it has ranked in the global top ten for past three years, with listeners in 27 countries and over 200+ episodes released, and featured in Forbes, Daily Telegraph, and at SXSW.Our guests include -- Malcolm Turnbull (Prime Minister of Australia), Keith Rabois (Managing Director, Khosla Ventures), Jason Collins (Head of BlackRock, Asia Pacific), Brad Banducci (CEO, Woolworths), Michael Schneider (CEO, Bunnings), David Eckstein (CFO, Legora), David Schneider (Growth Fund Co-Lead Partner, Coatue), Venky Ganesan (Managing Partner, Menlo Ventures), Shiv Rao (CEO, Abridge), Jesse Zhang (CEO, Decagon), Vandita Pant (CFO, BHP), Elena Verna (Head of Growth, Lovable), David Haber (a16z Partner), Jodie Auster (Uber's Global Head of Travel), Paul Grosmann (CEO, RM Williams), Rob Giglio (CCO, Canva), Jean-Michel Limieux (CTO, Shopify and Atlassian), Stevie Case (CRO, Vanta), Cristina Cordova (COO, Linear), Gautam Chari (Head of Capital Commitments, Bank of America), John Haddock (CBO, Harvey), Mark Suster (Partner, Upfront Ventures), Niki Scevak (Partner, Blackbird), Craig Tiley (CEO, USA Tennis), Jeanne DeWitt Grosser (COO, Vercel), Paul Bassat (Partner, Square Peg), Bowen Pan (Creator, Facebook Marketplace), Peter Varghese (Secretary of Foreign Affairs, Australian Government), Sam Sicilia (CIO, Hostplus), Jack Zhang (CEO, Airwallex), Tim Doyle (CEO, Eucalyptus), Sukhinder Singh Cassidy (CEO, Xero), Sanjeev Gandhi (CEO, Orica) and Philip Green (Australia's Ambassador/High Commissioner to India).

Work-life balance and boundaries are at the center of this conversation with Sarah Armstrong, author of The Art of the Juggling Act.Sarah Armstrong is the head of Global Marketing Operations at Google and the author of The Art of the Juggling Act: A Bite-Sized Guide for Working Parents. With a career spanning McKinsey, Leo Burnett, and two decades at Coca-Cola, she writes and speaks about what it actually looks like to show up for both work and life — and how to decide which is which.In this conversation, we cover:The 5-ball framework: Work, family, friends, health, and spirit — Sarah's framework for identifying which balls in your life are rubber (they bounce when dropped) and which are glass (they don't), and why that distinction is more useful than any calendar hack.Defining balance on your own terms: Why balance isn't a fixed state you achieve once and maintain, why imbalance is inevitable (not if, but when), and how deciding what balance means for you is the work before the tactics.Saying no without explaining yourself: The story of a colleague who turned down a request with no justification — and why the absence of an explanation wasn't rude, it was the skill.The Grace block and the Sunday list: Two low-friction practices that protect non-work time — a standing calendar block that signals you're off, and a Sunday habit for parking unfinished thoughts so your brain can actually stop carrying them.Outsourcing and the transference of hours: The cost-value equation for deciding what to offload, and why the real question isn't what something costs — it's what you'd do with the hours you get back.If you're a working parent who feels like you're failing at everything simultaneously, this conversation is worth your full attention. Sarah doesn't promise balance — she helps you figure out what yours actually looks like, and gives you the tools to protect it. Find her book, The Art of the Juggling Act, at the links below.Connect with Sarah:saraharmstrong.comThe Art of the Juggling ActConnect with Erik:LinkedInThreadsFacebookBlueskyThis Podcast is Powered By:Brain.fm - 20% off your first monthDescriptDescript 101CastmagicEcammPodpageRodecaster ProGrab Shortcasts from Beyond The To-Do List by Blinkist: http://beyondthetodolist.com/blinkistSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What if the CIA and MI6 began spying on each other? This is the question that David McCloskey, the former CIA analyst and co-host of the Rest is Classified, discusses on this episode with Carl Miller.  Together, they examine what would happen if the ‘special relationship' between the Agency and its British counterpart were to be purposefully disrupted. From a potential technological revolution upending intelligence tradecraft to navigating a new environment where old friends become adversaries, McCloskey and Miller discuss the scenarios that inspired the former's latest thriller, London Station.  David McCloskey is the Sunday Times-bestselling author of The Persian, The Seventh Floor, Moscow X, and Damascus Station. He is co-host of the podcast The Rest is Classified. David is a former CIA analyst and former consultant at McKinsey & Company. Carl Miller is a Senior Fellow at Demos and founder of the Centre for the Analysis of Social Media (CASM). He is the co-writer and host of the investigative podcast Kill List and is the author of The Death of the Gods: the New Global Power Grab. If you'd like to become a Member and get access to all our full conversations, plus all of our Members-only content, just visit intelligencesquared.com/membership to find out more. For £4.99 per month you'll also receive: - Full-length and ad-free Intelligence Squared episodes, wherever you get your podcasts - Bonus Intelligence Squared podcasts, curated feeds and members exclusive series - 15% discount on livestreams and in-person tickets for all Intelligence Squared events  ...  Or Subscribe on Apple for £4.99: - Full-length and ad-free Intelligence Squared podcasts - Bonus Intelligence Squared podcasts, curated feeds and members exclusive series … Already a subscriber? Thank you for supporting our mission to foster honest debate and compelling conversations! Visit intelligencesquared.com to explore all your benefits including ad-free podcasts, exclusive bonus content and early access. … Subscribe to our newsletter here to hear about our latest events, discounts and much more. https://www.intelligencesquared.com/newsletter-signup/ Learn more about your ad choices. Visit podcastchoices.com/adchoices/ Learn more about your ad choices. Visit podcastchoices.com/adchoices

Get Promoted Faster: How the Dolphin Strategy Took One Stuck Supervisor to VP — and What It Means for Women Leaders Last updated: September 26, 2026 Trusted by leaders at Stanford University, Ernst & Young, Autodesk, MGM Grand Resorts, and Farmers Insurance Executive Summary: Have you been told you "don't have the personality" for promotion? Sabrina Braham shares how her coaching client Martin, stuck five years as supervisor, reached VP using five moves: decode feedback, recruit dolphins, build your voice, make the Half-Point Ask, and volunteer for visibility. Use them to get promoted faster. Quick Takeaways: Vague feedback like "personality" isn't a verdict — translate it into observable behaviors. Recruit "dolphins": allies in the room who back your ideas when you speak. Employees with sponsors are twice as likely to be promoted (McKinsey & LeanIn.Org, 2025). Ask your manager for a 1–10 rating, then ask what earns one more half point. Martin: five stuck years, then manager in six months — then director and VP. Jump to: Martin's Story · Why You're Stuck · The 5 Moves · The Results · Action Plan · Mistakes to Avoid · FAQ · 2026 Trends As an executive leadership coach with over 30 years of experience (MA, MFT, PCC) and host of the Women's Leadership Success Podcast — on air since 2007 and ranked in the top 1.5% of podcasts worldwide — I hear one question more than any other: how do I get promoted faster when I'm already doing a great job? The question is urgent. By September 10, layoffs.fyi counted more than 128,000 tech layoffs in 2026 — already more than all of 2025. And McKinsey and LeanIn.Org's Women in the Workplace 2025 found only about half of companies still prioritize women's advancement. Good work alone won't help you get promoted faster. In Episode 169, the tables turned. My co-founder and executive producer, Tim Warren, interviewed me about Martin — a Fortune 500 supervisor told he "didn't have the personality" to be a manager. He believed it. Then, step by step, he proved it wrong. His story is the clearest map I know to get promoted faster, especially if you're the only one like you in the room. The Feedback That Kept Martin Stuck for Five Years At Martin's company, supervisors usually became managers within a year. Martin had been a supervisor for five. His numbers were strong, his people loved him, and his leaders said he was doing a great job. Then came the "but": he just didn't have the personality to be a manager. Martin grew up speaking English as a second language, was the first in his family to attend college, and graduated with honors. None of that protected him. When someone with authority labels you, you tend to believe it. I know that feeling. I was raised in a blue-collar family, and when someone with authority said I had a flaw, I assumed it was true. It took me years to unlearn. If you've absorbed a label like Martin's, take this from his story: the label can be wrong, and you can change the evidence behind it. His question to me was painful: could he change his personality to move up? Why Talented Leaders Don't Get Promoted Faster in 2026 Martin's situation isn't rare. A strong performer gets fuzzy feedback, loses confidence, goes quiet in the rooms where promotions are shaped — and stalls. Here's why that pattern makes it harder to get promoted faster right now. The "broken rung" is still broken For every 100 men promoted to first-level manager, only 93 women are promoted (McKinsey & LeanIn.Org, 2025). That first step — the one Martin was stuck on — shapes every level above it. The sponsorship gap is real At entry level, 31% of women have a sponsor versus 45% of men, and employees with sponsors are about twice as likely to be promoted. The finding that matters most: when women and men get equal career support, the gap in promotion ambition disappears. The problem isn't drive. It's backing. Being "the only" changes how you're heard Roughly one in five women are often the only woman in the room, more for senior and technical women (LeanIn.Org). Being "the only" tends to make people cautious about sharing ideas — less visibility when you need more. The cost of waiting In 2026's market, "I'll speak up once I feel confident" is a risky plan. To get promoted faster — or stand out after a layoff — treat visibility as a skill you practice. Ready to get promoted faster — before you feel fully ready? Leading Before You're Ready — a practical playbook for leaders stepping into bigger roles. Inside, you'll find: Language for speaking up with confidence before you feel fully ready Ways to build trust fast with the decision-makers who shape your next role A framework for positioning yourself as promotion-ready — actively, not passively GET THE COMPLIMENTARY PLAYBOOK The Dolphin Promotion Framework™: 5 Moves to Get Promoted Faster Here's exactly what Martin and I worked on. None of it required a new personality — just consistent, specific action. Each move helps you get promoted faster on its own; together they compound. Move 1: Decode the vague feedback "Personality" is nearly useless feedback. What does it even mean? So we started at ground zero: what would Martin need to do differently to be seen as a manager? The answer was concrete. In meetings with peers or senior leaders, Martin went quiet. That silence, and the confidence gap behind it, was what his leaders called "personality." Once we named the behavior, we could change it. Success metric: The feedback becomes two or three observable behaviors — your first step to get promoted faster. Move 2: Recruit your dolphins Picture a shipwreck survivor clinging to boards while a shark circles. When dolphins surround a person in the water, sharks tend to stay away — and dolphins have been reported guiding swimmers to shore. A dolphin at work is someone in the room who has your back, believes you're capable, and supports you when you speak up: A mentor shares knowledge and advice, often in private. A sponsor uses their power and influence to advocate for you — often when you're not in the room. A dolphin is in the meeting with you, backing your idea in real time. Far fewer leaders have dolphins than mentors. Lean In reports that high-potential women often have more mentors than men, yet mentorship didn't correlate with promotion. If you want to get promoted faster, real-time backing does what advice can't. How to find your dolphins: Look for a friend in your key meetings, or someone who often shares your viewpoint. If no one comes to mind, hold one-on-ones, share the idea you want to raise, and see who's aligned. Then make a simple ask. Try This Now (3 minutes): Pick the idea you most want to raise next meeting, then send one colleague: "Here's an idea I'd like to share Thursday. Would you be willing to support it when I bring it up?" That's the whole ask. Move 3: Build your speaking muscle — and rehearse your one main point The most cost-effective confidence builder I know is Toastmasters. Clubs are in nearly every U.S. city, dues are modest (often around $20 a month), and the program works. At a district meeting years ago, I was struck by the room: real confidence and presence, built through structured practice. Martin joined, and it helped him learn to speak up. The second half is rehearsal. You usually know the agenda and what would help your team. Pick your main point and practice it out loud. What surprises people: the CEOs I work with still rehearse their main points before meetings. Success metric: One prepared point, delivered weekly. Small reps like this are how you get promoted faster. Move 4: Make the Half-Point Ask With practice behind him, Martin went directly to the leaders who had formed the wrong impression. Most people skip this step, yet it's the move that helps you get promoted faster than any other. Here's the conversation: State the goal. "I'd like to be promoted to manager. What's helping, and what do I need to do differently?" Ask for a number. "On leading my team, from 1 to 10, what would you give me?" Ask for the half point. If it's a 7: "What would I need to do to be a 7.5?" Always just a half point. Schedule the follow-up. "Could I check back in a few weeks?" Why a half point? It's achievable, and it pulls your manager into problem-solving mode. Once they give a number, they become invested in your progress. There's a psychological bonus. It's why you notice red cars everywhere after buying one: the brain's attention filter, the reticular activating system, scans for what it's primed to find. After the Half-Point Ask, your manager watches for your improvement. Success metric: You have a baseline number from at least one decision-maker and a follow-up date on the calendar. Move 5: Volunteer for visibility Martin also began joining committees. On one sat five vice presidents — and Martin, a newly promoted manager. He practiced his idea for turning a project around. In the meeting, the VPs talked over him toward a decision. So Martin said, "I have an idea." The room stopped. The lead VP asked to hear it. Martin explained it in detail. When he finished, the room went silent. His heart sank. I blew it, he thought. Then the senior vice president said: "Good idea, Martin. Let's do that." That was the game changer. Rehearsal plus visibility had become executive presence — and the surest way to get promoted faster is to be seen doing the next job. What Happened Next: From Supervisor to VP After five stuck years, here's how Martin's trajectory changed: About 6 months: promoted to manager — roughly a 30% raise. About 4 months after that meeting: director. Two to three years later: promoted to vice president, with stock options, earning roughly double his supervisor pay. What moves me most is what didn't change: Martin kept his kindness and has mentored many others to promotion. His words: "I wish I would have contacted you sooner. It was a game changer. It changed my life....

Solar has quietly become the single largest source of electricity in Europe, and in many emerging markets, clean energy is no longer a climate ambition but a matter of national energy security. In this episode of Sustainable Edge, Scatec CEO Terje Pilskog explains how renewables have moved beyond the ESG hype cycle into disciplined, profitable infrastructure, and why economics, not politics, is now driving the energy transition.In this episode of Sustainable EdgeRecorded live at the annual Pareto Energy conference in Oslo, host Joachim Nahem, Executive Chairman and Co-Founder at Position Green, sits down with Terje Pilskog, CEO of Scatec, which builds utility-scale solar, wind and storage in markets such as Ukraine, South Africa, Egypt, Brazil and the Philippines.Five years ago, renewable stocks rode an unprecedented valuation boom. Today, the hype has cooled, interest rates are higher, and developers have shifted their focus to profitability and sustainable cash flows. Terje shares how Scatec navigated that reset, from sharpening its focus on core markets and reducing corporate debt to lowering its cost of capital, and why he remains a climate optimist even as global political attention on climate has faded.Together, they explore why governments in emerging markets are choosing renewables without subsidies, whether recent Middle East conflicts mark a turning point for clean energy, what solar developers can learn from oil and gas majors, and how Scatec continues to operate in Ukraine amid ongoing attacks on energy infrastructure.Learn aboutFrom ESG hype to business fundamentals How Scatec responded to the post-2021 market reset by focusing on fewer markets, cutting debt and building a more resilient, profitable business.Why economics now drives the transition Why renewables no longer need subsidies, and how a single solar and battery project in Egypt saves the country hundreds of millions of dollars a year compared to LNG-fired power.Energy security as a strategic priority Why the war in Ukraine and the Iran crisis are stark reminders that dependence on imported fuel is a structural risk, and why more energy crises are likely ahead.The hidden cost of fossil fuel subsidies How subsidised electricity tariffs burden state budgets across Africa, and how renewables could free up resources for health and education.Managing risk in challenging markets How long-term power purchase agreements and sovereign guarantees protect revenues in high-risk countries.Lessons from oil and gas, and lessons back What renewable developers have borrowed from the oil majors on execution and risk assessment, and what the traditional energy sector could learn from a more nimble way of working.Responsible supply chains How Scatec uses due diligence, physical audits and full traceability to ensure its solar panels, batteries and turbines come from responsible value chains.Grid-friendly renewables in Europe How combining solar, wind and batteries creates a balanced 24/7 generation profile, supports grid stability and opens up new opportunities in markets like Romania and Poland.About Terje PilskogTerje Pilskog was appointed CEO of Scatec in 2022, having joined the company as EVP Project Development in 2013. Before Scatec, he held management positions at Renewable Energy Corporation (REC), which he joined from McKinsey & CoWith close to two decades in renewables, Terje has led Scatec through one of the most turbulent periods in the industry's history, steering the company towards profitability while continuing to build large-scale clean energy projects in some of the world's most complex markets.Why it mattersAs geopolitical instability exposes the risks of dependence on imported fossil fuels, renewables are increasingly being chosen for their cost competitiveness and their contribution to energy independence. Terje argues that the transition is now being driven by a strong business case, one that delivers climate benefits even when climate is not the primary motivation.This conversation offers business leaders a grounded view of how the renewable sector has matured, how risk can be managed in challenging marke

A McKinsey report argued that 95% of a firm's value is produced by 5% of its workforce. An MIT professor spent years finding out what that means for the other 95%. His answer: approximately 35% of the entire US workforce is now employed with no employer intention of retaining them — building cleaners, security guards, travel nurses, freelance journalists, adjunct faculty and millions of W-2 workers in jobs their employers never intend to keep. On today's episode of America's Work Force Union Podcast, MIT Sloan Professor Emeritus Paul Osterman discusses his book Disposable Workers: The Transformation of Employment, published by Harvard University Press in August 2026. He discusses why companies are making this shift, what AI will do to the numbers and why the evidence that unions make workers better off is clear. Book available through Harvard University Press at hup.harvard.edu.

McKinsey research finds that companies executing transformations with rigor are much more likely to meet overall organizational transformation goals. Chris Hagedorn, Preeya Mody, and Michel Morenville join us to discuss what rigor really means in the context of transformation and how to embed it throughout the process, from setting the aspiration to mobilizing to delivering impact. Related insights Rigor: What it takes to turn ambition into impact The power of rigor in transformation (podcast episode) Wave by McKinsey McKinsey Insights on Transformation How to gain and sustain a competitive edge through transformation Going all in: Why employee ‘will’ can make or break transformations Seven principles for achieving transformational growth Beyond transformation: What we now know about driving bottom-line performance The powerful role financial incentives can play in a transformation McKinsey Transformation on LinkedInSupport the show: https://www.linkedin.com/showcase/mckinsey-strategy-&-corporate-finance/See www.mckinsey.com/privacy-policy for privacy information

Sovereignty, by definition, is being updated. Sovereignty 2.0. Under geopolitical tensions, supply chain dependencies and competing regional regulations, the discussion around digital sovereignty is shaping where you're allowed to build, what models you're allowed to train on, and who's allowed to see the results. Competing lines are being drawn. On one side there are those calling for the democratisation of AI and opening the global doors to innovation. On another is a fragmented map of regional regulations, like the strict mandates of the EU AI Act. Bubbling underneath is the geopolitical chess match, primarily between the US and China, turning data, frontier models and the infrastructure behind them into a matter of national security.All of this offers up some big questions for governments and businesses. One no bigger than this: Can global enterprise innovation really survive in a world of digital borders?Joining host Tom Parker is Stéphane Israël, Managing Director of the AWS European Sovereign Cloud and Digital Sovereignty at AWS, alongside Ali Ustun, Senior Partner from McKinsey's Middle East Office and co-leader of their global Data and AI Foundations Service Line and Dr. Catherine di Lorenzo, Partner at A&O Shearman. Sources: FT Resources, McKinsey, NASAThis content is paid for by AWS and is produced in partnership with the Financial Times' Commercial Department. The views and claims expressed are those of the guests alone and have not been independently verified by The Financial Times. Hosted on Acast. See acast.com/privacy for more information.

The global beauty market is expected to hit almost $600 billion by 2030, according to a report by McKinsey & Company. And just like pretty much every industry, it's being transformed by AI.L'Oréal and OpenAI announced a partnership this summer to bring virtual makeup try-ons and product discovery to ChatGPT. An AI styling firm called Alta is integrating e.l.f. Beauty products into its virtual try on avatars. And consumers are increasingly looking to chatbots for skincare and makeup recommendations.Apparently beauty inquiries account for almost half of generative AI retail referral traffic, according to market research firm EuroMonitor. For more we're joined by fashion-tech journalist and consultant Maghan McDowell, who's been following this trend.

The global beauty market is expected to hit almost $600 billion by 2030, according to a report by McKinsey & Company. And just like pretty much every industry, it's being transformed by AI.L'Oréal and OpenAI announced a partnership this summer to bring virtual makeup try-ons and product discovery to ChatGPT. An AI styling firm called Alta is integrating e.l.f. Beauty products into its virtual try on avatars. And consumers are increasingly looking to chatbots for skincare and makeup recommendations.Apparently beauty inquiries account for almost half of generative AI retail referral traffic, according to market research firm EuroMonitor. For more we're joined by fashion-tech journalist and consultant Maghan McDowell, who's been following this trend.

Send us Fan MailMidway through a practice case, one of George Cary's clients did the math and said 90,000 when he meant 900,000. George didn't care.After 5 years and 100+ interviews at McKinsey, George will tell you the right answer is the bare minimum.The offer comes from how you got there and what the answer means for the client.In this episode, he walks through the 3 case math mistakes that cost strong candidates the offer, even with the math right. If case math is the part you dread, all 3 are fixable with the system George lays out.Resources:If you struggle with mental math, Black Belt pairs you with an ex-MBB coach who drills it with you until it's automaticNot sure what you need? Book 15 minutes with Katie and she'll tell you straightBuild the recap, structure, solve and insight habit on your own with Case Foundations, MC's free case prep courseConnect With Management ConsultedCreate a free MC account or download the MC app (Apple, Android) to start your prep todaySchedule a free 15min consultation with the MC TeamWatch the video version of the podcast on YouTubeFollow us on LinkedIn, Instagram, and TikTokJoin an upcoming live event – case interviews demos, expert panels, and more

What happens when AI moves beyond the digital world and starts transforming the companies that manufacture the things around us?In this episode of Riding Unicorns, James and Hector sit down with Robin Van Aeken, Co-Founder & CEO of Magentic, the AI company building digital workers for some of the world's largest manufacturers.Magentic's AI agents, or "mages", work alongside procurement and supply chain teams at companies including Siemens and Coca-Cola Europacific Partners. They connect with existing systems, analyse huge volumes of procurement data and identify opportunities to make supply chains cheaper, faster and more resilient.The economics can be significant. A manufacturer spending $10 billion a year on procurement might save $50 million by making its team 50% more efficient. But improving procurement costs by just 1-2% could generate $100-200 million in savings. Robin explains why this makes procurement one of the most compelling applications for enterprise AI.The conversation also explores how Magentic deploys AI agents inside complex enterprises. Rather than expecting autonomy from day one, its digital workers effectively begin as "interns", learning the organisation, its systems and its data before gradually earning the trust to take actions and eventually run significant parts of procurement and supply chain workflows.Topics Covered• Why the next major AI opportunity could be in the physical economy• Building AI digital workers for procurement and supply chains• Why AI can create more value by reducing procurement spend than headcount• How human-in-the-loop feedback helps agents develop domain expertise• Using AI across complex ERP systems like SAP and Oracle• Building trust with some of the world's largest manufacturers• Data privacy, sovereignty and deploying AI inside sensitive organisations• How Magentic's "mages" progress from interns to autonomous digital workers• Why AI agents increasingly interact with software like humans• Robin's journey from McKinsey to founding Magentic• What his co-founder's experience at OpenAI taught them about the physical economy• Building an enterprise AI company backed by Sequoia Capital• How to construct the right investor syndicate beyond simply raising capital• Why faster, cheaper supply chains could ultimately reduce the cost of physical goodsRobin also explains why the explosion in AI infrastructure is creating a huge new challenge for the physical economy. Data centres, chips, power infrastructure, cooling and other components all depend on manufacturing and supply chains that weren't designed for today's speed of demand.This is a conversation about bringing AI into the physical economy: deploying agents inside complex enterprises, making global supply chains more efficient and using software to unlock potentially hundreds of millions of dollars in savings.

The Remarkable Retail podcast turns six. Steve Dennis opens with the macro picture: inflation remains stubborn, driven largely by fuel. U.S. diesel just hit an all-time high, regular gas is up 36% year over year, and retailers absorbing higher freight costs say they're nearing their breaking point. Michael LeBlanc adds that diesel is almost perfectly correlated with food inflation, and that Canadian retailers expect fuel surcharges to persist into early 2027.The hosts review the first holiday forecasts. Deloitte projects 4 to 4.8% growth for November through January, with e-commerce up about 8%; Bain sees 4.5% growth and roughly 9% online over November and December. Steve wonders whether high fuel costs could push more shoppers online.At Macy's Inc., Bloomingdale's posted its highest comp ever at 11.3%, while the Macy's nameplate managed just over 1%, in line with Dillard's. Coresight's mid-year data shows store closings down 44% against an unusually heavy prior year, openings at their lowest since 2020, and a widening gap between scarce A-quality space and struggling B, C and D properties. Toys R Us is betting big, planning 120 more small-format U.S. stores before the holidays, though Michael notes the concept stumbled in Canada.The centerpiece: Steve's Pardon the Disruption post arguing that "the race to the doorstep is escalating." With Amazon rolling out sub-same-day delivery in as little as 30 minutes and holding roughly 40% of e-commerce, most retailers can at best match the offering through store fulfillment and gig partners like Instacart and DoorDash, at far worse economics. The smarter play: reach delivery parity where it matters and compete on reasons beyond ultra-convenience. Both hosts agree traditional grocers sit squarely in the bullseye as Amazon moves from the everything store to the everyday store.In earning news Inditex posted a 9% August sales gain, Zara plans 20 new U.S. stores, and sister brand Bershka is expanding fast from Miami to New York, India and Brazil. Kroger's sales were flat and guidance was cut, with retail media (up 24%) the lone bright spot.On the radar screen: Target Beauty Studio replaces Ulta shops in about 600 Target stores, and Michael shares insights from his quarterly retailer conversations on AI's ROI, including a McKinsey finding that change-management costs run roughly three times the technology itself, plus the shock of seat-based bills and exhausted token budgets. About UsSteve Dennis is a strategic advisor and keynote speaker focused on growth and innovation, who has also been named one of the world's top retail influencers. He is the bestselling author of two books: Leaders Leap: Transforming Your Company at the Speed of Disruption and Remarkable Retail: How To Win & Keep Customers in the Age of Disruption. Steve regularly shares his insights in his role as a Forbes senior retail contributor and on social media.Michael LeBlanc is a senior retail advisor, keynote speaker and media entrepreneur. Michael has delivered keynotes, hosted fire-side discussions hosted senior retail executive on-stage in 1:1 interviews worldwide. Michael produces and hosts a network of leading retail trade podcasts, including The Remarkable Retail Podcast, The Voice of Retail, The Food Professor, The FEED powered by Loblaw and the Global eCommerce Leaders podcast. He has been recognized by the NRF as a global Top Retail Voice for 2025 and 2026 and continues to be a ReThink Retail Top Retail Expert for the fifth year in a row.

What kills hard-tech startups usually isn't the technology. It's everything surrounding it: unit economics, supply chains, customers, workforce, financing, and the long road from demonstration to deployment.Guest bio:Dr. Vanessa Chan is an entrepreneur, engineer, angel investor, and educator who works at the intersection of technology, commercialization, and business. She previously served as Chief Commercialization Officer at the U.S. Department of Energy and now leads innovation and entrepreneurship at the University of Pennsylvania's Engineering program. She was also a partner at McKinsey & Company, where she co-led its innovation practice. TIME named her to its TIME100 Climate list of influential climate leaders in 2024. She holds three patents and, outside of work, runs her own pottery studio.Seven things you'll learn in this episode:Technology readiness isn't enough: founders also need to systematically reduce market, supply chain, workforce, regulatory, community, and economic risks.A startup doesn't need to eliminate every risk before raising capital, but it needs data, explicit assumptions, and a credible plan for driving each major risk down.Commercialization ultimately comes down to three questions: Do customers want it, will they pay enough for it, and can you deliver it at a cost that lets the value chain make money?The hardest financing gap in hard tech often sits between development and demonstration, when first-of-a-kind projects remain expensive, but traditional capital wants proven economics.America's capital providers may need new structures that spread risk across the first several deployments instead of waiting to finance the eighth or ninth project.Founders trained as technologists need to replace “technology push” with “market pull,” including talking to customers long before the technology is finished.Some of the best entrepreneurial training comes from getting comfortable without a rubric: observe problems, ask why, experiment, build networks, and learn how to find answers you were never taught.--Are you a VC- or PE-backed CEO building in energy, infrastructure, or climate tech?Join 45 CEOs and 45 investors and post-exit founders who help each other make better decisions on capital, strategy, scaling, and leadership.See if the CEO community is a fit → entrepreneursforimpact.comGet smarter on energy, infrastructure, and climate tech in 2 minutes.Join 40,000+ professionals getting practical insights on startups, investing, commercialization, strategy, and leadership.Get the free newsletter → entrepreneursforimpact.substack.comHelp more people find this podcast.If this episode was useful, take 20 seconds to follow the show or leave a rating on Apple Podcasts or Spotify. It helps bring these conversations to more entrepreneurs, investors, and executives.

Ottieni 4% annuo lordo x 12 mesi fino a €1 Milione se apri ⁠⁠Conto Corrente Arancio Business di ING ⁠⁠entro il 2/11/26: https://links.madeitpodcast.it/ING Virginia Gambardella ha trasformato una grande community sui social in un progetto imprenditoriale ambizioso: Qura, la startup che vuole rendere la prevenzione e il monitoraggio della salute più accessibili grazie alla tecnologia e all'intelligenza artificiale. In questa puntata di Made IT ripercorriamo la sua storia: da Napoli alla Bocconi, dall'esperienza in McKinsey al mondo delle startup, fino alla decisione di lasciare un percorso sicuro per diventare founder. Parliamo di startup, fundraising, venture capital e intelligenza artificiale, ma anche di tutto ciò che succede dietro le quinte della vita da founder: la paura di fallire, la disciplina, i sacrifici, il rapporto con il successo e la capacità di prendersi dei rischi. Con Virginia affrontiamo anche il suo rapporto con i social media: come è riuscita a costruire una grande community senza diventare schiava di numeri, views e performance, e perché ritiene fondamentale separare il proprio valore personale dai risultati online. CAPITOLI 00:00 Introduzione 01:20 Chi è Virginia Gambardella e da dove parte la sua storia 07:19 Da McKinsey al mondo delle startup 13:37 Come è iniziata la sua crescita sui social 19:41 Come avere un rapporto sano con i social media 24:38 Come nasce Qura 28:30 Da San Francisco all'intelligenza artificiale applicata alla salute 37:20 Come ha raccolto 1,5 milioni di euro per Qura 42:06 Stress, disciplina e vita da founder 43:51 Startup, carriera e maternità 46:23 Il consiglio più importante: non aver paura di fallire Learn more about your ad choices. Visit megaphone.fm/adchoices

Keith Williams is Managing Partner – Credit Strategies and Chief Investment Officer at Crestline Investors Inc. Crestline has a suite of strategies across direct lending, fund liquidity solutions, insurance and reinsurance. Keith was previously a director at Goldman Sachs and an Executive VP at McKinsey in their Recovery and Transformation unit. Our conversation with Keith starts with the work ethic that was instilled in him during his young adult years and how the years working in restructuring shaped his approach to difficult assignments and thinking about tradeoffs. We move then to his launch of the credit strategy within Crestline and some of the ups and downs that came along that trajectory. We end with reflections on what really matters, pulling the lens back to focus on the importance of family and balance. A special thank you to our sponsors at Baillie Gifford and GCM Grosvenor. Baillie Gifford is a long-term investment manager, dedicated to discovering the innovations and changemakers that deliver exceptional growth opportunities for you.GCM Grosvenor is a global alternative asset management solutions provider, with more than $90 billion in assets under management across private equity, infrastructure, real estate, credit, and absolute return strategies.For over 50 years, the firm has helped investors navigate the complexities of alternative investing through a flexible, open-architecture platform. GCM Grosvenor is also focused on what's next. Through its Elevate strategy, the firm supports the next generation of private equity leaders, making seed investments in emerging managers and providing the resources, network, and strategic guidance needed to help them grow. With nearly $800 million raised for its inaugural Elevate Fund, GCM Grosvenor is helping drive innovation and expand access across private markets. Learn more at gcmgrosvenor.com.

This week, Jack Sharry talks with Jim Patrick, Senior Business Advisor at McKinsey. Jim has more than 25 years of experience in wealth management, asset management, institutional investing, and family office advisory services. A former Group President at Envestnet, he now advises McKinsey and other financial services firms on growth strategy, operating model transformation, product development, distribution, regulation, AI enablement, advisor productivity, alternatives, and serving the evolving needs of affluent and ultra-high-net-worth clients.  Jack and Jim explore how the role of the financial advisor is changing as investment products, information, and technology become increasingly accessible. Jim argues that greater choice and complexity make advisors more valuable—not less—as clients look for help making better decisions, managing their behavior, and connecting investments to long-term goals. They also discuss the looming advisor capacity shortage, the growing complexity of alternative investments and regulation, and why UMH can position advisors as the trusted quarterback across a client's entire financial life. Jim also explains how AI can improve advisor productivity while giving advisors more time to focus on what technology cannot replace: human connection and trust. In this episode: (00:00) - Intro (01:30) - How the advisor value proposition has changed (02:50) - Why technology has made financial advisors more relevant (04:23) - The looming advisor capacity challenge (05:38) - Why behavioral coaching creates advisor value (06:52) - Navigating an increasingly complex investment landscape (07:58) - How advisors should approach alternative investments (09:36) - Breaking down regulatory complexity for clients (11:49) - The evolution from UMA to Unified Managed Household (13:33) - Rethinking how financial advice is priced (15:10) - How AI can improve advisor productivity and personalization (17:06) - Why trust remains fundamental to financial advice (19:29) - Technology has democratized access, but not judgment (19:54) - Jim's interests outside of work (21:00) - Jim's advice for the next generation of wealth management leaders Quotes "The biggest shift over the last 29 years I've been in the business is that it's no longer about access to products, services, solutions, or asset allocation, as those things have become more ubiquitous. It's about decision-making and decision-making consistency. Because as consumers engage with more and more information, they become paralyzed." ~ Jim Patrick "While innovation and technology have increased transparency and removed friction, advisors are getting the productivity lift they need, but it's not enough to overcome the real needs of end clients, and that is better and more consistent decision-making." ~ Jim Patrick "The end clients need help managing their expectations, their goals, and the activities they complete to achieve results. And they fail because they panic. They fail because they chase performance. They fail because they get focused on a shiny new lure that goes by." ~ Jim Patrick Links  Jim Patrick on LinkedIn McKinsey Envestnet Capital Preferences Connect with our hosts LifeYield Jack Sharry on LinkedIn Jack Sharry on Twitter Subscribe and stay in touch Apple Podcasts Spotify LinkedIn Twitter Facebook

Jeremy Oppenheim left a top job at the management consulting firm McKinsey&Co in 2016 to become a Founding Partner of and build SYSTEMIQ, at the high water mark of climate optimism. Then came Trump and Brexit. Ten years on, Joe asks him what the movement got right, and what it got badly wrong, from ignoring the politics of decline to vilifying the very incumbents it needed. And most importantly, what does this mean for how we think about what comes next? Conversations with a CE/O is a new series on The Circular Economy where the Ellen MacArthur Foundation's CEO Joe Murphy sits down with leaders whose decisions are shaping the economy and asks one question. We've been working on the circular economy for more than a decade, the next 10 years will look nothing like the last, so how does the work itself need to change?Part 2 of this conversation will be available next week. Subscribe to the podcast and never miss an episode.Links:SystemIQ at 10 - https://www.systemiq.earth/systemiq-at-10/Blue Whale Enquiry - https://www.systemiq.earth/reports/bluewhale/Subscribe to The Ellen MacArthur Foundation for more insightful videos: https://www.youtube.com/channel/UCQAC2otE5_agzHZPnk3mE5w?sub_confirmation=1Follow us online on these channels:Instagram: http://instagram.com/EllenMacArthurFoundationLinkedIn: https://www.linkedin.com/company/ellen-macarthur-foundation/Website: http://www.ellenmacarthurfoundation.org

Dependence on consulting firms is a growing trend among governments globally. Left unchecked, it can have a negative impact due to high costs or transparency issues. Such dependence came to the fore in France a few years ago, when the Macron government was criticised for its close ties with US consulting giant McKinsey. UNESCO's Inclusive Policy Lab, headed by Iulia Sevciuc, has established a new blueprint to tackle this problem. She spoke to us in Business.

Envision a fraud detection model embedded in a bank's AI system, continuously monitoring transactions for unusual activity. The warehouse behind it updates itself every 15 minutes; however, that seems like a short interval. A fraudulent transaction took place 13 minutes ago, and the model still hasn't picked it up. The thing is, the model is not faulty. The data being fed to it had already overlooked the critical moment. But how?In this episode of the Don't Panic! It's Just Data podcast, host Shubhangi Dua, Podcast Producer and B2B Tech Journalist at EM360Tech, sat down with guest Sundar Nathan, VP of Product Marketing, Enablement and Academy at Striim. They discuss the gap that exists between the time an event takes place in a production system and the time an AI agent becomes aware of it. As the frontier models from companies such as OpenAI and Anthropic become more commonplace, the model ceases to be a source of competitive advantage for any enterprise. What remains then is the data beneath the model and the speed at which that data actually moves.“I'd go even a step further and state that in 18 months the model you select will be less important to you than the data which is feeding that model,” Nathan said.'Everybody Is Renting The Same Brain'Alluding to his personal experience, Nathan tells Dua that his "superpower was memory,” particularly, the ability to remember circuit diagrams and organic chemistry structures as clearly as in a photograph when taking an exam. But with the introduction of Google search, that memory ceased to be an advantage since everyone had the same tool at their disposal.Why is that experience relevant? It's similar to the use of AI in the enterprise today. "Your competitor next door has access to the same frontier models at the same price, roughly on the same day," he says. According to the Striim Marketing VP, what a competitor cannot rent is an enterprise's operational data, its business insights and "the institutional knowledge accumulated over decades", in particular, how close an agent's view of production data is to the actual data. "The time gap between the agent and where your production data is measured is the new source of competition," he adds.Also Read Use Case: UPS Leverages Striim and Google BigQuery for AI-Secured Package DeliveryRead Use Case: The Hyper-Responsive Payments OrganisationTakeawaysThe model matters less than the data feeding it within 18 months, Viswanathan predicts.Four Cs of AI-ready data: current, consistent, consumable, contextual.Only 23% of enterprises scale AI agents past pilot stage (McKinsey).Change data capture reads transaction logs directly, in real time.Governance built for non-human users masks PII/PHI before agents see it.Chapters00:00 - Why AI advantage is moving from models to real-time data02:06 - Sundar's path from memory-based learning to simplifying complex tech04:10 - Why “everyone is renting the same brain”06:52 - Why impressive pilots fail in regulated production workflows08:30 - The four audit questions that block deployment10:43 - Why 15-minute refreshes are not real time for fraud13:25 - Why enterprises need a nervous system, not a warehouse scan15:52 - How consumable data turns raw events into agent-ready context18:29 - What Stream's intelligent pipe does in practice21:12 - Governance for non-human users and mission-critical guarantees22:26 - Stop benchmarking models and start benchmarking data staleness25:45 - Final takeaway: it really is just data, but it must move faster

 Rohit Pathak |  CEO of Copper business of Hindalco Rohit Pathak is the CEO of Birla Copper, the largest Copper player in India and #3 globally for Copper Rods outside China. This is the Copper business of Hindalco Industries Limited, a flagship company of the Aditya Birla Group.Mr. Pathak is a Director on the National Executive Council of IEEMA since 2019 the industry association of the electrical equipment industry in India and the President of the Association for the year 2022-23. Mr. Pathak is also the President of the Indian Primary Copper Producers Association IPCPA since 2022 and a Director of the Fertiliser Association of India FAI since 2021.Prior to moving to Birla Copper, Mr. Pathak was the President & CEO of Aditya Birla Insulators largest Insulator player in India and 3rd largest porcelain player globally, where he led its diversification into Composites and the growth of the international business. He was also appointed the first CEO of Aditya Birla Power Composites Limited, a JV of Grasim Industries Limited with Maschinenfabrik Reinhausen of Germany for Composite Hollow Core Insulators.Mr. Pathak joined the Aditya Birla Group in 2011 as the Principal EA to the Chairman, Mr. Kumar Mangalam Birla. In that role he advised Mr. Birla on key priorities such as M&A, organic growth, and special initiatives and strategic planning & monitoring across the Group Businesses, and helped the businesses on strategic issues. He is a recipient of the Chairmans' Award for Exceptional Contribution in 2015.Prior to joining the group, Mr. Pathak  was an Associate Principal at McKinsey & Company, where he worked on diverse issues such as new market entry, business turnaround, inorganic growth, large scale performance transformations, and business plan development and delivery. He also led the Procurement practice and co-led the Automotive & Assembly practice in India for the firm.Mr. Pathak has done his PGDM from the Indian Institute of Management, Ahmedabad India and Electrical & Electronics Engineering from BITS Pilani Pilani Campus, India. He is a recipient of the Prof L K Maheshwari Distinguished Alumnus Award 2023, awarded by the EEE Dept of BITS Pilani. 

Magnus Grimeland grew up in Holm outside Sande, Norway, in a community he remembers as having around 50 to 70 people.At 16, he left Norway for UWC Atlantic College in Wales. He later studied at Harvard, served in the Norwegian Special Forces, worked at McKinsey, helped build Zalora and Global Fashion Group in Asia, and eventually founded Antler.Today, Antler receives around 160,000 founder applications a year and backs hundreds of new companies globally. In this conversation, we talk about why Magnus believes AI is the biggest platform shift he has experienced, why technology itself is becoming less of a moat, and why distribution increasingly matters. We also go into what Antler looks for in founders before the numbers exist, the importance of spike, drive and grit, why European founders often sell too early, Norway's tax debate, Singapore, mental resilience, Janteloven, success and purpose. Music licensed through Soundstripe.Codes: ACRUT3HZ9EFCI399, 5OQTOAM7HCOAXEPU, TJ1X8CVRHVSNVNUS

Why do pet owners so often learn the limits of their insurance when an animal is already ill and the veterinary bill is growing? That trust problem sits at the center of my conversation with Hedda Båverud Olsson, co-founder and CEO of Lassie, a pet insurer that combines coverage with preventative health guidance, rewards, activity tracking, and AI-assisted claims. Hedda's reason for starting Lassie is personal. Her mother is a veterinarian, and Hedda grew up around healthy pets without fully appreciating how much fear and financial pressure many owners experience. After working at McKinsey and EQT, she became absorbed by an idea she describes as putting her mother in every owner's pocket. The aim was to help people understand risks earlier and make better daily choices, rather than waiting until an animal needed treatment. The claims process shows where AI can offer immediate value. Lassie has developed a system called Bark Office that scans an invoice, reads each line, identifies whether the treatment relates to illness or an accident, checks the policy, and decides whether enough information is available. Hedda says that when the system is confident, the money can reach the customer in around six minutes. She reports that approximately 65 percent of claims in Germany follow that route. Automation has limits, especially when a blurry receipt, missing diagnosis code, incomplete journal, unusually expensive treatment, or uncertain policy detail prevents a reliable decision. Those cases can prompt a request for further information or move to a human reviewer. Hedda says customers receive a line-by-line explanation of what was and was not covered, with the option to dispute a result and request another review. She reports an error rate below 2 percent for automated claims and compares it with what she describes as a 5 percent human error rate across insurance. Those are Lassie's figures, but the operating principle is useful across many regulated services: automate clear cases, explain the result, and give uncertain or sensitive cases to a person. We also consider why an insurer should have a role when nothing has gone wrong. Hedda says over 90 percent of Lassie customers use its app and roughly a quarter use it daily. Owners can watch health videos, complete quizzes, follow life-stage guidance, record activity, and earn rewards that can reduce their insurance price. Advice changes according to breed, age, and season, covering subjects such as weight, joint health, toxic foods, nail trimming, and ticks. Lassie also works with Tractive, allowing customers to connect a tracker and bring activity data into the app. Hedda explains that Lassie customers can receive a tracker while paying the Tractive subscription, and existing Tractive users can connect their current device. Owners who do not want a tracker can record activity manually. The feature gives the company another regular point of contact while helping customers follow their pet's routine. That daily relationship has commercial consequences. Hedda says regular app use supports customer loyalty, reduces churn, and raises lifetime value. Preventative actions may also support lower prices for owners. The opportunity is to make insurance useful before a claim, although firms must avoid turning care advice and rewards into confusing conditions or allowing gamification to distract from clear coverage. The conversation moves to the UK, where the supplied briefing estimates that around 20 million pets remain uninsured. Hedda believes culture and distrust may outweigh price alone, comparing the UK with Sweden, where she says approximately 90 percent of dogs and 50 to 60 percent of cats are insured despite higher prices. She also argues that established insurers have been slowed by old systems and disconnected technology, making simple onboarding, mobile service, and automated claims harder to deliver. For Lassie, the test is knowing where automation improves the experience and where it would make a difficult moment worse. Customers may welcome an administrative claim completed in minutes, but few want to speak with a bot when a pet is seriously ill or dying. That distinction between speed and empathy may be the most useful lesson for any business automating emotionally sensitive work. Can insurance become something customers value every day without losing the clarity and human care they need during a crisis? Listen to the episode and share your thoughts with me.  

Send us Fan MailDivya spent 8 years at McKinsey. She sat down with Sanya, a senior at Penn, and ran a case with her, live.Divya told her afterward it would've passed a McKinsey Round 1. Listen to learn how Sanya did it – built her structure, worked the math, and landed on a recommendation. Then Divya breaks down what worked and what she'd tighten up.Resources:Bates White is hiring undergrad summer consultants for 2027 and economists for PhD candidates – apply hereWant this type of feedback from an ex-McKinsey expert coach? Join the Black Belt programConnect With Management ConsultedCreate a free MC account or download the MC app (Apple, Android) to start your prep todaySchedule a free 15min consultation with the MC TeamWatch the video version of the podcast on YouTubeFollow us on LinkedIn, Instagram, and TikTokJoin an upcoming live event – case interviews demos, expert panels, and more

Great leadership isn't just about having the right strategy—it begins with understanding the person making the decisions. In Manage Yourself to Lead Others, Margaret Andrews argues that self-awareness is the foundation for leading with clarity, confidence, and empathy. Then, The Journey of Leadership, by Dana Maor, Hans-Werner Kaas, Kurt Strovink, and Ramesh Srinivasan, draws on McKinsey's work with hundreds of CEOs to explore the inner transformations that make leadership sustainable.

AIUC first got our attention with the NFDG backing, and have just announced a $40M series A today, with the most impressive industry advisor list we may have ever seen for an early startup behind AIUC-1, their agent standard backed by real insurance:From being Anthropic's first product hire to building the standards, testing, and insurance infrastructure meant to make frontier AI deployable, Rune Kvist is betting that the biggest constraint on AI adoption won't be capability it will be trust. In this episode, the AIUC cofounder joins swyx and Vibhu to announce a new $40M round and explain why companies like Cursor, Harvey, Lovable, and ElevenLabs are increasingly confronting a problem that gets harder as AI gets better: who is responsible when autonomous systems fail?We go deep on AIUC-1, the emerging standard for agent security, safety, and reliability; how AI agents are stress-tested for jailbreaks, hallucinations, and data leaks; and why Rune thinks standards and insurance could become critical infrastructure for AI. We also discuss the growing trust gap between governments and frontier labs, AI-enabled cyber and biological risks, why every model can ultimately be jailbroken, what happens when a $20 coding agent causes $200M of damage, whether AI engineers should be certified, and why even after AGI there may be one job the labs can never do themselves: be their own watchdog.We discuss:* Why risk, liability, and trust may become the binding constraint on AI adoption* Rune's path from reading the Scaling Laws paper to joining Anthropic in its earliest days* What Anthropic understood about scaling, compute, and the future years before it became obvious* Why Waymo illustrates the gap between AI capability and real-world deployment* AIUC's $40M round and work with Cursor, Harvey, Lovable, ElevenLabs, and other frontier AI companies* AIUC-1: a standard for AI agent security, safety, and reliability* How agents are tested for jailbreaks, hallucinations, and data leakage* Why most AI companies optimize the happy path without seriously stress-testing adversarial cases* Why AI standards may need to update every quarter instead of every decade* The emerging trust gap between frontier AI labs and governments* Cybersecurity, child safety, biological weapons, and the expanding frontier-model risk surface* Why standards and insurance may need to evolve together* How Lloyd's of London can insure AI systems and bring trust to enterprise deployment* What happens if a $20 Cursor subscription contributes to a $200M plane crash* The Air Canada chatbot case and how AI failures are beginning to clarify legal liability* Why copyright may be one of the hardest AI risks to insure* Evals, mechanistic interpretability, monitoring, and models becoming aware they're being tested* The impossible CISO mandate: adopt AI fast, but don't let anything go wrong* Why robotics will make AI liability dramatically more consequential* Whether AI engineers should have Level 1, 2, and 3 certifications* AIUC's roadmap across agents, frontier models, robotics, and universal red teaming* Why AGI could become a question of national sovereignty* Why the labs can never fully serve as their own watchdogs* The Big Short problem: how do you stop competing watchdogs from racing standards to the bottom?Rune Kvist* LinkedIn: https://www.linkedin.com/in/runekvist/* X: https://x.com/RuneKvistAIUC* https://aiuc.comTimestamps00:00:00 AIUC's $40M Round and the Risk Bottleneck for AI00:01:07 From Scaling Laws to Early Anthropic00:07:58 Why Trust, Not Capability, Could Limit AI Adoption00:12:19 Founding AIUC and Building AIUC-100:18:52 How AI Agents Are Audited and Stress-Tested00:25:26 Frontier Models, Government, and the AI Trust Gap00:33:32 Cyber, Child Safety, and AI-Enabled Biological Risk00:38:14 Why Standards and Insurance Belong Together00:41:45 What Does an AI Insurance Policy Actually Cover?00:50:44 The $20 Cursor Subscription and the $200M Plane Crash00:53:53 AI Liability, Monitoring, and Earning Enterprise Trust00:56:21 From AI Agents to Models to Robotics00:58:29 Copyright, Adverse Selection, and AI Insurance01:03:28 Evals, Mechanistic Interpretability, and Eval Awareness01:08:36 The Impossible Enterprise AI Mandate01:11:52 Prediction Markets vs. AI Audits01:14:43 Should AI Engineers Be Certified?01:19:10 AIUC's Roadmap, AGI, and Who Watches the Watchdogs?TranscriptIntroduction: AIUC, the $40M Series A, and Risk as the Adoption BottleneckSwyx [00:00:00]: Okay, we're in the studio with Rune from AIUC, the Artificial Intelligence Underwriting Company, with our trusty co-host, Vibhu. Welcome.Rune Kvist [00:00:10]: Thank you. Thanks for having me. Thank you.Swyx [00:00:11]: What are you announcing today?Rune Kvist [00:00:12]: We have raised $40 million, led by Ribbit Capital and First Harmonic.Swyx [00:00:17]: You first came to my attention when Nat and Daniel invested in you guys. Is the story, like, pretty much the same? Like, what are you today versus what you thought you were back then?Rune Kvist [00:00:26]: When we raised our seed round, we had a hypothesis that at some point risk was going to hold down adoption. At that point in time, that felt kind of hypothetical, and I think that is now over. Clearly, the moment is now with Mythos and Fable. It's pretty obvious that literally the binding constraint on adoption is risk. And so for us, it feels like this is a natural continuation of the same hypothesis, but where previously it was speculation, now it feels like fact.Swyx [00:00:54]: And let's get a list of the customers that you're highlighting as part of your Series A.Rune Kvist [00:00:58]: Totally. Yeah. So we are now working with folks like Cursor, Harvey, Lovable, ElevenLabs.Swyx [00:01:05]: Yeah. Amazing. Congrats.Rune Kvist [00:01:06]: Thank you.Swyx [00:01:07]: So you were famously one of the first hires involved in GTM and product. I'm just kind of curious: what was your path into AI? Just recap.Rune's Path Into AI: Scaling Laws, Capital, and AnthropicRune Kvist [00:01:18]: Yeah.Rune Kvist [00:01:19]: Late 2021, I sold a company, my first company, an edtech company. I had a bit of time to think about what was next. I came across the Scaling Laws paper, and that just struck me like lightning. I was just like, “This is a big idea.” In short, the Scaling Laws paper just says the bigger the model, the smarter the model.Swyx [00:01:38]: So this is the Kaplan one, not the Chinchilla one?Rune Kvist [00:01:40]: Exactly, the Kaplan one.Swyx [00:01:42]: Yeah.Rune Kvist [00:01:42]: And the important thing that clicked for me there was, oh, now capital will understand this. If you put in more money, you get more money out, and so that will kick off a hype cycle. And so you get a sense of predictable returns, which is, in fact, what's played out. And so I just packed my bags. I'd never been to San Francisco. I'd never been there. I just packed my bags, flew out here to find the people who had written it. And at the time, they had just started a small lab called Anthropic. There were around 40 people at the time or so. Drank a bunch of coffee until I eventually got introduced to Dario. And at the time, they were wrestling with some of these questions of, like, should we deploy our models? Should we make revenue? How should we engage with the rest of the world? They'd just broken off from OpenAI, and it's been publicly reported that they were kind of concerned with how they were dealing with deployment. So they were wrestling with some of those questions. At this point, this is early fog of war, like early 2022. The hottest product at the time was, like, Jasper. Like, there's nothing out there. So where value was going to accrue, and what the different parts of the stack were going to be, were all open questions.Swyx [00:02:48]: I want to highlight to people, you ask these questions because you have a PPE background.Rune Kvist [00:02:52]: Yes.Swyx [00:02:52]: I actually was in Singapore in one of the sort of feeder programs for prepping people for PPE. So I had a tutor. We learned, you know, philosophy and politics and economics. But, like, I think your kind of background matters. Machine learning people who read the neural, Scaling Laws paper would not necessarily draw the same conclusions that you did. Whereas any capitalist would read that and go, “Holy s**t.”Rune Kvist [00:03:19]: Correct.Swyx [00:03:20]: Right?Rune Kvist [00:03:21]: Yes.Swyx [00:03:21]: Who tipped you onto that paper? Because it's not a paper that you normally read, right, like, in your circles?Rune Kvist [00:03:26]: Yeah. I think I'd actually, ever since AlphaGo, had some appreciation that AI was a big deal.Swyx [00:03:36]: Yeah.Rune Kvist [00:03:36]: But it kind of felt like it raised all these kind of interesting philosophical questions, but it was kind of not clear from afar where exactly that would go. But it was obvious enough that it was like, this is going to be a big thing if we find the kind of right mechanism to kind of get the techno-capital machine to work on this. But it was just not clear. And so I think there was some way in which, like, that became obvious, and also it wasn't as obvious at the time than it is now, right? Like, it was just like, wow, this is so interesting. But it still felt, coming from kind of a philosophy and economics background, it felt like if this turns out to be true, you're going to be wrestling with all of the big questions in society. Everything you've learned about politics gets thrown out of the window. Everything you've learned about economics at least gets challenged. And so what felt interesting was to be at that frontier that has ramifications across everything. So that's why I sought it out.Swyx [00:04:32]: I mean, clearly really good insight. For people who don't know, the PPE program is, like, where prime ministers are born. So then you end up meeting Dario.Rune Kvist [00:04:41]: Yep. First Dario, yeah.Swyx [00:04:43]: Yeah. Well, I mean, like, so did you get extra insights from talking with them that you didn't get from your original hypothesis?Anthropic's Early Conviction and the Scaling Laws Crystal BallRune Kvist [00:04:50]: If you read the Scaling Laws paper, you get this, like, very vague sketch of like, wow, this seems kind of important. There are some lines on a chart. This seems kind of important. And what I think the team at Anthropic had thought more about than anyone was like, what are the implications of this if you really play this out? And back then they had, kind of vision documents for what the world would look like in 2026, and they were kind of in vivid detail playing out how much compute is going to be needed, what the CapEx was going to look like, what some of the societal concerns were going to be, but also what is the amount of economic value coming out here? And so it kind of felt like they held a crystal ball that in hindsight turned out to just be dramatically correct. And they weren't holding it like they were obviously correct. They were just like, “Take this hypothesis really seriously.”Swyx [00:05:38]: Think it through, yeah.Rune Kvist [00:05:38]: And think it through in the same way as the kind of situational awareness that isSwyx [00:05:43]: Across the street.Rune Kvist [00:05:44]: Across the street.Swyx [00:05:44]: Your office, yeah. Oh my God, we're all living across the street in the same one square mile.Rune Kvist [00:05:50]: Correct. And that's now a couple of years old, but also people keep referencing it these particular weeks with Fable and Mythos, and it's like, wow, if you take this one idea seriously- For the Scaling Laws, a lot of things fall into place.Vibhu [00:06:03]: And keep in mind, at this point, this is the same team that did GPT-1, GPT-2, and GPT-3.Rune Kvist [00:06:08]: Correct.Vibhu [00:06:08]: Which is also, like, it's not just some experimentation. Like, this is a real model that we just scaled up.Rune Kvist [00:06:14]: And they had deep conviction in this idea: if you take a big blob of compute and data, it just wants to learn, and out of that will come smarter and smarter models. And all the particulars were not clear.Vibhu [00:06:26]: Yeah.Rune Kvist [00:06:27]: And all the implications were not clear. But their deep conviction in this, like, core thesis, and that was kind of dizzying. It was both phenomenally interesting and exciting, and also very quickly you get to, like, the world we know today will no longer be if this hypothesis holds. So it also just felt, like, important in some kind of grand sense.Vibhu [00:06:48]: What kind of shaped you there? So that was early 2022. Not only had GPT-1, GPT-2, and GPT-3 come out, but, you know, the amazing founders of Anthropic that have never split up, the only ones, they actually had the conviction to leave OpenAI, start their lab. You said there were about 40 people there. What was the time like there?Inside Early Anthropic: Mission, Deployment, and RiskRune Kvist [00:07:06]: It was kind of remarkably like what it looks like on the outside today. Extremely cohesive, extremely mission-oriented, and living in this tension between their two ideas, which is AI could both go really well and really bad, and we want to be part of building it. That creates astounding amounts of tension. And they were wrestling with this incentive challenge where they know they're in a race that they're in where you might get forced to cut corners, but it also felt very important to them to be at the forefront of technology. And all of those ideas were just present at that time. It kind of feels like that line has been just very clear, and I think kind of love them or hate them, they have really stuck to their guns. There's a core set of beliefs that they hold more deeply than most companies hold any beliefs.Vibhu [00:07:58]: Yeah. Fast-forward to today.Rune Kvist [00:08:00]: Yeah.Vibhu [00:08:00]: What does that lead us to AI underwriting company? What are you up to? What motivated you to start this?From Waymo to AIUC: Confidence Infrastructure for AIRune Kvist [00:08:05]: Yeah. AIUC builds confidence infrastructure for frontier AI through standards and insurance. The link from Anthropic to building confidence infrastructure, looking out the windows at Anthropic offices and seeing Waymos driving by. Already back then, early 2022, Waymos were in some ways like AGI for cars. Like, they were superhuman drivers, but you couldn't take one to the airport. And now, four and a bit years later, you still can't take your Waymo to the airport, despite now everyone having kind of looked at the evidence and being like, “They're better drivers than humans.” So in that particular instance, what's clear is that the binding constraint on AI being useful is not capability, but is that liability or risk or trust. That problem is, general. The reason why right nowRune Kvist [00:08:52]: Fable is not open for access is not because it's not a good model, it's because it's a very good model. It's just hard to make promises about what it will or will not do. And this problem gets worse as AI gets better. Basically, more intelligent AI can be more autonomous. That's more valuable, but also the risk surface grows. And so - what Waymo illustrates is that unless you build the confidence infrastructure to make promises about AI, or at least bring light to the risks, you grind adoption to a halt. Governments, banks, hospitals, militaries need to have some sense of what AI will and will not do to be able to operate for them to incorporate it. And that's the problem that we're trying to solve. Now, why standards and insurance? If you trace this problem back through history, every technology wave has had some version of this problem. So if you go back to, like, year 1900, electricity comesVibhu [00:09:47]: Ben Franklin.Rune Kvist [00:09:48]: Cars burn down, sorry, houses burn down, lots of people die. 1930s, cars are a big deal, kill lots of people. 1950s, private nuclear energy is a big deal, poses big risks. In each of those instances, the market runs ahead of regulation to create confidence infrastructure because that's required to make go/go decisions. That is required for adoption, and the market fundamentally wants adoption. And in all of those instances, common blueprint emerges between standards and insurance. The reason these two components is standards kind of provide the rules of the road, and they also specify, like, what are the tests that need to be run so we can get a sense of how high the risk is. So take in the case of cars, that's like a car crash. Great, everyone, they inform your insurance pricing today, they inform your purchasing decisions, et cetera. That's basically the risk framework. The insurers are important because they pick up the bill. So they are the private institution that is most on the side of. That is best incentivized to quantify the risks truthfully and then figure out all the ways to reduce the risk ‘cause that increases their profit. So they're basically, they help shape the incentives. And these two work really well in unison. Now, how does that show up as a company? Well, one of the things that was obvious even - or starting to become obvious even a couple years ago was that frontier companies, some of our customers today, like Cursor, Sierra, ElevenLabs, Harvey, were going to have a very easy time selling a pilot to a bank. The, like, the demo just sells itself. It's magic. But bringing that through, if you want to do a wall-to-wall rollout at a bank or a hospital, you have to go through the risk process. These banks have no idea even which questions to ask, let alone which answers are sufficient, let alone, like, how do they go and test whether these agents actually work the way they're supposed to. And so they had this problem of, like, what can we say to earn the trust? And we think there's, like, a golden sentence that goes something like, “Hey, I hear you're really worried about hallucinations or jailbreaks or whatever it may be. We've had an independent third party test us against the gold standard. We passed with flying colors. And as a vote of confidence, the world's most conservative insurers have looked at the data.” And they're willing to take some of the risk onto their balance sheet.Swyx [00:12:06]: Yeah.Rune Kvist [00:12:07]: So if something does go wrongSwyx [00:12:07]: There's money behind it, yeah.Rune Kvist [00:12:09]: Exactly. So that's kind of like the link between all this. We can get into some of the hard parts related to the technical testing, which is, I think, the crux of the matter, but I'll pause there.Swyx [00:12:19]: How did you and Rajiv come together? This-- there's always, like, you come across very confident and, you know, and we're announcing your Series A and all these things, but I want to see, like, the early initial stages of, like, idea formation.Cofounding AIUC with Rajiv DattaniRune Kvist [00:12:31]: Yeah. Rajiv is actually my soon-to-be brother-in-law.Swyx [00:12:35]: Oh.Rune Kvist [00:12:36]: So I'm actually, in a week and a half getting married to Rajiv's sister.Swyx [00:12:42]: Okay, now you're tight.Rune Kvist [00:12:44]: Exactly.Swyx [00:12:44]: Now you know.Rune Kvist [00:12:45]: So - Rajiv and I have known each other for a decade. Funny story, I met both Rajiv and his sister, Hena, at the same time when Hena and I were interns at McKinsey in London, and Rajiv was assigned as my mentor. And so met them at the same time. For the longest time, it was not obvious that we were necessarily going to work together. I was in startups. He was, an insurance partner at McKinsey. Three or four years ago, I think Hena convinced him that AI was going to be a really big thing. And so he quit his job, cushy partner job at McKinsey in London, packed his bags, flew to San Francisco, and ended up joining METR. You guys are probably online enoughSwyx [00:13:24]: CEO.Rune Kvist [00:13:24]: Exactly.Swyx [00:13:24]: We've, we've, we've heard of METR.Rune Kvist [00:13:25]: You see the plot-- the chart of the horizons of the tasks that agents can take on is doubling extremely fast. So he was COO at METR, led their partnerships with Anthropic and OpenAI to test their models before release, but also working closely with the US and UK government, to figure out, like, how do you know whether a model can be released? And in some ways, that was, like, the perfect background. He's spent a lot of time in insurance, knows that world, spent a lot of time with frontier testing of models. And so when I was bumbling around this idea space, starting with some of the ideas we talked about related to Waymo, as soon as we got into the content, we were both like, “Oh, this would be an amazing business to build together.” This is wrestling with the problem that we both think is the most important in the world from a market angle, which is kind of our intuitions is that the market can do a lot, and the faster AI moves, the harder it is for government to solve some of these problems. And then it took a little bit of time to work through what is it like to work with family.Swyx [00:14:27]: Sure.Rune Kvist [00:14:27]: And,Swyx [00:14:30]: Because you were already dating at the timeRune Kvist [00:14:31]: Yeah. Yeah, exactly.Swyx [00:14:33]: Yeah.Rune Kvist [00:14:34]: Already back then, itSwyx [00:14:35]: Yeah.Rune Kvist [00:14:35]: We felt like we were a family.Swyx [00:14:36]: Nice.Rune Kvist [00:14:36]: And so starting a business together felt like kind of a big step. And, here we are with just immense amounts of trust.Vibhu [00:14:43]: Yeah. So now you're a company of how big? How big are you guys now?AIUC-1 Certification: Agent Security, Safety, and ReliabilityRune Kvist [00:14:46]: There are just 20 of us now.Vibhu [00:14:47]: 20 of you guys now, have Series A, and you have your first certification out, the AIUC-1. Let's bring up the certification. So this is the agent certification, right? What goes into the process? I have, like, two questions here. One is, walk us through the certification, and two is, what is the process for a company to get certified, you know?Rune Kvist [00:15:08]: Great. As it says right on the top, AIUC-1 is a standard for agent security, safety, and reliability. The fundamental design principle is take all of the concerns that slow down adoption, so all the questions, all the fears that keep, security leaders in the Fortune 1000 up at night, and put them into one comprehensive framework. That's what you'll see there. You can see the six categories. Two, you want to ground all of this in technical testing. So one of the concerns with security standards that often feel kind of like theater paperwork is that they're not actually ground out in, does any of this work? Does any of this matter? And so we had a conviction from early on that was going to be the kind of crux, was to pass this, you must get tested every quarter, basically run thousands of simulations to see, well, so can it actually be jailbroken? How hard is it to jailbreak? How often does it hallucinate? How often does it leak data? Et cetera. And then the last, core idea here, if you scroll up to the top here, is to refresh it quarterly.Rune Kvist [00:16:08]: So the core trait of AI is that it moves extremely fast. Whatever concerns we're discussing today were not the same ones three months ago, and this will keep changing. Typically, standards update on a, like, a decade cycle is obviously not going to work. But the question is kind of how do you update it? And the core thing here was to basically get the risk leaders of the Fortune 1000 around the table. So if you go over to the left hereVibhu [00:16:32]: YeahRune Kvist [00:16:32]: You'll see the AIUC-1 consortium. The consortium is a group of risk leaders who run real banks, real hospitals, real critical infrastructure, who are facing these challenges every day. And we meet with these folks twice a quarter and hear what's top of mind, what is keeping them up at night. There's tremendous amount of desire for that conversation. And then we operationalize that into a specific standard that gets into. And actually, we can go into and look at whatVibhu [00:16:55]: YeahRune Kvist [00:16:55]: What even is the standard. So if we go back to introduction, out there to the left, scroll up a little bit to the wheel, click into reliability. So if you take something like hallucinations sits in reliability. There is a number of requirements here. If you go into the top one, prevent hallucinated outputs, hallucinate outputs, this is one particular requirement. This is a technical control. Basically, we want some kind of ground in this filter. The first thing you see here is what's called a crosswalk. So everyone and their grandmother has put out a framework, very high-level framework for what are the AI risks.Swyx [00:17:27]: This is basically your competition,Rune Kvist [00:17:28]: In some ways our competitionSwyx [00:17:29]: Not seriously, yeah.Rune Kvist [00:17:30]: We're, in fact, friends with them. We'll come back to why.Swyx [00:17:31]: Yeah.Rune Kvist [00:17:32]: But mapping everything together so you have one superset. The claim you're trying to support here is, if you follow this framework, then you can also see how you follow the other frameworks. But the meat of it comes down here in control activities and evidence. So control activities is like, great, you have this high-level requirement. How do you turn that down to something operational? Here's what you must do, and then what is the evidence that we're looking for?Rune Kvist [00:17:57]: And the reason we go this deep is that there's actually not that much confusion about what are the big concerns in AI. Everyone agrees to these. The question, like, what are you actually supposed to do? And so. What we found a lot of demand for is getting down to the specific evidence, that people need to look for. Whether you are Cursor building something or, even JPMorgan building something, but also if you're just a risk leader at JPMorgan, like what exactly should you ask for? What can you ask for without sounding stupid? Like if you ask for some-- you won't believe the amount of time a risk leader has asked for the IP rights to the underlying model to Cursor or something, and you're just like “Sorry, what?” Like,Swyx [00:18:39]: You slip it in there and you seeRune Kvist [00:18:40]: SlipSwyx [00:18:40]: See if you notice.Rune Kvist [00:18:41]: See if they. Exactly.Swyx [00:18:42]: Yeah.Rune Kvist [00:18:42]: Put that in the questionnaire. All right, so that's kind of what our standard is, and we update this every quarter with these folks, to keep up with the latest concerns.Swyx [00:18:51]: Can I double-click on this one?Controls, Evidence, and Third-Party TestingRune Kvist [00:18:52]: Yeah.Swyx [00:18:52]: So first of all, the website's beautiful. Like, it's so confidence-inducing which is the whole point where, like, okay, I know exactly what I'm signing up for when I talk with you. Like, I don't even have to talk to you. I can just see your whole, certification, which is great. But, like, okay, so from here, like D001.1 configure a groundedness filter, how does that get applied? Like, you have a person thatRune Kvist [00:19:16]: Yeah,Swyx [00:19:16]: Goes through it?Rune Kvist [00:19:17]: If you, go backVibhu [00:19:19]: I did see somewhere there's like, you know, fifty-one requirements, a hundred thirty controls. There's like a wholeSwyx [00:19:25]: Right. I just want to. Like, to me, this doesn't translateVibhu [00:19:27]: Yeah.Swyx [00:19:27]: Into a test or an eval.Rune Kvist [00:19:28]: Yes. So if you go into, on the left-hand side. So actually, if - before we go in there are three types of requirements. The first is technical controls, like you must implement some guardrails.Rune Kvist [00:19:42]: Two, there are test controls. So you must have an independent third party go and run some tests against you. I'll show you one of those in a second. And then three, there are policy controls. For example, you must have a person whose name is on the line when you guys f**k up, and you must have a plan for how you tell your customers and how you engage with them. They're kind of more traditional, standard type stuff. So in this particular instance, we just check whether they in fact have a ground in filter. So we will partner with an auditor. So we partner with auditors like KPMG or like Schellman who go in and do the thing auditors do, which is to check the evidence. In this case, that might be a screenshot, it might be part of the code that they need to review to see that it actually. Just that it exists.Swyx [00:20:21]: Oh, okay.Rune Kvist [00:20:22]: And then the second thingSwyx [00:20:22]: So you're not testing the effectiveness of it.Rune Kvist [00:20:24]: That's the second thing. So if you go downSwyx [00:20:25]: Yeah.Rune Kvist [00:20:25]: To the third-party testing for hallucinations out on the left, that's basically the next requirement. This is where we test how well does it actually work.Swyx [00:20:32]: Okay, and is it you testing or the auditor?Rune Kvist [00:20:34]: We test them.Rune Kvist [00:20:35]: We test them.Swyx [00:20:36]: That's a lot of work.Vibhu [00:20:37]: How long does testing take? So if I want to get certified, justCertification Timelines, Remediation, and Quarterly UpdatesRune Kvist [00:20:40]: Yeah.Vibhu [00:20:40]: How long does the end roughly take?Rune Kvist [00:20:42]: Yeah, the end, almost always is dependent on, like, our customers needVibhu [00:20:47]: Yeah.Rune Kvist [00:20:47]: To look something for us. It takes somewhere between, like, 3 to 10 weeksSwyx [00:20:52]: Yeah.Rune Kvist [00:20:52]: Depending on how up to snuff they already are. So some people show up to us with, like, extremely rigorous security programs. When we test them, it works extremely well. We can get that done very quick. Some people come to us, and they're not that far along. We give them kind of the spec that they need to build towards, and then their security teams and engineers get to work and build to meet the standard. The testing itself typically takes a couple of weeks, including the time for them to remediate. Often, we'll find something that we cannot pass, where this is actually just not up to the standard. - you won't pass the standard. And then they will need to go and implement additional safeguards or additional remediation that makes them more robust so that they can actually kind of hand on heart look at their customers in the eyes and say, like, “Hey, we've done truly our very best.”Vibhu [00:21:35]: And they're certified for a year and have quarterly updates?Rune Kvist [00:21:38]: Correct, yeah.Vibhu [00:21:39]: And, yeah, it's pretty interesting. I think, you know, what's changed since. So this is certifying agents in production, right? Your customers, like you've had Lovable, ElevenLabs, Intercom, and they've all gone through this certification.Rune Kvist [00:21:50]: Yes.Vibhu [00:21:51]: What has changed? So I see you post, like, you know, Q2 added MCP agent,How Agent Risks Are Changing: Coding, MCP, and Agent-to-Agent InteractionsRune Kvist [00:21:56]: Yeah.Vibhu [00:21:56]: agent communication. Any other things that you want to kind of highlight since the first iteration? What comes in quarterly?Rune Kvist [00:22:03]: Yeah. So some of the changes have just been agents are not just one thing. So, like, if you take agents like Cursor and compare them to Sierra, they're really quite different. And compare them to Harvey again, compare them to you out of againSwyx [00:22:16]: ElevenLabs, yeah.Rune Kvist [00:22:17]: ElevenLabs, they're all quite different. And so we wanted to design a standard that works for all of the types of agents. And we started with one that was, like, pretty text-based, like, honestly, pretty customer support-focused. That's where there's a lot of existing demand. And then over time, we've picked, some of the frontier companies in each of these other domains that we could work with and build out the standard, so, such that we know that the same standard works for code, it works for customer support, works for automation, et cetera. So that's been one big thing. Yeah, then some of the things that have been top of mind recently, Mythos is bringing up a lot of concerns for security leaders. We're starting to get more and more questions around agent interactions. It's very nascent, at the moment, but it's starting to emerge. There've been a lot of, questions related to OpenClaw and MCP. Again, like agents starting to interact with each other, is really top of mind. Then as coding agents have really taken off, that's also where banks and hospitals, et cetera, are getting more and more precise on what it is they need. So really dialing in as that start to be, like, where most of the tokens flow through in the world, getting much sharper on that.Vibhu [00:23:26]: Can you share for people that are listening that don't really think about this? Like you mentioned, there's the obvious stuff, you know, hallucination, citations. What are best practices that people should do when building agents? Like, if they come to you pretty ready with certification like, you know, they'll probably pass certification. What are the things people don't think about that they should have?Best Practices for Agent Builders: Stress Tests and GuardrailsRune Kvist [00:23:46]: The most important thing is that a lot of companies have not done a serious stress test. They spend most of the time, perhaps rightly so, optimizing for how does it work in the good case, the average case, how high-quality is the output for the customer. And a lot of these companies are pretty new, so they haven't spent a lot of time stress testing the what is there as an adversary on the other side? What are some of the complicated corner cases that you've not really considered? So I think that's, like, a frame of mind. And you'll also see this in startups. It often takes a while until they hire their first security person. They- And that's a whole different kind of risk surface than just building a good product. So a lot of that applies. Most companies actually also have the right kind of architecture. Most of them will have some kind of guardrails in place, either some that come out of the box from their model provider or they'll have built their own filters that sit in between. They just don't work very well. The difference between putting a classifier in place that, like, maybe goes and checks whether you're giving medical advice when you shouldn't and says, “Hey, if this looks like medical advice, filter it out.” Lots of companies have that in place. The question is whether it works. And it's actually pretty fiddly to sit down and think about all the ways in which you could ask for medical advice, read the academic literature on what are the kinds ofRune Kvist [00:25:03]: Framings or tricks you might play to get an AI to give you medical advice when you really shouldn't. And so there's, like, an area of expertise that's just missing. So what we find is that most people have the right building blocks in place. They don'- It doesn'- It's not rocket science, but the finicky thing is, like, getting into the corners and testing whether it works such that you can look your customers in the eye, or maybe a bank or maybe a hospital and be like, “This is going to work for you.”Vibhu [00:25:26]: I see. So we talked a lot about the agent-level certification. Where do you guys go from here? So announcing series A camera, we talked about this a bit. There's the whole security risk of Fable, government stepping in. You guys are kind of announcing that you're also going into model certification?Toward Model Certification: The Government–Lab Trust GapRune Kvist [00:25:46]: When we do a bit of cutting afterwards,Vibhu [00:25:48]: YeahRune Kvist [00:25:48]: We will not yet be announcing this,Vibhu [00:25:49]: NiceRune Kvist [00:25:50]: The question that is top of everyone's minds now is at the model level. And Mythos, then Fable, has really brought this to the fore that in addition to the commercial risk and the kind of economic security risks that are happening at the agent layer, the models are going to present risk in the national security category. The shape of the problem is very similar. You have some people that are on the hook if something goes wrong. In the case of agents, it's often security leaders in the enterprise. In this case, it's the government. They don'- haven't necessarily spent their entire lives thinking about what are the new risks that come here, what is the kind of data you might be looking for, how might you test that? But they do have to make sure that their concerns are addressed. You have some frontier AI companies that are deeply technical. They know a lot about the risks, but they fundamentally have an incentive to not always be truthful. So you have a trust gap between the government and the labs. And in every other industry, you end up with some kind of body sitting between, a neutral third party sitting between those people. There's no other industry where you allow people to audit themselves. So there is going to be a need for a third party that can take the rigor of the labs to run frontier technical evals, but can also speak legible trust in the way that the government trusts PwC to go and run financial audits. And they know that they output audit reports in a way that's consistent, that's easy to read, that's factual, that's, trustworthy. Those two things need to be brought together. And what we've learned from our work with agents is that if you want those-- that communication between those two parties to be smooth, there has to be one common standard that is public, that people can go and inspect. What are the risks that matter? Within each of these risks, what are the kinds of threat models that you're really looking for? You need to specify for each of those risks, what are the guardrails that need to be in place, and what are the tests they need to run to see whether those guardrails are effective? And then you need to go and run audits that are - technical audits that are consistent. So if you're trying to bring trust, it's extremely important that you methodically work your way through the risks. You can't send one researcher in and say, like, “Come back with whatever you find.” You need to be able to explain exactly what you did, exactly what you tried, exactly what you did not try, and therefore the kinds of promises you can and cannot make at the end of it. I think ofNeutral Third Parties, CAISI, and Model Risk AuditsRune Kvist [00:28:13]: Fable as a direct symptom of this problem that the government was told that there's a risk. The government may struggle to assess just how big that risk is. They call Anthropic, and Anthropic is trying to tell them, “Hey, actually, every model can be jailbroken.”Swyx [00:28:28]: That's not what you want to hear, right?Rune Kvist [00:28:32]: As the government, that might be hard to trust.Rune Kvist [00:28:36]: And we think that a broker is the most natural solution. In other markets, you see something like, in financial markets, you see Moody's. Moody's goes in, and they look at a bond, and they output a rating. They say like, “Here's the evidence we found. Here's the rating.” We don't decide whether anyone should buy this bond or not buy this bond. Well, that depends on their risk appetite. But we do provide this common information layer that everyone can rely on. In the case of Moody's, the government, points to them and say, “Hey, pension funds, you should probably really take care. You shouldn't risk your pensioners' money, so you can only invest in triple-A rated bonds.” That means that now the government doesn't have to staff thousands of financial technical experts to rerun forecasts every week to see whether things are correctly rated. They get to point to some neutral third party. So my hypothesis is, my hunch is that you will see a third party that sits between the government and the labs, and it could either be the government builds it themselves. So something like CAISI was set up to do exactly this. And the questionSwyx [00:29:44]: Sorry, I'm not familiar with CAISI.Rune Kvist [00:29:45]: CAISI is the Center for AI Standards and Innovation.Swyx [00:29:49]: Okay.Rune Kvist [00:29:50]: I won't get into the details, but it's a body of NIST that typically sets standards. So it's basically a government body that has AI experts. Yeah, exactly. Exactly.Swyx [00:29:59]: Very key. Very key.Rune Kvist [00:30:00]: Very key.Vibhu [00:30:00]: I think, you know, it's one of those things where when you just sit back and listen-- look at it, like, is there enough technical expertise in the government to measure, test these things right now? Probably not, right? And Fable is a result of, okay, we've had to scale back and pause things,Rune Kvist [00:30:17]: Yeah. And they have excellent people, but they have an extraordinarily small budget compared to the scale of the challenge that's ahead of us. And I think they have a role to play. The question is kind of like, who does what? We have now outlined the jobs to be done, and they're quite extensive. Every model release, there is an astounding-- Given that they take in any input, their risk surface is astounding. And so the question is really: what can only the government do, and what can the market provide here that can keep up with the pace as AI risk changes? Our perspective is that also at the model layer, the risks that people care about today are not the same ones they cared about three months ago. So the pace of legislation is too slow to deal with pinpointing the risks here. And so we think there's a lot that the market can do to surface timely information. Ultimately, there is a bunch of policy decisions here. Is the national security risks of a model too high?Swyx [00:31:12]: Yeah.Rune Kvist [00:31:12]: That's a political answer. But what we want to make sure is that the process that produces this risk information is compatible with very fast innovation. So you don't want to. This is not a question of like, can you slow the things down? Can you keep, the models locked up until-- for months on end until everyone can make a guarantee? But it is this, can you, in the time it. Given that the US is competing with China on releasing models, can you insert risk information that allows the government to, like, make rapid decisions on some of these questions? Balancing that trade-off between failing to adopt AI is going to put us at risk, but also reckless adoption is going to put us at risk. And that's a very kind of fine balance that they're going to need, like, a lot of high-quality intelligence to make.Chinese Models, Data Flows, and National Security ConcernsSwyx [00:31:55]: Just a side mention, because you mentioned Chinese models, any specific concerns that you're hearing from your CISOs about that? ‘cause I guess it's free, but.Rune Kvist [00:32:05]: CISOs have a bunch of concerns around data flows in general that they're really concerned about. So there's a lot of questions like, if these models are Chinese, where does that, where does that data go? I think a lot of this can be addressed, but they come up often.Swyx [00:32:18]: I mean, they understand they're running on American GPUs.Rune Kvist [00:32:21]: Some of them, some of them understand that they're running on American GPUs.Swyx [00:32:23]: They're not, like, phoning home every time you, like, call home.Rune Kvist [00:32:26]: No. A year ago, there was not a lot of understanding of this. I actually think, you're seeing the security leaders becoming kind of AI literate at a blistering pace, and you're actually also seeing my Twitter timeline that's very pilled and my LinkedIn feed that used to not at all be pilled kind of converge. They're both talking about Fable.Swyx [00:32:45]: Right. Yeah, that's true.Rune Kvist [00:32:46]: They are both talking about whether you can prevent models from being jailbroken these days.Swyx [00:32:51]: Yeah.Rune Kvist [00:32:52]: Like national security national security risks are now the conversation that is actually emerging. Other than that, I think you mostly see a kind of general picture: there are no concerns with any particular model or any particular model output, but there is a general nervousness of having critical infrastructure run on models that are not produced in America by Americans where the American government has control.Swyx [00:33:14]: But it doesn't necessarily show up in your framework that directly, or it might, I don't know.Rune Kvist [00:33:18]: There's a bit of stuff in there actually on the, like, the provenance of the models and disclosing that. But I think there's a bunch of use cases where running a Chinese open-source model is just the best solution.Swyx [00:33:27]: Yeah.Rune Kvist [00:33:27]: And a concern is slightly more macro here, which is not best addressed at any particular certification level.Vibhu [00:33:32]: Is there anything interesting that you see at the. You know, if you're trying to fill that middle gap, that mediation gap, any interesting stuff that you guys forecast would be required other than, you know, what the average person might expect?Cyber, Child Safety, Bio Risk, and Expert CoordinationRune Kvist [00:33:47]: There's a bunch of interesting questions about what are the risks that matter here. So right now, the risk of the day is cyber, because it's very real, very tangible. And some of the risks that are also emerging as pretty real and pretty tangible are things like child safety is becoming both extremely important, but also politically important. And then there are some of the risks that are coming down the pipeline that today feel kind of speculative, but people who spend a lot of time with the models see them coming down is things like, risks that relate to biology.Rune Kvist [00:34:18]: And specifically whether models will help adversaries produce biological weapons and making that extremely cheap, extremely accessible, producing-- making the chance of another COVID or worse pandemic. COVID was not engineered to be bad, as if you were trying to do that. So I think those are some of the risks that are coming down the pipeline. I think one other thing to just note is that agents are kind of deliberately narrow. So, like, when a frontier agent company puts a chatbot that interacts with customers, they've really tried to narrow the topics it's interested in talking about. Such that if you ask it, like, “What do you think of the president?” it will just decline, which means that the kind of risk area is somewhat smaller. For models, it is infinite. And so there's not a single expert out there who can competently evaluate the risks of cyberattacks and fifteen-year-olds having month-long conversations with a chatbot and seeing whether it will in fact recommend suicide or something horrendous like that, and can evaluate the risks that terrorists can use AI to produce bioweapons. The risk surface is just too big. And so the central challenge actually becomes how do you get those subject matter experts to work within a one coherent framework that outputs one coherent report and rating that the world can go and inspect? ‘Cause that global perspective is central, but there's not a single organization today that could produce that.Swyx [00:35:47]: And you would be the presumptive one when you put out your model standards.Rune Kvist [00:35:51]: We think there can be one company that can, with a consortium of experts, build one coherent standard. I think we've shown that across all of the enterprise risks today. We think it could be one company that could, with a consortium, specify the audit rules, basically like the inputs and outputs that all these technical experts need. What access do they need? How should they treat infosec- info security? They can look at whether the eval- evals are well-produced without necessarily being able to say, “Hey, is this a threat or not a threat?” But overall, evaluating whether the evals are good, well-constructed, that set of audit rules that basically becomes the interface for all these experts, we think one clearinghouse could put together. To be clear. When I say one company, I think of it as one company coordinating lots of this in the same way that when we saw our consortium, it's not like we say we have all the answers on agent security. What we say is we are taking on the role of eliciting all of the concerns and being the secretary that puts it together and runs a tight house such that the standard updates lockstep every quarter, and that the audit reports that come out, in this case, 100-page audit reports, uniform and crisp and clear all to the level of detail that is required for executives that need to make a clear go/go decision. So that's kind of the role that we think we might play.OWASP, Frameworks, and the Operational Audit LayerSwyx [00:37:11]: I think in many ways you're performing the role that OWASP used to do there, and you said, like, you know, competition and partners.Rune Kvist [00:37:18]: Yeah.Swyx [00:37:19]: Can you go more into, like, how they partner?Rune Kvist [00:37:20]: Yeah. So first of all, OWASP is basically an open source community of security practitioners that are coming together to build frameworks for addressing the latest security concerns. We think they are phenomenal at creating frameworks. We'- In fact, we'- First of all, we're partners with them, so we have a joint article. Two, we've learned a lot from them. We think they're a tremendous source of intelligence. What OWASP does not do is building the machine that runs third-party audits such that a company like Cursor or a company like JPMorgan could get a third party to go and review them against this and say, “Hey, you've passed the standard, and here is the report that you can use to build trust and preempt your partners' or customers' questions.” So they fundamentally try to do something different. You - They are part of the information gathering and intelligence gathering and creating clarity, but the operational layer of turning this into promises is not the business they try to be in.Swyx [00:38:14]: The standard is emerging and is doing very well. Was it necessary to then also do underwriting? Obviously it's in the name, so please remember you thought about it first. I feel like if you just have enough consensus, you don't actually need the money angle, but it does help.Vibhu [00:38:30]: I did want to also note, you guys are a profit company too, right? It's not profit where there's a whole business side to it as well?Why For-Profit Standards and Insurers MatterRune Kvist [00:38:39]: Yeah. Yeah, so I'm just getting crazySwyx [00:38:41]: I think about the money part.Rune Kvist [00:38:42]: Yeah. Yeah, let's get into the money part. Let's start from actually your question, profit versus profit. In the security space today, cybersecurity, most of the standards are produced by nonprofits. I think that's an issue.Rune Kvist [00:39:00]: The question you have to ask yourself is, how do you create good incentives for these standards to be good and keep up?Rune Kvist [00:39:09]: Nonprofits tend to not have these adverse profit incentives where they, hollow out their standard and create a race to the bottom, but they're also not at all responsive by default to the communities that they serve. There's no process-- They don't have customers that they serve where they go and ask, “What do you want? What do you want? What do you want?” And when you look at the overall satisfaction with the security standards today, people tend to just not like them very much. You do see in other domains, that profit standards can serve the world quite well. So there are examples, like we talked about Moody's before. It's not without flaws, but, it is absolutely critical societal infrastructure that gets run at an astounding scale today. Your credit score, it's FICO. It's also a profit business. And when you go back even further in history, some of the crash testing standards came out of insurance companies.Rune Kvist [00:40:06]: The insurance companies together founded the Insurance Institute for Highway Safety because they were very interested in, like, how can we use standards to drive down mortality and save money? Go back, prior-- Our name actually pays homage to the Underwriters Laboratories, UL, which, was started right around when electricity came out. Houses started burning down. Insurers, again, were paying the bill, and they were maybe also good people, but their profit incentive was, let's prevent houses from burning down. Let's test all the electrical products, the light bulbs. All the light bulbs in here are probably tested, the toasters, et cetera. And they set up, an entity to create those standards. Today, UL has a profit entity and a profit entity. What they've recognized, they spun - They started profit. They spun out a profit because what they recognized was like, hey, actually to serve customers well, you need a profit entity. The lesson here is one of the ways that the market can align incentives so you're both responsive to customersRune Kvist [00:41:07]: And not hollowing out your standard over time is to align it with insurers because they fundamentally have good incentives. And so if you're a profit standard that works closely with insurers, you get the feedback loop in such that you're really tuned into your customers, but also have their interest at heart. So that's the model that we - the kind of inspirational model that we've learned a lot from, and that's also where the name comes from. In some ways, the term underwriting can both be associated with insurance, but it's also a broad term for, like, making decisions.Rune Kvist [00:41:40]: If you underwrite a decision, you're fundamentally kind of taking ownership for the consequences of it.AI Insurance Contracts, Lloyd's of London, and ElevenLabsSwyx [00:41:45]: Yeah, I mean, what does an insurance contract look like for AI?Rune Kvist [00:41:49]: Yeah. Most of the demand comes today for insurance contracts is, sitting between people who've built AI and people who are buying AI.Swyx [00:41:56]: Yes.Rune Kvist [00:41:57]: And what you want—the reason why people want insurers involved, both for the traditional reasons, hey, if something goes wrong, we want to be compensated, but it's in particular because insurers can bring trust to the equation. Because insurers will pay for the damages, if they're willing to write an insurance policy, that is them saying, “Hey, we think there is risk here, but that is manageable.” And that is kind of a. Their incentive aligns with the enterprises adopting it, so that's a really a good signal to the market. In the same way, actually, one of the things that Waymo tried to get their first permit to even operate in San Francisco was to get a lot of insurers to stack up a huge insurance policy. In the case if something went wrong, not because Google can't pay, but because it was very valuable to have a third party go and look at that dataRune Kvist [00:42:47]: That are trusted by governments, trusted by enterprises as conservative people and say, “Hey, we've looked at it. We're actually willing to take some of this on our balance sheet.” So that's, that's kind of the reason why people are interested in it. What it looks like is, in some ways like every other insurance contract. You specify what are the perils you want to cover, how much do you want to cover them, like up to what limits, and what does it cost to cover that. And in the case of, if we take a really concrete example, ElevenLabs, bought a first of its kind AI agent insurance policy. They work with some of the biggest, enterprises that work with governments. They're really interested in going above and beyond and making promises to their customers. So they wrote a policy that covers just some of the core concerns that their customers have been asking about. And, the crucial thing was really to get Lloyd's of London, the world's oldest insurer, one of our partners, to look at this data and be that third party alongside us to say, “Hey, we think there's something here that's worth underwriting.” and that's actually what it looks like. And so they will show that contract to their customers, and they can see how much they're covered for. They can see what exactly it covers, and that will also probably change next year. They will want to write an insurance policy that might cover more.Swyx [00:44:04]: When you say Lloyd's, is it reinsurance, or are they sharing somehow at the same level orRune Kvist [00:44:11]: Yeah. So typically, the way, new companies get into insurance is that they partner with insurers such that the insurers take the majority or all of the financial risks. Fundamentally, if insurance is useful, because it brings trust, you have to be able to pay the bill. Lloyd's of London is 400 years old. They've never not paid a claim. They're extremely trusted. What Lloyd's of London struggle to do on their own is to figure out which of the risks are real, what should we be looking for, what are the kinds of technical controls, and running the tests. So they use AIUC-1 as kind of the underwriting framework, and we produce a bunch of eval results that then directly feed in to inform the pricing. So this means that ElevenLabs customers know that payment will be there. They don't have to look to our series A and see, like, do we think they have enough cash on the balance sheet? They will look at Lloyd's.Swyx [00:45:05]: Yeah.Rune Kvist [00:45:05]: Yeah.Swyx [00:45:05]: And Lloyd's, like, famously very creative. I think I remember some headline like, they insured Jennifer Lopez's, butt or something.Rune Kvist [00:45:13]: Correct.Swyx [00:45:13]: Right?Rune Kvist [00:45:13]: And I think, was it, David Beckham's right foot?Swyx [00:45:16]: So, yeah. Right?Rune Kvist [00:45:17]: And stuff like this.Swyx [00:45:18]: So, like, clearly not a large data set.Rune Kvist [00:45:22]: Exactly. It's actually a remarkable institution that's both kind of has some of the truly school virtues of having been around for a long time. They, like, really. They really operate like a trusted entity, and they have appetite to figure out the future. And I think there's a lot of recognition that both there is, like, tremendous amount of risk in AI that is poorly understood today, so getting into this business carries real risks. But also this is where lots of the risk exposure will happen in the future. This is the one market where risk is truly growing. This is the one market that will also take out some of the existing markets. Take, like, auto insurance. When there are no human drivers, how's that market going to look? Well, it's clearly going to change. How are you going to assessSwyx [00:46:08]: You want to insure Waymo?Rune Kvist [00:46:10]: I. All I'll say is the principles for how you insure Waymo are very similar to how you insure other kinds of AI.Swyx [00:46:15]: Right.Rune Kvist [00:46:15]: So again, crash testing, that's what we do for customer share at Lovable. That will also need to happen for Waymo, which is not how you do it for human drivers. So there's this growing awareness that the world is changing very fast, and the only way to learn how to underwrite AI is to write some policies. You may incur some losses and think of that as R&D expense, really. But the question for them is, like, who are the trustedtechnical partners they can get into this business with that can help them navigate and make sure they don't make, kind of foolish mistakes? But also who is willing to hear the wisdom that they have? They've done this before. They've seen it was. They were there when cyber came out. So there are lots of ways in which AI feels completely new, but there's also lots of ways in which risks look the same. And so there's actually a tremendous amount of wisdom sitting in some folks that may have gray hair, but really have, like, a keen sense of, how to quantify risk.Swyx [00:47:08]: Yeah. And the number is. So it's basically like I want fifty million dollars worth of coverage against these perils, and Lloyd's will give you a quote on it, and then you have, like, a small markup or something, and then you turn it around and do that? Is that as simple as it is?Risk Capital, Premiums, and Working with InsurersRune Kvist [00:47:23]: You basically share some of that premium.Swyx [00:47:25]: Yeah.Rune Kvist [00:47:25]: X percent goes to the people who do the pricing of it.Swyx [00:47:28]: You're. It's kind of like a. It's kind of like a merchant bank for insurance type of thing.Rune Kvist [00:47:33]: Exactly. You basically split the fee, and you can think of the insurance supply chain as, like, there's bringing the capital, there is doing the pricing, and there is doing the distribution. And typically, you will pay out some X percent of premium here, Y percent of premium here, and the rest of it will go here.Swyx [00:47:46]: Does all the insurance world work like this, or is there some point at which, like. So if right now you have equity capitalRune Kvist [00:47:51]: Yeah.Swyx [00:47:52]: At some point, maybe you start raising, debt or whatever, and then you have enough of a bank account and enough history, let's say you've been in operation for ten yearsRune Kvist [00:48:00]: Correct.Swyx [00:48:00]: That you don't need Lloyd's anymore?Rune Kvist [00:48:02]: That's totally an option. And I could see some worlds where that makes sense, specifically if there are risks that we feel high confidence that we'd want to insure where the incumbent insurers are too slow to find appetiteSwyx [00:48:13]: Okay.Rune Kvist [00:48:13]: Or simply struggle to evaluate it such that they don't want to do it. But by and large, in general, you do not want to compete with insurers on, bringing risk capital to the game for two reasons. One is that's fundamentally a cost of capital game. They have extremely low cost of capital. Startups have high cost of capital, by and large. And two, you want to hedge your bets, and it's very helpful then to also have a portfolio of home insurance, of car insurance. And we're not about to become a car insurer nor a home insurer.Rune Kvist [00:48:43]: So they have some natural advantages, which makes it much more likely that we'll partner.Swyx [00:48:48]: Yeah.Rune Kvist [00:48:48]: And they bring that, the capital at scale, and we bring the technical expertise.Swyx [00:48:51]: You're, you're going to work with them for a long time.Vibhu [00:48:52]: How are the discussions with the insurers as well? So basically, they're going off of your certification, right? They're trusting the diligence on you that your certification is valid, you tested the right things, and they're backing the money that, you know, you have the right testing in place. So any interesting takeaways from working with insurers?Rune Kvist [00:49:12]: I think the maybe the first thing is they feed into the standard as well. So if there are things that they feel like they need that they're not seeing, we are also taking that as input into the standard, because fundamentally we think a good standard is one that creates a really healthy promise ecosystem, and we think insurers are a critical part of that. And again, they are the most well-incentivized to. They see all the lost data across every. Any particular CISO knows their particular concerns. Insurers see the concerns across the entire portfolio and often have direct access to, like, what exactly happened, who was at fault, et cetera, as they do part of their forensics. So they're actually, like, a great source of intelligence on this. One of the big takeaways from cyber insurance, which is a market that didn't work that well, was that the insurance and the technical expertise was not married up. What our conviction is that standards have to precede insurance. Fundamentally, what everyone first and foremost want, whether you're a CISO at JPMorgan or a CISO at Cursor or an underwriter at Lloyd's of London syndicate, is you want to not have an incidentRune Kvist [00:50:19]: In the first place. You want to know that the risk is well-managed, and only then does insurance start to make sense. So we'll see the standard ecosystem basically run ahead of the insurance. And the reason why we. You asked us kind of why I also do insurance, this is kind of proving what we think a whole promise confidence infrastructure ecosystem needs to look like, and we think it's very compelling to bring that to life, even if we think the standard is kind of the core linchpin that unlocks the rest.Claims, Liability, Air Canada, and Duty of CareSwyx [00:50:44]: There's been no claims yet, right?Rune Kvist [00:50:45]: Nope.Swyx [00:50:46]: This is one of those things where, you know, if people haven't really worked through what it means to cover things.Rune Kvist [00:50:52]: Yeah.Swyx [00:50:52]: So for example, I pay Cursor $20 a month.Rune Kvist [00:50:55]: Yep.Swyx [00:50:56]: And I write a vibe code something that makes, a plane crash, causing $200 million worth of damage.Rune Kvist [00:51:02]: Yes.Swyx [00:51:02]:

How can leaders handle conflict more effectively, give feedback that actually helps people grow, and build stronger trust with their teams? In this episode of the Live Greatly podcast, Kristel Bauer sits down with Caroline Webb, leadership coach, economist, former McKinsey partner, and author of Leadership Intelligence: Science-Backed Strategies for Mastering 21 Everyday Management Challenges. Caroline shares science-backed strategies for navigating some of the most common—and challenging—situations leaders face. She introduces her Common Ground Model for working through disagreements, shares tips for giving and receiving feedback more effectively, and explains why simply telling people what to do often isn't the best way to help them learn and develop. Kristel and Caroline also discuss what it takes to build trust, strengthen relationships, and become more effective at handling the everyday challenges of leadership. Tune in to learn: How to approach conflict and find common ground during disagreements Tips for giving and receiving feedback more effectively Why telling people what to do can get in the way of development How to better support people in learning and growing Strategies for building trust within your team Science-backed insights from Leadership Intelligence that can help you become a more effective leader Whether you're leading a team, managing others, or looking to strengthen your own leadership skills, this conversation offers actionable strategies to help you lead more effectively through the challenges that come with working with and leading others. ABOUT CAROLINE WEBB: Caroline is a leadership coach, economist, and author of How to Have a Good Day and the forthcoming Leadership Intelligence. She has been named one of the top fifty executive coaches in the world by Thinkers50, and one of the top fifty leadership and management thinkers by Inc. magazine. She is a senior advisor to McKinsey & Company, where she was previously a partner. Her work has been featured in The Wall Street Journal, The New York Times, Harvard Business Review, Financial Times, The Economist, The Guardian, and Fortune. She lives in New York. Connect with Caroline Webb:  Order her book LEADERSHIP INTELLIGENCE: Science-Backed Strategies for Mastering 21 Everyday Management Challenges:  Website: https://carolinewebb.co/  SOCIAL MEDIA • LinkedIn      • Instagram About the Host of the Live Greatly podcast, Kristel Bauer: Kristel Bauer is a corporate wellness and performance expert, keynote speaker and TEDx speaker supporting organizations and individuals on their journeys for more happiness and success. She is the award-winning author of Work-Life Tango: Finding Happiness, Harmony, and Peak Performance Wherever You Work (John Murray Business November 19, 2024). With Kristel's healthcare background, she provides data driven actionable strategies to leverage happiness and high-power habits to drive growth mindsets, peak performance, profitability, well-being and a culture of excellence. Kristel's keynotes provide insights to "Live Greatly" while promoting leadership development and team building. Kristel is the creator and host of her global top self-improvement podcast, Live Greatly. She is a contributing writer for Entrepreneur, and she is an influencer in the business and wellness space having been recognized as a Top 10 Social Media Influencer of 2021 in Forbes. As an Integrative Medicine Fellow & Physician Assistant having practiced clinically in Integrative Psychiatry, Kristel has a unique perspective into attaining a mindset for more happiness and success. Kristel has presented to groups from the American Gas Association, Bank of America, bp, Commercial Metals Company, General Mills, Northwestern University, Santander Bank and many more. Kristel's work has been featured in Forbes and she has had multiple TV appearances including NBC News Daily, ABC News Live, FOX Weather, ABC 7 Chicago, WGN Daytime Chicago and more. Kristel lives in the Chicago, IL area and she can be booked for speaking engagements worldwide. To Book Kristel as a speaker for your next event, click here. Website: www.livegreatly.co  Follow Kristel Bauer on: Instagram: @livegreatly_co  LinkedIn: Kristel Bauer Twitter: @livegreatly_co Facebook: @livegreatly.co Youtube: Live Greatly, Kristel Bauer To Watch Kristel Bauer's TEDx talk of Redefining Work/Life Balance in a COVID-19 World click here. Click HERE to check out Kristel's corporate wellness and leadership blog Click HERE to check out Kristel's Travel and Wellness Blog Disclaimer: The contents of this podcast are intended for informational and educational purposes only. Always seek the guidance of your physician for any recommendations specific to you or for any questions regarding your specific health, your sleep patterns changes to diet and exercise, or any medical conditions.  Always consult your physician before starting any supplements or new lifestyle programs. All information, views and statements shared on the Live Greatly podcast are purely the opinions of the authors, and are not medical advice or treatment recommendations.  They have not been evaluated by the food and drug administration.  Opinions of guests are their own and Kristel Bauer & this podcast does not endorse or accept responsibility for statements made by guests.  Neither Kristel Bauer nor this podcast takes responsibility for possible health consequences of a person or persons following the information in this educational content.  Always consult your physician for recommendations specific to you.

Episode 83 - Penny Dash, Chair of NHS England, is a physician and healthcare leader focused on improving quality, safety and efficiency. A former NHS and DHSC strategy leader and McKinsey partner, she advises health systems globally.Disclaimer: Please note that all information and content on the UK Health Radio Network, all its radio broadcasts and podcasts are provided by the authors, producers, presenters and companies themselves and is only intended as additional information to your general knowledge. As a service to our listeners/readers our programs/content are for general information and entertainment only.  The UK Health Radio Network does not recommend, endorse, or object to the views, products or topics expressed or discussed by show hosts or their guests, authors and interviewees.  We suggest you always consult with your own professional – personal, medical, financial or legal advisor. So please do not delay or disregard any professional – personal, medical, financial or legal advice received due to something you have heard or read on the UK Health Radio Network.

For years, wealth management firms have looked for ways to unlock wealth management growth, become more valuable to their clients, and differentiate themselves beyond traditional investment management. Financial planning, estate planning, insurance, and other services have become increasingly important pieces of the client relationship. But one area continues to stand out as both a major opportunity for financial advisor tax planning and a major operational challenge for advisory firms: tax. Many advisors understand the value of financial advisor tax planning. The problem is execution. Building an in-house tax practice can require finding and retaining talent, integrating outdated technology, managing a seasonal workload, and creating systems that connect tax professionals with the broader wealth management team.   In this episode of The Model FA Podcast, David DeCelle sits down with Raj Doshi, President and COO of April, to discuss how embedded tax technology is changing the way financial advisors and wealth management firms serve their clients. Raj explains why tax returns represent one of the most comprehensive sources of financial information available, and how firms can leverage embedded tax technology to uncover opportunities, deepen client relationships, and drive tax-driven client acquisition. David and Raj also explore the growing demand for family office-style services, why clients increasingly expect their financial professionals to work together, and how technology can help advisors offer tax services without necessarily building a traditional tax department from scratch.   The conversation also covers Raj's career journey through McKinsey, Google, growth-stage companies, TaxAct, Avantax, and eventually April. Drawing from his experience participating in multiple business exits, Raj shares an important lesson for entrepreneurs and firm owners: the best way to prepare a business for an eventual exit is to stay focused on building a great business.   In This Episode, You'll Learn: • Why embedded tax technology is becoming a major competitive advantage for wealth management growth • How the tax return can provide one of the most comprehensive views into a client's financial life • Why advisors are increasingly looking to financial advisor tax planning to create alpha outside of portfolio management • How tax services can help advisors uncover held-away assets and new planning opportunities • Why clients often think about investments, taxes, insurance, and estate planning as part of one financial relationship • How April helps firms offer tax filing, tax planning, and tax data insights • Why advisors do not necessarily need to build or acquire a tax practice to offer tax services • How a three-way collaboration between the client, advisor, and tax professional can create a more connected experience • Why legacy tax software and disconnected systems can create major operational bottlenecks • How automation and AI can help tax professionals operate more efficiently • Why tax season creates a natural opportunity for advisors to engage clients and identify changes in their financial lives • How tax-driven client acquisition strategies improve prospect conversion, onboarding, and asset gathering • Why outsourcing tax work does not have to mean losing visibility into the client relationship • Raj's biggest lessons from participating in multiple business exits • Why entrepreneurs should keep operating and growing the business through the finish line, even during a sale process   Raj also shares how his career has evolved across consulting, technology, financial services, and entrepreneurship. After starting at McKinsey and later working at Google, Raj developed experience in corporate finance, wealth management, growth strategy, and building businesses. His time at Blucora, which owned both TaxAct and Avantax, gave him firsthand experience with embedded tax technology and financial advisor tax planning, ultimately shaping his path to April.   If you're a financial advisor or wealth management firm exploring how tax-driven client acquisition fits into your long-term wealth management growth strategy, this conversation offers a practical look at the opportunities and operational challenges involved. Whether you're considering tax filing, tax planning, better use of client data, or an embedded tax technology service model, Raj provides a useful framework for thinking about where the industry is headed.   Connect with Raj Doshi and April Connect with Raj Doshi: https://www.linkedin.com/in/rajrdoshi  Learn more about April: https://www.getapril.com/ Connect with April on LinkedIn: https://www.linkedin.com/company/getapril/   About the Model FA Podcast The Model FA podcast is a show for fiduciary financial advisors. In each episode, our host David DeCelle sits down with industry experts, strategic thinkers, and advisors to explore what it takes  to build a successful practice — and have an abundant life in the process. We believe in continuous learning, tactical advice, and strategies that work — no "gotchas" or BS. Join us to hear stories from successful financial advisors, get actionable ideas from experts, and re-discover your drive to build the practice of your dreams.    Did you like this conversation? Then leave us a rating and a review in whatever podcast player you use. We would love your feedback, and your ratings help us reach more advisors with ideas for growing their practices, attracting great clients, and achieving a better quality of life. While you are there, feel free to share your ideas about future podcast guests or topics you'd love to see covered.    Our Team: President of Model FA, David DeCelle   If you like this podcast, you will love our community! Join the Model FA Community on Facebook to connect with like-minded advisors and share the day-to-day challenges and wins of running a growing financial services firm.

SmarterX founder and CEO Paul Roetzer joins the boys for a chat about how AI is reshaping the workforce in ways most don't suspect. Paul sold his marketing agency in 2021 as AI was already writing at near-human level—then ChatGPT showed up and things went into hyperdrive. Bentley and Gallup's 2026 numbers say most Americans, especially young ones, don't trust companies that use AI, while Microsoft, Google, and every CRM already do. Paul talks human-centered adoption, Jobs GPT, Copilot/Gemini/Claude stall-outs, why IT shouldn't own this, and what IBM, Deloitte, and McKinsey actually sell. He walks through his Co-CEO GPT, a nine-month Anthropic/Claude build, HubSpot Breeze, Monday data agents, “human in the loop” versus a phrase he coins live, the 100-person split that becomes an HR problem, recruiting through a flood of AI applications, liberal-arts hires, and what he tells parents when asked about AI and entry level jobs.

My guest today is Michael Stich, partner at CourtAvenue. Michael has spent more than 25 years helping some of the world's biggest brands navigate innovation, digital transformation, customer experience, AI, commerce, and just about every major shift marketing has faced over the last two decades. Today at CourtAvenue, he works with organizations including Kia, Epson, General Mills, Dell, and the US Air Force to solve complex business and marketing challenges. Before that, he held leadership roles at WPP, VML, Rockfish, Bridge Worldwide, Texas Instruments, McKinsey, and Dell, giving him a front-row seat to the evolution of modern marketing. And along the way, he's advised Fortune 50 companies, invested in startups, helped launch groundbreaking products, and built businesses that have transformed how brands connect with customers. He's also been recognized as a Cincinnati marketing legend by the AMA and has earned multiple industry honors for his leadership.

Don’t get left behind in the AI revolution. Subscribe to our Newsletter: https://theultimatepartner.com/ebook-subscribe/ Check Out UPX: https://theultimatepartner.com/experience/ In this powerful episode, Vince Menzione sits down with Rebecca Jones of Bridge Partners and Mark Yaphe, Head of Consulting Partners for AWS, to uncover how AI is fundamentally rewiring the partner ecosystem. They explore the urgent shift from 90% stalled AI pilots to a new era of rapid execution, warning against the trap of “shiny object” syndrome. By unpacking the necessity of a “builder mindset” and a product-focused approach, this discussion reveals exactly what top-performing companies are doing to collapse six-month development cycles into four weeks and secure their place in the 2026 market landscape. Key Takeaways The transition from on-prem to cloud and marketplace is now entirely focused on AI transformation. Top companies approach AI with a product mindset rather than running scattershot pilots. Empowering frontline teams with a “builder mindset” can collapse solution cycles from six months to four weeks. Partners must avoid the $260 billion AI “FOMO” trap by specializing in specific industries and workflows rather than trying to do everything. Evaluating the “highest and best use” of AI models like Claude is essential for managing token economics and ROI. Thriving through AI disruption requires cultivating a strong growth mindset and prioritizing human connection and critical thinking. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags AI transformation, AWS partner ecosystem, hyperscaler alignment, builder mindset, product mindset implementation, Bridge Partners insights, GenAI solution cycles, AI token economics, Claude model utilization, GSI strategy, 2026 ecosystem shift, AI ROI measurement, agentic tools, workflow specialization. Transcript Rebecca Jones and Mark Yaphe AUDIO EPISODE [00:00:00] Rebecca Jones: You can either, um, think about being disrupted or being a disruptor. [00:00:07] Vince Menzione: You can feel it happening. The ecosystem is shifting beneath us the way hyperscalers are partnering, how AI is remaking the channel. And what it means to win in 2026. [00:00:18] Vince Menzione: Welcome to the Ultimate Partner Podcast. I’m Vince Menzi, own your host. [00:00:23] Vince Menzione: And each week I sit down with leaders at the intersection of [00:00:26] Vince Menzione: technology, partnerships and outcomes, the voices shaping how ecosystems actually work. We talk about what’s real, what’s changing, and what it takes to lead in this era where the partner channel isn’t just part of the strategy. It is the strategy because being in the room changes everything. [00:00:45] Vince Menzione: Let’s start. We have another incredible session today, right? So I get to invite another friend of, of ultimate partner who’s been around for a while and, uh, it’s just absolutely amazing. Rebecca has been in the studio, she’s been at, how many of events have you been with? Fourth, fourth one, and I’m gonna have you introduce Mark as well. [00:01:10] Vince Menzione: So come on, on stage. Rebecca. Rebecca Jones to many of you know. [00:01:14] Rebecca Jones: Thank you, sir. [00:01:15] Vince Menzione: Good to see you. Good to see you. And Mark, great, great to have you. I want to have you, Richard, we’ll have you, Rebecca’s gonna introduce you and then we want you to introduce yourself as well, sir. [00:01:23] Rebecca Jones: Wonderful. Well, [00:01:24] Vince Menzione: and another AWS exec. [00:01:26] Vince Menzione: I love this. Like, I know. Yeah, we’re finishing out the day Strong. [00:01:28] Rebecca Jones: Well, Vince, I have to say, you’ve got me, um, the last time we got together, it was the last session before happy hour. So I guess we’re closing. [00:01:36] Vince Menzione: Well, you know, we’re gonna close us [00:01:38] Rebecca Jones: out [00:01:38] Vince Menzione: really nicely. Know we, yeah. We’re serving Bloody Mary’s, by the way, while you’re guys are up here. [00:01:42] Vince Menzione: No. Good. [00:01:42] Rebecca Jones: So, um, we’re so excited to have Mark. Thank you, mark, for joining us here. Um, head of consulting partners for AWS and, uh. We’re gonna close this down, aren’t we? I love [00:01:54] Vince Menzione: it. I love it. Yes. I’m looking forward to it. [00:01:56] Rebecca Jones: Okay. [00:01:56] Vince Menzione: So Mark’s well, welcome. Good to have you. [00:01:58] Rebecca Jones: Yeah. Do you wanna take a seat? [00:02:00] Vince Menzione: Uh, yeah, [00:02:00] Rebecca Jones: please do. [00:02:01] Rebecca Jones: All right. [00:02:01] Vince Menzione: Please do. I’m morphing the pillows up, by the way. [00:02:05] Rebecca Jones: Oh, are you [00:02:05] Vince Menzione: by the way, for those of who don’t know, these got shipped from my house because we got Oh, I was wondering. It’s hard to find, but yeah. Yeah, they’re, we take them from event to event. It’s so funny to have them. But I wanna, well, thank you for both being here. [00:02:17] Rebecca Jones: Yes. [00:02:18] Vince Menzione: I think it’d probably be helpful for those who don’t know, bridge Of course. Maybe just spend a moment because I know you well. [00:02:23] Rebecca Jones: Yeah. [00:02:23] Vince Menzione: And we know the organization well, those of us. Those of us. [00:02:26] Rebecca Jones: But for me, uh, so let me talk to you a little bit about Bridge Partners and my role, um, the company has been around for almost two decades. [00:02:34] Rebecca Jones: Yeah. And so when you think about the transformation that’s happened within the tech industry. And our primary focus is the tech industry. Uh, and within that we focus on enterprise companies and we help them with product go to market and how they scale that through partners. Yeah. Uh, so that’s given us a really interesting and, uh, vantage point around the transformations from on-prem to cloud, cloud to marketplace and now marketplace and the transformation with ai. [00:03:04] Vince Menzione: I feel like you’re the McKenzie of the, of the partner business. Like I, [00:03:07] Rebecca Jones: I like that. [00:03:08] Vince Menzione: Can we get that? [00:03:09] Rebecca Jones: Yeah. [00:03:10] Vince Menzione: I’ll, I’ll, I’ll sign an agreement with you, but I really do, I feel like as we work together, bridge was always like the organization we bring in to help us. Solve the big issues. Yeah. Like that I think about your organization. [00:03:20] Vince Menzione: Yeah. And Mark, talk to me about Global Consulting services. Sure. So is it all GSIs? Is it, [00:03:24] Mark Yaphe: uh, so I head up, uh, global Consulting Partner Marketing. Okay. So I focus really on, on two key categories for the, the more sig larger, uh, GSIs. Uh, I’ve got a team that actually partners very closely with them. Nice. [00:03:36] Mark Yaphe: That helps them develop the right strategies, go to market approaches, nice to unlock the opportunity. And then for the full consulting community, I look at those mechanisms. Go to market approach is leveraging marketplace to help our whole consulting community become successful with AWS. [00:03:51] Vince Menzione: And we’ve got GSIs in the room here, which is kind of cool actually. [00:03:53] Vince Menzione: Yeah. Um, where do we wanna start? Let’s, let’s, [00:03:57] Rebecca Jones: well, yeah, we’ve got a good list of questions to go through. How’s everybody feeling? We’re we’re good? We’re awake. One more session, everyone. Alright. Okay. [00:04:09] Vince Menzione: So Rebecca, uh, across the organizations you work with. What are you seeing from the highest ’cause? I, I say you’re like the McKinsey. [00:04:16] Vince Menzione: What are you seeing from the highest performing companies? Yeah, that they do differently. When it comes to turning your go-to market strategy into outcomes? [00:04:23] Rebecca Jones: Yeah. Um, I will say the most important thing that we’re seeing from companies is they’re asking different questions, fundamentally different questions when it comes to ai. [00:04:34] Rebecca Jones: Interesting. [00:04:34] Vince Menzione: What do you mean by that? [00:04:35] Rebecca Jones: Well, we, we talked a lot this morning about there’s never been higher access, and I’ll say general adoption for tools and technology. There was a great stat this morning. Uh, I think Jay shared that, uh, from MIT. [00:04:50] Vince Menzione: We keep looking there as if he’s still [00:04:51] Rebecca Jones: sitting there. [00:04:51] Rebecca Jones: Yeah, I’m looking. Where was Jay? He, he was all over the place. Um, there was a great stat from MIT that there was, you know, if you looked at last year, 90% of pilots. Were stuck and they weren’t going anywhere. And now that’s dropped down to 70%. So there’s movement and transformation. And so when I think about that, and when I go back to the types of questions leaders are asking, um, that are really moving ahead, they’re looking at operating systems differently and they’re looking at, um. [00:05:25] Rebecca Jones: They’re asking the questions on where should I apply AI within those work streams, um, and within those operating systems, and the way in which they’re approaching that is with a product mindset. So that is fundamentally different than just the scattershot of let’s just do pilots everywhere. [00:05:44] Vince Menzione: Yeah. You’ve talked about product, uh, mindset with me as well. [00:05:48] Rebecca Jones: Yeah. [00:05:48] Vince Menzione: And I think we were gonna talk about builder mindset as well, mark, that that is a kind of a different point of view. When you think about moving from strategy to execution, how does that mindset show up inside teams and organizations? [00:06:00] Mark Yaphe: No, absolutely. Yeah. You know, the notion of the builder mindset is about, uh, taking the notion of innovation and pushing it out to the edge. [00:06:07] Mark Yaphe: Of the organization, um, the greatest ideas for innovation, the greatest things that will help you scale. They’re in the minds of your customers and the people that can best understand them and best address ’em. They’re your teams. Yeah. Your, your customer teams or your technical teams, but unlocking it. You, you want these teams to do more than just have the conversations and understand needs. [00:06:28] Mark Yaphe: You want them to be tooled and equipped to build. Yeah. So the ones that are right in front of the customers. In that moment of need where they say, I’ve got these offerings and these motions, and it gets me this far, but if I could only do a little bit more, I could delight them. I could really power this up. [00:06:45] Mark Yaphe: And so you wanna unlock that. You want to give them the tools to build, to build the POC to address specific, uh, options in the meeting. And then when they’re showing some success, show the rest of the organization how they can scale that. [00:06:58] Vince Menzione: How do you think about, because I think about big GSIs. Having huge organizations like Accenture has half a million people, and then you have customer teams that may not, are, may not be as fluent in the technology side of things. [00:07:13] Vince Menzione: Like how do you make sure that’s getting from the customer all the way to the right people in the organization and driving that loaded question. I know. [00:07:20] Mark Yaphe: No, I, I, um, you, you, you want to think about how that process works. Yeah. And there are parts of the organization. That define how do we get go to market offers in motions out to the field. [00:07:34] Mark Yaphe: Um, and they look at the whole thing and they say, well, how effective are we and how quickly can we cycle through? Yes. These activities. There’s one partner I worked with, um, they looked at this and they measure the cycle time. How long does it take me to get from pushing on an offer? Working with customers, getting feedback, and then creating new updates. [00:07:53] Mark Yaphe: A long, long time ago, like two years ago, this would take, it was a hundred [00:07:57] Vince Menzione: years ago in AI terms. [00:07:59] Mark Yaphe: Well, that’s basically it. This took about five to six months. They get about two revs a year. Now. They literally implemented a geni solution that number one uses geni to push it out to the teams, makes it bespoke on an engagement by engagement basis. [00:08:14] Mark Yaphe: It makes it relevant for their industries and their use cases. And that same tool is the feedback mechanism. So in real time it’s providing feedback. So they’ve collapsed six month cycle times to four weeks. And the punchline here is we talked about builder teams. The people that figured out they needed the solution, built the solution, and piloted the solutions were the builder teams. [00:08:36] Mark Yaphe: They were the people working with the customers. [00:08:38] Vince Menzione: I love it. Yeah, I love it. Anything to add to that? Rebecca, I know you work again, being the McKinsey of the, of the partner world. [00:08:46] Rebecca Jones: Well, I’ll, I [00:08:47] Mark Yaphe: It’s gonna stick, [00:08:47] Rebecca Jones: stick. It’s [00:08:48] Vince Menzione: gonna [00:08:49] Rebecca Jones: stick. You say it three times, that’s stick. No, I, you know, mark just hit on some really important things with the customer mind. [00:08:57] Rebecca Jones: You’re really looking at what outcomes are you trying to drive for those customers and that builder mindset, you, you’re going to hear a lot about that because companies need, as you transform, you really need to be thinking differently. And transformation takes quite a while. And while there is massive opportunity and you see the, the quickness you have to have that long-term vision and then be able to work backwards from that. [00:09:21] Rebecca Jones: And so I couldn’t agree more with the, the focus on customer outcomes. [00:09:26] Vince Menzione: So we’re in a very interesting, I’ll call it, almost a seminal point, although that’s overused in terms of where we are with AI today, right? I you mentioned like two years, feels like 10 years. Yeah. Ago, right? I mean, we’ve seen such transformation happening, but it also doesn’t feel like organizations are keeping, like, I, I feel like small SMBs actually are further ahead because they, they have to be agile, but the bigger organizations are still trying to figure some things out, right? [00:09:53] Vince Menzione: So. What needs to change around organizations, culture management processes? Like how do we bring, how do we bring everyone along on this journey? [00:10:04] Mark Yaphe: There’s a lot that needs to happen. Um, [00:10:07] Vince Menzione: yeah. [00:10:08] Mark Yaphe: One thing that struck, there’s a lot of things I, I wanted to anchor on. One that Yeah, please. It could be a relevant conversation. [00:10:13] Mark Yaphe: Both, um, as part of your, uh, partner organizations delivering outcomes to customers. And, um, it’s about focusing on the business outcomes. It can be very easy, uh, to talk about the technology and the services, but day to day, the sales organization is going into solve customer problems. They’re meeting line of business leaders in specific industries who have very specific business problems to tackle. [00:10:42] Mark Yaphe: And I think one thing that organizations can do is impress upon them that it’s critical to understand. What are the business problems that we solve for our customers that we’re serving? What are those use cases? What are the drivers for it? In the role that I’m doing in an organization, how does that move the needle? [00:10:58] Guest: Yeah. [00:10:58] Mark Yaphe: For the business outcomes, it’s, it’s not dissimilar to other things, and perhaps it’s a little bit of a pivot, but always thinking about business outcomes, I think is, um, a little bit of a change that needs to be instilled within [00:11:10] Vince Menzione: what, what are the best doing better, and where are you seeing the gaps? [00:11:16] Mark Yaphe: Couple of areas, uh, one area, um, nobody knows everything. Yeah. Nobody’s got all the knowledge. [00:11:23] Vince Menzione: Right. [00:11:23] Mark Yaphe: And so rely on your ecosystem of partners and stakeholders. Yeah. Recognize you’ll only have so much information, um, and reach out, whether it’s to your technology partners, your business partners, your hyperscalers AWS to find out what am I missing. [00:11:38] Guest: Yeah. [00:11:38] Mark Yaphe: Um, again, many years, you know, a hundred years ago, two years, two years ago, um. We’d have these conversations about, well, what use cases are you seeing and what business problems are you solving? But, but those would be in scheduled meetings quarterly. Now there are agenda items on weekly standards. [00:11:55] Mark Yaphe: They’re happening every single week. What are you seeing? What are you seeing? And further, I’ve seen some gen AI and agent solutions that actually automate how that information flows to, to make it, to accelerate. [00:12:06] Vince Menzione: Yeah, it’s, it’s absolutely amazing. Yeah. Anything on, I mean, certainly you’ve got a perspective ’cause you’re working with these organizations. [00:12:13] Rebecca Jones: I have a couple thoughts on this specifically for the partner organizations and the partner companies here. I can understand there’s a lot of, you know, we looked at a stat earlier about the AI partner opportunity and it was. $260 billion somewhere in that bracket. And that can create maybe some fomo, you know, maybe, uh, let’s go after everything in this area. [00:12:37] Rebecca Jones: Yes. And not pick and choose [00:12:39] Mark Yaphe: a [00:12:39] Rebecca Jones: shiny object. Shiny object and not prioritize. And it’s actually the opposite. It’s really understanding where your strengths are in the market. Um, who’s in your partner ecosystem? What are you bringing to market? Are you, uh, a tech company that are looking to break? Bridge and bring out services or your services company, and now that can build product. [00:13:01] Rebecca Jones: But really understanding your opportunity. What industry do you play, what specialization do you have? And go really deep and then know how to augment your partners and the ecosystem around you to make you stronger and better for the customer. So with that market opportunity, which is. Tremendous, how do you focus and prioritize? [00:13:21] Rebecca Jones: And that’s where I have observed partners. Oh, I’m a little bit here, a little bit there, a little bit here. And, and, uh, I would be curious, I mean, that’s probably pretty hard for you if a partner shows up and they’re a little bit of everything. [00:13:34] Mark Yaphe: Well, I, I resonated with a point that you made before. Yeah. I, I’ve spent, um, half my time at AWS on the consulting side working with enterprise customers, the us half the partners. [00:13:43] Mark Yaphe: It’s critical that partners understand what’s unique about them. [00:13:45] Exactly. [00:13:46] Rebecca Jones: Yeah. [00:13:47] Mark Yaphe: You it. I mean, everybody here, they’re looking at cloud migrations and modernizations and agentic, but that’s kind of part of the noise. You’ve gotta know what uniquely you do in an organization to deliver value. Are you developing supply chain for transportation companies or drug acceleration pipelines for. [00:14:06] Mark Yaphe: Pharmaceuticals. Yeah. Starting with that anchoring on your differences, I think is, is really important. [00:14:11] Vince Menzione: When I first started in the partner world, that was one of the biggest challenges and dilemmas, and I’m sure you still see it today, where I do all things. You know the partner that does the big SI that does everything, they have all the certifications. [00:14:24] Vince Menzione: I have 10,000 people trained on every technology certification, right. And then like, well what do you do? Like, and they can’t clarify. Right. Have that conversation. [00:14:33] Mark Yaphe: And then how do people, customers, [00:14:35] Vince Menzione: yeah. [00:14:35] Mark Yaphe: Or sales organizations choose you and why. [00:14:38] Vince Menzione: Yes, exactly. Exactly. So how do you get them to show up in that way? [00:14:43] Vince Menzione: Like especially if they’re like, how do you coach them through that? ’cause it feels like it’s still exists, right? This like mentality or this mindset. I can do all things, especially with the shiny objects that we’re facing today. [00:14:55] Rebecca Jones: Mm-hmm. [00:14:55] Vince Menzione: And I feel like we’re almost, I, I almost feel like we’re at a point right now where we were getting clearer and we’ve had so many shiny objects, even just in the last few months. [00:15:03] Vince Menzione: Like you were talking about how like months feels like ears, uh, you know, I’ll, I’ll use the Claude example here. Yeah. ’cause we, a lot of us pivoted and shifted and like, what do I do now as a partner in the room? Again, I think you, you mentioned the solving for business outcomes for client outcomes as opposed to chasing the next shiny object. [00:15:24] Vince Menzione: Like how do you get, how do you coach them on that? [00:15:27] Mark Yaphe: It’s always on the agenda. It’s, it’s day one conversations. Yeah. Who are you? What’s unique about you? How do you deliver value? Which customers do you focus on and with? Which use cases, and if it is a jack of all trades. Then my team, my and my team will help ’em. [00:15:42] Mark Yaphe: We know that down to specific areas of focus. [00:15:44] Vince Menzione: Yeah. So how do partners need to evolve their capabilities? Like how do they, I mean, how do they actually hone in on this? Like, you know, okay, I can state one thing, but how do I hone in on my capabilities, offerings and teams to stay relevant during this time? [00:15:59] Mark Yaphe: Um, what I’m coaching them on right now? Yeah. That’s what I is, uh, use the technology internally. The agentic tools and the gen AI tools are. I’ve been at this for a while, and the tools that exist right now dramatically expand your capability and capacity. So the thing I coach ’em is embed them in your organization. [00:16:18] Mark Yaphe: Yeah. Mm-hmm. Tackle those key things organizationally. You need to change and leverage these tools to help you accelerate. [00:16:23] Vince Menzione: And they’ll help you solve, they’ll help you solve for absolutely any of them. Right. It’s like, it’s like hiring a consulting organization to come in and solve for that. [00:16:29] Mark Yaphe: Yeah. [00:16:29] Vince Menzione: Yeah. How are you thinking through this? [00:16:31] Rebecca Jones: Well, uh, there’s a couple things I’m thinking about. Um, if you start to. I’ll stay with the customer for just a minute because you’re talking about Claude and just the dramatic improvement. [00:16:45] Guest: Yeah, [00:16:46] Rebecca Jones: that’s there. Just with Claude, uh, we start to think about highest and best use of the model because, uh, we had another talk earlier about the economic conditions and the. [00:16:58] Rebecca Jones: And so now we’re asking partners like, right, [00:17:01] Vince Menzione: the tokens. [00:17:01] Rebecca Jones: Yeah. Yep. How do you specialize and be focused by industry, by workflow, by use cases, you’re gonna start to look at what is the ROI of that investment? Is this a good enough? Look at the models, look at how you’re using that, and you’re having a token conversation because the economics might not be there. [00:17:21] Rebecca Jones: And so as you’re a business and a customer looking to transform their organization. They’re going to look across the business and figure out what are the highest and best use cases that should get that focus. And as a partner, if you wanna be in that conversation and really helping that company or that. [00:17:40] Rebecca Jones: Customer transform from where they are. It’s not only industry specialization, but it’s functional and workflow and really helping them understand what they should be using in that particular use case. So specialization is king or queen and that, um, scenario, and that’s where, you know, you ask partners today to specialize because there’s a whole economic conversation coming behind that, around how do you think about the models as that new one shows up? [00:18:09] Vince Menzione: Let’s shift from the technical side to the human side. [00:18:12] Rebecca Jones: Yeah. [00:18:13] Vince Menzione: Super important, right? I mean, we were having this conversation internally, like everybody’s saying, you know, jobs are going away, jobs are going away. I think I, I believe more jobs are gonna happen, but we’ve gotta get humans aligned properly to what their new roles will be. [00:18:29] Vince Menzione: Comments on this one? [00:18:31] Mark Yaphe: I think this is like a classic organizational transformation Yeah. Question. Mm-hmm. Where the 70, 80% of the problems are people process change. Um, I, I think there are these three areas that organizations need to focus on, and I’m gonna sound a little bit repetitive, but one, it’s okay. [00:18:46] Mark Yaphe: It’s, uh, the role of the team members have gotta be focused on outcomes, especially when things are moving quickly and there’s ambiguity. The one way that you can anchor on moving in the right direction is how do I let my customer, so one is outcomes. The second one is the builder mindset. Move from, I’m presenting, I’m hearing, but I’m gonna build things. [00:19:05] Vince Menzione: Yeah. [00:19:05] Mark Yaphe: And the last one is, uh, inspiring your team, making them competent and confident to navigate ambiguity because that is the premise upon which everybody’s operating. So those three, [00:19:17] Vince Menzione: Rebecca, what capabilities. Would be embodied in, in that organization that Mark describes. [00:19:23] Rebecca Jones: Yeah, I think that the growth mindset, you know, if you can package that around, you can either, um, think about being disrupted or being a disruptor. [00:19:34] Rebecca Jones: And if you have a growth mindset around the opportunity that’s ahead, it’s a whole different perspective of the challenges before you. I love that. And so when I think about what. Capabilities. You know, it’s the critical thinking and the judgment, human connection. We’re all here for a reason. Yes. Right? [00:19:50] Rebecca Jones: Yes, yes. And so as a leader, um, really helping set that tone and letting them see the art of the possible, um, around that vision. But it’s really, if I boiled it down to one thing, it’s having a growth mindset to the opportunity ahead. [00:20:05] Vince Menzione: Well, I wanna open it up. We have about five minutes left. Yeah. And this has been so insightful, but I. [00:20:11] Vince Menzione: I mean, I feel the energy. There’s gotta be some questions out here too. ’cause this, we have two incredible experts up here talking. I mean, and this is such an impactful conversation today. So John’s got a mic and uh, I think we’ve got some questions coming. [00:20:32] Vince Menzione: Yeah, [00:20:33] Rebecca Jones: this’s [00:20:33] Vince Menzione: a long way [00:20:33] Rebecca Jones: around. [00:20:34] Vince Menzione: Took a [00:20:34] Guest: thanks, long David Younger with. Thank you. That was great, great discussion. So, uh, you, you brought up a key statistic, uh, which is the MIT data and around the, the 90, I think it was 95%. Of, uh, businesses, uh, are not in production. And, and actually they, they went further to say that 95% of businesses. [00:20:56] Guest: Uh, we’re achieving zero ROI. And, and that was about a year ago, right? And now, and now you said the number, I think the number was quoted earlier today too, is, is shifting to about 70% of those, uh, projects in production. I’m curious to, to know as you, and I think you nailed it too, when you talk about product, right, have a product mindset or business mindset, right? [00:21:16] Guest: Not just how can I save money, but how can I actually generate revenue, whether it’s saving money or generating revenue. Where would you say. Uh, what, what percentage of companies you talk to are actually achieving real ROI would you say? [00:21:31] Rebecca Jones: Yeah, that’s a, that’s a great question. Really. Great. So I’ll go back and explain a little bit more about what I mean by product mindset. [00:21:39] Rebecca Jones: So a lot of companies did get stuck or there were just, uh, a. Large amount of pilots happening in the organization. And that’s not a bad thing. ’cause you think about, that’s a builder mindset, go and test and trial. But when you’re starting to look at true business transformation, you really need to think about where that, um, high value use case is. [00:22:00] Rebecca Jones: So a. The product mindset I’m talking about is taking a long-term view of the outcomes you’re trying to achieve and how are you going to measure those? And then look at that workflow, that function, and if you’re an expert in that function, whether that be a sales process or a marketing process, you know what KPIs your business is trying to drive today, and you start to unpack that. [00:22:24] Rebecca Jones: And so we’ve seen and what. Um, the most, uh, accelerated motion is knowing the KPIs and the measures you’re trying to achieve and then working towards that. And from there you can build, right? And you start to think and you have an ecosystem approach to that workflow or work stream. So we have seen, um, everybody wants cost on the system. [00:22:46] Rebecca Jones: Um, we have seen dramatic cost reduction in areas we’ve seen, you know. Two to three times, um, faster time to market. Um, there’s multiple things that we’ve seen as, uh, leaders really start to unpack that, understand what they’re trying to accomplish in the business, and I’m happy to go into greater detail. [00:23:06] Rebecca Jones: I know we have just a couple minutes left, but that’s just the product mindset up. How do you get started and how do you look at that long-term opportunity? [00:23:15] Vince Menzione: Really great answer. Mark, do you wanna add that? [00:23:17] Mark Yaphe: I think if you look at all use cases. Maybe 30% perform. But if you look at this across enterprise, I think each enterprise is finding very specific use cases where they’re driving ROI and and um, and so I think it’s about picking your spots, knowing who you are, identifying the top priority ones, not worrying about the broad enterprise transformation. [00:23:38] Mark Yaphe: Find those areas where you can drive value a little bit. Yeah, [00:23:41] Vince Menzione: that’s great that that’s almost a mic drop moment in my opinion. Yeah. That’s really great. Any other questions? I we’re holding every, oh, we got one in the back. I was gonna say I’m holding people up from happy hour. Yeah, [00:23:53] Rebecca Jones: just, we’ll just bring the cocktails in here [00:23:56] Vince Menzione: pretty soon. [00:23:57] Guest: Uh, Jeremy with Integral, um, um, a money question, something comparable. Uh, activator portfolio, the programs for founder firms that are trying to really get off the ground with new ideas. And there’s some comparable programs, I think with different providers. How much of that is a strategy, and I don’t wanna put you on the spot if activating portfolio aren’t the things you’re covering, but, but that money investment for startups that are trying to grow and really focus on AWS uh, the thousand dollars is the founder version that gets us in and then a hundred thousand dollars. [00:24:26] Guest: It’s a bit difficult to get into. And then there’s bigger ones after that if we attend the schools and all these things. But I’m thinking about as we all are trying to grow and really focus in AWS, which a lot of folks really wanna do with Bedrock and all the things that are kind of cool going on, it’s just. [00:24:40] Guest: Great AI focused conversation, but how is that playing into attracting more of the MSPs that are, that are trying to grow and more of the startups to really funding this idea of, of startup mentality. Hopefully that’s not too off topic, but your, your fair game [00:24:57] Mark Yaphe: was, was the question, how does funding. [00:25:01] Mark Yaphe: Attract startups in specific categories, process. [00:25:04] Guest: I think it’s, it’s about if there’s, uh, the other hyperscalers also have programs comparable. So Microsoft’s program is, uh, 150 grand to to, to build out the founder kind of, and it’s fairly easy to get into. Aw. WS is a bit harder to get into, but is that going to change as far as using that as a, as a key strategy for incubating more and more ideas to accelerate the velocity of everything you guys were talking about? [00:25:25] Mark Yaphe: I’m really not the right person. Definitely outta my wheelhouse on that. No problem. [00:25:31] Guest: Yeah. [00:25:37] Vince Menzione: And we’re about seven seconds away from uh, happy hour. [00:25:41] Rebecca Jones: I know, [00:25:41] Vince Menzione: I know. This was fantastic. I know. It was so great. [00:25:44] Rebecca Jones: Yes. [00:25:45] Vince Menzione: And I think the McKenzie thing is gonna stick. I think it is, it is. [00:25:48] Rebecca Jones: Now, mark, I’m gonna make [00:25:49] Vince Menzione: sure it does. And Mark, it was great to have you up on stage with us today. So, so great to have AWS supporting us and sponsoring the event with us and, uh, and having just this broad audience of people just so interested in. [00:26:02] Vince Menzione: Being in the room and and learning from each of you. So thank you so much today. Thank you. Appreciate it. Thank you. Thank you. [00:26:09] Mark Yaphe: Thanks for listening to The Ultimate Partner [00:26:11] Vince Menzione: Podcast. If today’s conversation resonated, share it with a partner leader in your network. Subscribe where you listen, and head over to the ultimate partner.com. [00:26:22] Vince Menzione: For show notes related content and the resources for this episode. And if you haven’t already, now’s the time to register for the Ultimate Partner Live Event in Reston, Virginia, October 26th through October 28th. Until next time, keep showing up in the rooms that matter because being in the room changes everything.

There is simply too much greenwashing happening. Environmental reporting has become a meaningless bureaucracy feeding a fictional reality through glossy reports that nobody reads anymore.  But things are changing; the impact of climate change (heatwaves, floods) is hitting back at governments trying to ignore it. Some BigTech, historically in favour of renewable energy are now busy building the biggest gas plants in the world for their datacenters, while pretending still to be on track for their “net zero” commitments.  They maintain the fiction through carbon accounting tricks, maximisation of loopholes and heavy PR campaigns run by the American Petroleum Institute and McKinsey.  Fortunately, there are a lot of companies which start to see the direction of travel: a more granular way of accounting for Energy and Emissions. Not by the year, where summer solar can be accounted for winter consumption, but by the month and soon by the hour.   Hourly matching is new, tough, but far from unsurmountable. That is what new companies such as Renewabl are enabling: by cutting though the bureaucracy and Excel Sheets, and helping the forward thinkers to present, report and optimise their energy and emissions profile.  Laurent and Gerard have the privilege of receiving Carolyn Addy, Head of Commercial at Renewabl, to talk about the new trends, the innovations, and how progressively, we are entering a more transparent and efficient world.  We talk about immediate non-regret solutions and the impact of AI in the process. We also dive into how hourly PPAs are progressively making their way into the market, and whatever perceived additional work they require, in fact they provide better hedges against volatile energy costs.

319. bölümde, şirketlerin yapay zekâ sayesinde yazılım satın almak yerine kendi çözümlerini geliştirmeye yönelmesini konuşuyoruz. McKinsey'in araştırmasına göre şirketlerin yüzde 32'si bu nedenle en az bir yazılım satın almaktan vazgeçmiş durumda. Peki bu gerçekten bir maliyet avantajı mı, yoksa birkaç yıl sonra karşımıza çıkacak gizli bir fatura mı? Yapay zekâ yazılım dünyasında dengeleri değiştirirken, “kendimiz yaparız” yaklaşımının ne kadar doğru bir strateji olduğunu sorguluyoruz. (00:00) - Açılış (00:45) - Şirketlerin %32'si yazılım satın almaktan neden vazgeçti? (01:30) - Teknoloji şirketlerinde oran %41 (02:10) - Raporun gözden kaçan ikinci rakamı (02:55) - Yapay zekâ gerçekten kârlılığı artırıyor mu? (03:40) - Satın almak mı, kendin yapmak mı? (04:20) - AI projelerinde başarısızlık ve güvenlik riski (05:05) - Yazılımı kendin geliştirmenin gizli maliyetleri (05:55) - Yapay zekânın kendi çalıştırma maliyeti (06:35) - “Ayda 500 dolarlık abonelikten kurtuldum” hesabının yanılgısı (07:15) - Bulut dönüşümüyle benzerlik: Aynı hatayı mı yapıyoruz? (07:55) - Şirket yöneticileri için 3 kritik soru (08:45) - Yazılım şirketleri için yeni dönem (09:25) - Devrim mi, yanılsama mı? (10:05) - Abonelikten mi kurtuluyorum, faturayı mı erteliyorum? (10:30) - Kapanış Sosyal Medya takibi yaptın mı? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠  – ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ – ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ – ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ – ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Goodreads⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Bülten⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ – ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠E-Posta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ – Bu çalışmaları ve emeklerimi desteklemek için ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Patreon⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠  ve ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Buy Me A Coffee⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ hesabımız⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome to the What's Next! Podcast with Tiffani Bova.    I'm excited to welcome Caroline Webb to the show this week. She is an economist, executive coach, former McKinsey partner and senior advisor to the firm, and the best-selling author of How to Have a Good Day. She's also been recognized by Thinkers 50 as one of the world's top executive coaches. Her new book, Leadership Intelligence, draws on psychology, neuroscience, and behavioral economics to tackle 21 of the everyday challenges leaders face.    THIS EPISODE IS PERFECT FOR…leaders and managers looking to lead more effectively under pressure, communicate with greater intention, and turn good leadership knowledge into better everyday behavior.   TODAY'S MAIN MESSAGE…knowing what good leadership looks like is one thing; practicing it when you're tired, stressed, or under pressure is another. Caroline explains how stress affects our ability to think and respond well, and shares practical ways leaders can pause, ask better questions, give clear feedback, and stay connected to what matters.   KEY TAKEAWAYS: Stress and fatigue can make good leadership much harder to access in the moment. Small habits can help leaders respond thoughtfully instead of reacting. Better questions create space for people to share concerns and different perspectives. Clear, specific feedback is a form of kindness, not a lack of empathy. Taking a pause can lead to better decisions and better leadership.   WHAT I LOVE MOST…great leadership isn't about being perfect. It's about building the habits that help you respond with intention when it would be much easier to react. Running Time: 25:35   Subscribe on iTunes   Find Tiffani Online: LinkedIn Facebook X    Find Caroline Online: LinkedIn Website   Caroline's Book:  Leadership Intelligence: Science-Backed Strategies for Mastering 21 Everyday Management Challenges

While the podcast team is taking a Radical Sabbatical, Kim is interviewing authors whose books have had a big impact on her over the past two years.  In this episode, Kim Scott speaks with Caroline Webb about her latest book, Leadership Intelligence.  They explore the principles of effective leadership: the importance of widening perspectives; the role of cognitive load in decision-making; and the significance of intrinsic motivation through competence and connection. The conversation also delves into the dynamics of disagreement, the necessity of feedback, and practical strategies for fostering a collaborative team environment. They review effective feedback techniques and the significance of public praise.  Caroline also emphasizes the role of gratitude and giving praise in building strong workplace relationships, the importance of understanding stress and resilience in leadership, and how leaders can foster team resilience through structured conversations and practices. The discussion culminates in the introduction of the five C's of team resilience, emphasizing the need for communication, clarity, calm, connection, and capacity in creating a supportive work environment. Guest Background: Caroline Webb is a leadership coach, economist, and speaker known for being one of the world's leading experts in using insights from behavioral science to improve professional life. She is the author of Leadership Intelligence and of How To Have A Good Day, a global bestseller published in 20 editions and over 60 countries. She is also a Senior Advisor to McKinsey, where she was previously a Partner. She has been rated one of the top 50 leadership and management thinkers by Inc. magazine, and one of Thinkers50's top 50 executive coaches in the world. CHAPTERS (00:38) Introduction to Leadership Intelligence (03:24) Deliberate Wisdom: Widening Perspectives (06:29) Causal Maps and Driver Trees (09:27) Navigating Disagreements in Leadership (12:30) The Importance of Turn-Taking in Discussions (15:22) Lightening Cognitive Load for Better Leadership (19:19) Intrinsic Inspiration: Competence and Connection (22:21) The Power of Feedback in Engagement (30:29) Effective Feedback and Praise Techniques (32:57) The Importance of Public Praise (37:01) Cultivating Gratitude and Appreciation (37:32) Understanding Stress and Resilience (44:45) Building Team Resilience with the Five C's Connect with the Radical Candor team: ⁠⁠⁠⁠⁠⁠Website⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

Dr. Caroline Webb, a behavioral scientist, former McKinsey partner, and author of Leadership Intelligence. Drawing from her background at the Bank of England and McKinsey, she specializes in translating behavioral science into practical tools for working life. Her new book, Leadership Intelligence, is out now. Dr. Caroline Webb joined host Robert Glazer to talk about Leadership Intelligence, Behavioral Science in Business, and Applying High Standards to Work and Life. Thank you to the sponsors of The Elevate Podcast Shopify: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠shopify.com/elevate⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Masterclass: ⁠⁠⁠⁠⁠⁠⁠⁠masterclass.com/elevate⁠⁠⁠⁠⁠⁠⁠⁠ Framer: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠framer.com/elevate⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Northwest Registered Agent: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠northwestregisteredagent.com/elevate⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Indeed: ⁠⁠⁠indeed.com/elevate⁠⁠