Podcasts about mckinsey

How might economic frustration influence the way people evaluate political candidates? In this episode of PIVOT with Darryl Lyons, Darryl examines a recent McKinsey Institute for Economic Mobility report, In Pursuit of Progress: Americans' Aspirations for Economic Mobility, to explore the financial pressures and lack of economic confidence that can shape how people think about the future and who they choose to support. Using survey data from 30,000 adults, Darryl breaks down four major themes: the common desire for financial security, the cost squeezes people experience at different stages of life, the importance of community, and the role proximity plays in helping people move forward. He discusses rising living costs, health care, child care, housing, retirement savings, and the financial shocks that can make it difficult for families to build stability. Darryl also explores the roles employers, friends, family, churches, and government institutions play in helping people find opportunities. From a Christian worldview, he argues that community and relationships can create practical opportunities for people who are struggling, while employers can help employees build skills and become more valuable in the marketplace. Ultimately, this episode looks beyond politics to ask a more important question: What happens when people feel like they have no financial security, no clear path forward, and little hope for the future? You'll learn: • Why financial security is a priority for so many Americans • How rising costs affect people at different stages of life • Why groceries, health care, child care, and housing are major financial pressure points • What retirement savings reveal about economic mobility in America • Why strong community connections can influence people's sense of control and momentum • How employers can help employees improve their skills and financial opportunities • How economic frustration may influence political choices This episode is for anyone interested in financial planning, economic mobility, personal finance, leadership, community, and the forces that influence how people think about their financial future and political choices. Benefiting from the show? We'd appreciate it if you left a review on your favorite podcast platform. Resources: Americans' aspirations for economic mobility | McKinsey

Regrouper les infirmiers pour faire des économies. Leur retirer le téléphone, un centre d'appels s'occupera de tout. Chronométrer chaque geste : deux minutes trente pour un bas de contention, dix minutes pour une piqûre. Poser un code-barres sur la porte du patient, pour scanner à l'entrée et à la sortie. Chaque étape est raisonnable. Le résultat est un cauchemar, et c'était le vrai visage des soins à domicile aux Pays-Bas.Frédéric Laloux est l'auteur de Reinventing Organizations, autoédité en 2014, vendu à plus d'un million d'exemplaires et traduit dans plus de vingt langues. Ancien associate partner chez McKinsey, il a tout quitté à 32 ans après une séance de coaching qui devait durer une heure et en a duré trois. Il a passé des années à étudier une douzaine d'organisations qui fonctionnent sans managers, puis a refusé la suite logique : les conférences à six chiffres, les sièges au conseil, le statut de gourou. Il vit aujourd'hui à Ithaca, dans l'État de New York, et a cofondé avec sa femme Hélène The Week, une expérience collective sur le climat suivie par plus de 75 000 personnes dans 500 entreprises.Je suis venu à cette conversation avec un aveu à faire. « Predict and control », prévoir et contrôler : c'est un vocabulaire que j'ai moi-même utilisé, et sans doute abusé, pendant des années. Frédéric ne juge pas cela. Il montre simplement, exemple après exemple, qu'un autre regard existe, et ce qu'il libère quand on ose le porter. C'est l'une des conversations les plus dérangeantes, et les plus pleines d'espoir, que j'aie eues sur ce podcast.Dans cette conversation, nous explorons :→ Buurtzorg, fondé en 2006 par Jos de Blok avec quatre infirmières : aujourd'hui 15 000 soignants, zéro manager, et la moitié seulement des heures de soins que les médecins prescrivent, parce que le but n'est pas d'optimiser la minute de traitement mais de rendre le patient autonome→ Les trois piliers de Reinventing Organizations : l'autogouvernance, la plénitude, la raison d'être évolutive, et le basculement de « predict and control » vers « sense and respond »→ Pourquoi le problème n'est presque jamais les individus, mais la structure : ce que Frédéric a compris après quatre ans de coaching de comités de direction→ L'IA comme révélateur : le même outil, les mêmes équipes, et deux regards qui mènent à deux mondes opposés→ Douglas McGregor et les théories X et Y : les deux sont vraies, parce que les deux sont autoréalisatrices« Quand on enlève la hiérarchie de pouvoir, on enlève une sorte de poison qui existe entre nous. »Frédéric Laloux, auteur de Reinventing OrganizationsSi vous avez déjà senti qu'une réunion cachait plus qu'elle ne disait, que personne n'osait nommer l'éléphant dans la pièce, cet épisode vous expliquera pourquoi, et ce qu'on peut faire d'autre.

While the podcast team is taking a Radical Sabbatical, Kim is interviewing authors of the books that have had a big impact on her in the past two years.  In this episode, Kim Scott speaks with Angela Duckworth. Her first book Grit: The Power of Passion and Perseverance, is a #1 New York Times bestseller. Her second book is Situated: Find the People and Places That Bring Out Your Best. In this conversation, Kim interviews Angela about her new book, 'Situated.' They explore a deceptively simple three-box model that explains all of human behavior. Angela emphasizes the power of environment in shaping our thoughts and leading us to–or away from–the results we want. She and Kim discuss the limitations of willpower. Angela describes the two key ingredients of a good situation: challenge and support. Kim and Angela explore why it is important to seek managers and peers who both challenge and support us. They discuss the importance of feedback and why Ruinous Empathy is so damaging to both personal and professional growth. If you're looking for one thing you can control to get better situated, Angela shares some practical advice on curating your personal space to foster positive habits and growth. Guest Background: Prof. Angela Duckworth, PhD, is the Rosa Lee and Egbert Chang Professor at the University of Pennsylvania and faculty co-director of the Penn-Wharton Behavior Change for Good Initiative.  Prior to her career in research, Angela founded an academic enrichment program for low-income children that was profiled as a Harvard Kennedy School case study and today serves hundreds of students each year. She has also been a McKinsey management consultant and a math and science teacher at public schools in New York City, San Francisco, and Philadelphia. Angela co-founded Character Lab, a nonprofit dedicated to advancing scientific insights that help children thrive. Angela completed her undergraduate degree in Advanced Studies Neurobiology at Harvard, graduating magna cum laude. With the support of a Marshall Scholarship, she completed an MSc with Distinction in Neuroscience from Oxford University. She completed her PhD in Psychology as a National Science Foundation Graduate Fellow at the University of Pennsylvania. Angela's TED talk is among the most viewed of all time. CHAPTERS (00:00) Introduction to Radical Sabbatical and Angela Duckworth's New Book (03:23) The Snorkeling Incident: A Metaphor for Situational Awareness (05:58) Finding Your Best Situations: The Power of Environment (08:31) The Three Boxes Model: Understanding Behavior and Thoughts (11:13) The Role of Situations in Shaping Our Thoughts (14:16) Changing Your Situation vs. Changing Your Thoughts (17:10) The Limitations of Willpower and Self-Control (20:13) The Quest for Control: Understanding Human Nature (23:15) Creating Supportive and Challenging Situations (27:11) Understanding Radical Candor (32:56) Navigating Ruinous Empathy (33:19) The Dilemma of Short-Term Comfort vs Long-Term Growth (34:30) Feeding the Good Wolf: A Metaphor for Growth (36:40) Economic Disparities and Their Impact (39:23) Agency and the Power of Choice (43:09) Curating Your Personal Space for Better Outcomes Connect with the Radical Candor team: ⁠⁠⁠⁠⁠⁠Website⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

Most HR teams have already run their AI experiments. A pilot here, a policy draft there. Turning that scattered activity into something people actually use on a Tuesday is a completely different problem. In this episode: Why the biggest available gains from AI now come from teams working with it together, not individuals getting better at prompting How to pick a first project by finding the rock in your shoe instead of announcing a sweeping overhaul nobody asked forWhat the three Cs (crisis, commitment, and conflict) tell you about where AI should never touch an employee interaction Timestamps [00:01:52] What an AI catalyst actually does inside an HR function, and why the job changed from building fluency to driving adoption [00:02:49] Why HR teams that feel behind on AI are not, and what the range across SHRM's membership really looks like [00:03:53] Finding the rock in your shoe, and why the most annoying problem beats the most sophisticated one as a starting point [00:07:29] Nichol's dictation method for getting a model to write her prompts, including asking for a McKinsey-style or Fast Company-style prompt [00:08:15] How vibe teaming works, including the AI wrangler role, the facilitator role, and the transcript loop that feeds the group's corrections back in [00:10:08] The loneliness problem created by heavy individual AI use, and the 70-page proposal exchange that illustrates it [00:11:22] Over 44% of people use AI daily and nearly as many run into work slop daily, and what a biweekly team session does about it [00:12:44] Eight executive assistants who used vibe teaming remotely to redesign how their C-suite works together [00:15:09] The three Cs guardrail: crisis, commitment, and conflict are the moments to keep AI out of entirely [00:17:19] Why people can always tell whether a real human was on the other side, even when they can't identify AI-generated text Guest Bio Nichol Bradford is a futurist, investor, and executive with more than 20 years across technology and human potential. Her mission is to strengthen humanity's mental, emotional, and social health (MESH) as the foundation for innovation and progress. She reaches over 100,000 people annually through thought leadership and public speaking, including TEDx. As SHRM's AI + HI Executive-in-Residence, Bradford shapes global strategies that reach 362 million workers and their families through 340,000 HR professionals in 180 countries. In June 2025 she founded and launched Human Tech Week, which drew 250 speakers and more than 1,200 attendees in its first year. That event grew out of TransformativeTech.org, the global community she co-founded and built to members in 72 countries. She also co-founded Niremia Collective, a venture fund backing the future of human potential. Bradford works at the seam between advanced technology and deep human need, with a focus on human-centered AI adoption. Before this, she operated World of Warcraft in China. Today she runs the largest network for human potential technology. Brought to You by Paylocity Paylocity is the fastest growing unified platform for HR, Finance, and IT. Paylocity brings your people, processes, and data together in one place so HR leaders can spend less time managing systems and more time doing the work that actually moves their organizations forward. Learn more at paylocity.com Keywords: AI adoption in HR, responsible AI, vibe teaming, collective intelligence, work slop, AI guardrails, human potential, SHRM, AI catalyst, HR technology, team productivity, prompting, talent acquisition AI, performance management, employee experience, change management, workforce wellbeing, human-centered AI, Nichol Bradford, HR Mixtape

Send us Fan MailMost consulting interviews let you drive the case. McKinsey doesn't.McKinsey is one of the only firms that runs interviewer-led cases – the interviewer leads the case, not you.So candidates who prep the way BCG or Bain expects walk in ready for the wrong format.And the case is only half your score – the PEI (Personal Experience Interview) is the other half.Ex-McKinsey coach Mark Di Giorgio breaks down why the interviewer-led format catches strong candidates off guard, how to build your PEI story bank, plus the 3-week prep plan when you don't have a lot of time left.Resources:Join a Black Belt cohort to get paired with a McKinsey coach who's run McKinsey's actual interviewer-led cases from the insideCase Competition World Cup – Fall 2026Applications are open. Free for all students. Apply by Sept. 13.APPLY HEREConnect 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 does it really mean to lead with purpose in a world that rewards speed over intention?In this episode of B the Way Forward, host Brenda Darden Wilkerson sits down with Betsy Ziegler, CEO of 1871, one of the nation's premier startup incubators and innovation hubs in Chicago. From her early days at McKinsey and GE to leading innovation at Northwestern University's Kellogg School of Management and now championing thousands of founders through 1871, Betsy has built a career defined not by a linear plan, but by a learner's mindset, radical authenticity, and an unwavering commitment to expanding what people believe is possible for themselves.Brenda and Betsy dig into what it takes to lead through ambiguity, how to stay grounded in your identity when your title becomes your identity, and why the future will be shaped by whoever has the courage to grab the pen. This is a conversation about redefining leadership, reimagining success, and building something that lasts beyond yourself.Connect with Betsy on Twitter (@betsyzeo) and LinkedInWe Learned AboutStaying present as a leader while operating in environments that are constantly looking aheadWhy non-linear career paths are the norm, not the exception, and why that's actually a competitive advantageThe "40 by 40" list framework Betsy used to reorient her life around living, not just achievingHow authentic leadership can cost you power in some rooms while building deep trust in othersThe danger of defining your self-worth through your job titleChapters:0:00 Introduction & Season Theme1:44 Welcome to B the Way Forward – Meet Betsy Ziegler3:11 Betsy's Response: Partnership Between 1871 and AnitaB.org4:02 Leading in the Present While Focused on What's Next8:26 Was Your Career Path Linear? Betsy's Honest Answer13:10 The "40 by 40" List That Changed Everything16:08 Letting Go of Certainty to Step Into Something New19:42 Trusting Yourself Through Major Career Reinventions21:53 The Danger of Giving Too Much of Yourself Away25:07 How Betsy Separates Urgency From Importance29:56 Authenticity in Leadership: Where It Costs You and Where It Pays37:16 What Really Motivates Founders (It's Not the Metrics)43:24 A Founder Story That Shifted Betsy's View on Impact46:00 What People Misunderstand About Failure50:20 Advice for Anyone Struggling to Believe in Themselves Right Now54:05 AI, Abundance, and Who's Grabbing the Pen1:00:05 Closing Thoughts and Defining Integrity#BTheWayForward #WomenInLeadership #StartupEcosystem #Leadership #Innovation1871 #AuthenticLeadership #AIandInnovation

What if the most powerful AI in your practice still isn't the thing winning your cases? Sara Cordrey, CEO and co-founder of the legal AI platform Parambil, built with chief medical officer Dr. Ralph Horwitz, argues that technology is leverage—not a substitute for a lawyer's judgment or for the medical record itself. Drawing on her McKinsey work analyzing gaps in patient care, she explains how purpose-built AI helps trial lawyers rip through records, reorder how cases get worked up, and surface insights sooner—while never leaving the primary source behind. Host Ben Gideon digs into build-versus-buy, data security, and where legal AI is heading next.Learn More and Connect☑️ Sara Cordrey | LinkedIn☑️ Parambil | LinkedIn | YouTube | Instagram☑️ Ben Gideon | LinkedIn | Facebook | Instagram☑️ Gideon Asen on LinkedIn | Facebook | YouTube | Instagram☑️ Rahul Ravipudi | LinkedIn | Instagram☑️ Panish Shea Ravipudi LLP on LinkedIn | Facebook | YouTube | Instagram☑️ Subscribe: Apple Podcasts | SpotifyProduced and Powered by LawPods, a podcast marketing agency for law firmsSponsored by SmartAdvocate, Hype Legal, Expert Institute, and Steno.

This week, former Forrester Research Director Jeff Clark is back in the studio after his summer break with our host Ian Truscott to discuss an article in The New York Times called “I Helped Run Lululemon. Companies Need to Stop Kidding Themselves About A.I.” written by Julie Averill, the former chief information officer of Lululemon, and some interesting research from McKinsey that supports her experience.  The article discusses A.I. wishing and A.I. washing, and Jeff and Ian discuss how to get A.I. working and share 5 tips:  Create an effective business case Map processes Clean up your data Incorporate your culture Create a change management plan Then, Ian moves to our virtual bar, The Rose and Rockstar, and joins Robert Rose, Chief Trouble Maker at Seventh Bear, to discuss what else we marketers should be talking about, if not AI, and Robert suggests three classic marketing moves that can cut through, while everyone else focuses on digital and A.I. Enjoy! — The Links The people: Ian Truscott on LinkedIn  Jeff Clark on LinkedIn Robert Rose on LinkedIn Mentioned this week: I Helped Run Lululemon. Companies Need to Stop Kidding Themselves About A.I. Helping AI succeed in retail: Turn pilots into measurable impact | NRF The State of AI: Global Survey 2026 | McKinsey  Rockstar CMO: The Beat Newsletter that we send every Monday Rockstar CMO on the web and LinkedIn Previous episodes and all the show notes: Rockstar CMO FM. Track List: We'll be right back by Stienski & Mass Media on YouTube Piano Music is by Johnny Easton, shared under a Creative Commons license Dolly Parton - The Seeker (Official Audio) You can listen to this on all major podcast platforms, including Apple Podcasts, Amazon Podcasts, and Spotify. Learn more about your ad choices. Visit megaphone.fm/adchoices

Send us Fan MailMost candidates prep for the McKinsey PEI like a regular behavioral interview.McKinsey built it to do more than that. One story, and up to 25 follow-up questions testing whether what you said the first time still holds.That's why memorized answers fall apart under the PEI. Scripted stories crack under repeated follow-ups. The ones that hold up are built to survive being asked the same thing five different ways. In this episode, Namaan breaks down the four traits McKinsey scores in the PEI and how to build stories that survive the follow-ups.Resources:Prep your PEI stories one-on-one with a former McKinsey interviewer through Black BeltLearn more about McKinsey's interview processConnect 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

For large facilities scrambling to bring new energy capacity online, waiting several years for a new grid connection is not a viable option. John Carrington, CEO of ERock, and Jesse Noffsinger, Partner at McKinsey & Company, discuss current trends in behind-the-meter (BTM) generation and how it can provide a faster solution while utilities build needed grid connections. Over the long term however, BTM resources could shift from serving individual customers to supporting the larger power system. John and Jesse also explore the challenges that come with rapid growth on the grid, including supply chain constraints, complex large-load rate structures, and how costs and benefits should be shared. Hear two expert viewpoints on this fast-evolving BTM area in this episode.

Today, I am delighted to speak with Cory Klippsten, Founder and CEO of Swan, a financial services company that focuses exclusively on Bitcoin. Cory is an investor or advisor in more than 50 technology startups and was named to the Top 500 Most Influential list by LA Business Journal in 2024 and 2025. He is a partner in Bitcoiner Ventures, El Zonte Capital, and The Bitcoin Opportunity Fund, and as an angel has funded more than 60 early-stage tech companies. Before startups, Cory worked for Google, McKinsey, and Morgan Stanley, and earned an MBA from the University of Chicago. He is a frequent guest and contributor to tech, financial and Bitcoin media. Recent appearances include CNBC, Bloomberg, Barrons, The New York Times, and Yahoo! Finance. Cory explains how Bitcoin features in the asset portfolios of UHNW families and family offices today and how their attitudes and exposure to this foundational digital asset have evolved over the past few years. He also comments on how Bitcoin compares to or stands out from other digital assets families are considering or investing in. In the grand scheme of things, Bitcoin is still a relatively new asset, and many investors are still coming up the learning curve on how to invest in it. Cory talks about where Bitcoin is today in its maturity curve and its progression from a frontier digital alternative to an established, mainstream asset class. Cory offers his views on the best tools and platforms for families and family offices to become educated on Bitcoin and to keep up with the latest trends and development in this avant-garde space. He describes the products and providers family offices should consider when investing in Bitcoin and participating in the continued ascendance of this and other major digital assets. Don't miss this fascinating conversation with a prominent Bitcoin pioneer, innovator, and entrepreneur. Episode Resources from Cory Klippsten "The Bullish Case for Bitcoin" article Vigil Protocol family financial orchestration (complimentary trial for FOX listeners) "Welcome to Bitcoin video" series "Inventing Bitcoin" book Stephan Livera "Intro to Bitcoin Austrian Economic Thought" "Broken Money" book by Lyn Alden

What if the biggest mistake a small business can make is trying to operate like a big company? In this episode of the Deep Leadership podcast, I'm joined by Sri Kaza, seasoned business leader, former McKinsey advisor, entrepreneur, and author of Unconvention. After studying thousands of small businesses and examining which ones survived major disruptions, Sri discovered something surprising: the companies that endured weren't necessarily following conventional business wisdom. They were doing things differently. Sri explains why small businesses have advantages that large corporations struggle to replicate, including close relationships with customers, a clear sense of purpose, and the ability to make fast, unconventional decisions. We also discuss why chasing growth can actually weaken a business, how knowing which customers not to pursue can make you stronger, and why resilience often comes from staying true to what makes your business unique. In this episode, we discuss: • Why small businesses shouldn't try to operate like big corporations• What Sri learned from studying thousands of businesses during COVID• The three Ps of resilient businesses: positioning, proximity, and purpose• Why knowing your ideal customer is critical to long-term success• The danger of chasing growth at the expense of your identity• Why small businesses have a natural advantage in uncertain environments• How an underdog mindset helps entrepreneurs compete against larger companies• Why purpose and community can make a business more resilient• The customers your business should be willing to lose• Why leaders should role model their values instead of relying on policies Sri Kaza is the author of Unconvention, a book that challenges traditional corporate thinking and shows entrepreneurs how to build stronger, more resilient businesses by embracing what makes them different. Connect with Sri Kaza: Website: ⁠⁠⁠⁠⁠⁠https://sri-kaza.com/⁠ Book: ⁠https://amzn.to/3Ue2Ypx Subscribe to Deep Leadership: If you enjoyed this episode, make sure to subscribe and share it with someone who wants to become a better leader. Sponsors: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cadre of Men⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Farrow Skin Care⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Salty Sailor Coffee Company⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Leader Connect⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Qualified Leadership Series⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ____ Get all of Jon Rennie's bestselling leadership books for 15% off the regular price today! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠HERE⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

Anika sat down with George Khachatryan to explore the evolving landscape of AI-driven marketing, personalization, and the massive trust gap currently sitting between brands and consumers. The conversation revealed a counterintuitive truth: while 93% of marketing leaders believe AI helps them understand their customers, only 53% of consumers agree. George's unique journey—from earning a PhD in mathematics at Cornell and building an early ed-tech AI company to founding OfferFit and navigating its $325M acquisition by Braze—offered a practical look at how reinforcement learning and predictive data science are permanently replacing the manual grind of traditional A/B testing. In This Episode How a background in mathematics and early intelligent tutoring systems laid the groundwork for complex AI architectures. Stepping away from specialized tech to learn foundational company building through management consulting and operational transformations. Moving beyond rigid "Next Best Action" rules to autonomous reinforcement learning agents that experiment at the individual customer level. The strategic decision behind merging OfferFit with Braze in a $325M deal and why deep data science and engineering alignment matters. Why hidden bots, lack of transparency, and mismatched brand expectations are eroding consumer confidence. Blending predictive machine learning models (for timing and offers) with LLM agentic copy generation for maximum impact. Why students and early-career marketers must embrace AI literacy to stay competitive in a rapidly shifting job market. Timestamps 00:00 Introduction: The math, the $325M exit, and the AI trust gap 02:00 From Cornell mathematics and early ed-tech to management consulting 04:18 The limitations of traditional "Next Best Action" and the birth of reinforcement learning 09:22 Real-world personalization: How brands like Yum Brands optimize customer engagement 12:39 The acquisition journey: Why OfferFit chose to integrate with Braze 16:53 The 93% vs. 53% problem: Why consumers feel misunderstood by brands 20:41 Hybrid AI systems: Stitching together LLM copywriting and statistical decisioning 23:33 The personal cost of a "Sydney is just a bot" moment: The importance of transparency 28:32 The reality of enterprise caution vs. consumer expectations 29:56 Agentic commerce and the future of bot-to-bot interactions 34:39 Managing negotiation bots and complex consumer retention scenarios 37:25 Generational divides: Gen Z's dual relationship with AI adoption and career anxiety 40:59 Lessons for founders: Aligning philosophical visions before a merger 43:35 Final thoughts: Embracing the historic and fascinating shift in marketing technology Key Insights & Takeaways Insight 1: Personalization Requires True One-to-One Experimentation Traditional marketing relies on segmenting audiences and applying rigid, rule-based logic. True optimization requires reinforcement learning agents that operate at the individual customer level, autonomously testing variables like messaging, timing, and offers to discover what drives incremental engagement. Insight 2: The Danger of Hidden Bots and Broken Trust Consumers do not mind interacting with AI or automated tools, but they expect transparency. When a brand masks an AI agent as a human—and fails to take responsibility for its actions—it creates a deep sense of betrayal that permanently damages customer loyalty. Insight 3: The Power of Hybrid AI Infrastructure The most effective marketing systems do not rely on a single flavor of AI. Combining statistical reinforcement learning (to determine when and what to communicate) with LLM agentic text generation (to personalize how it is phrased) yields performance lifts of over 100%. Insight 4: Shared Vision is the Anchor of Any Successful Acquisition For founders navigating a potential exit, technical integration is only half the battle. Long-term success relies on frank, open discussions about philosophical alignment, shared visions, and mutual risk mitigation before signing a deal. Insight 5: Enterprise Caution vs. Consumer Speed While marketers are often bogged down by internal alignment and slow decision-making processes, consumers are interacting with cutting-edge AI tools daily. Brands that fail to bridge this expectation gap risk becoming obsolete. Resources & Links Mentioned Braze 2026 Global Customer Engagement Review OfferFit Yum Brands & Home Security (Client case studies discussed in the episode) About George Khachatryan George Khachatryan is a mathematician, entrepreneur, and executive leader serving as the Head of OfferFit by Braze. Holding a PhD in mathematics from Cornell University, George previously co-founded the ed-tech pioneer Reasoning Mind and worked as an associate partner at McKinsey. He co-founded OfferFit, an AI decisioning engine that utilizes reinforcement learning to automate marketing experimentation, culminating in its acquisition by Braze in 2025 for $325 million. Connect with George LinkedIn: https://www.linkedin.com/in/george-khachatryan/ Website: https://www.braze.com/ Like the show? Leave us a rating or review: https://lovethepodcast.com/67940257010b317cdaa9d857Follow the Show: https://followthepodcast.com/67940257010b317cdaa9d857Send a Message: https://podcastfeedback.com/67940257010b317cdaa9d857Check out our Website: https://www.yourbrandamplified.comSpeak to my Delphi Clone: https://www.delphi.ai/amplifywithanika Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

“More Chinese companies are put out of business by other Chinese companies. Chinese companies are not put out of business because of Western companies, so this whole competition is not, from a Chinese guy's mind, like a US-China competition. It's more ‘how do I survive this gym?' because it's damn hard to keep staying alive at home. That in turn makes you very competitive in the rest of the world.”Maura Fogarty speaks to Joe Ngai, Chairman of the China region for global consulting firm McKinsey.He advises senior management at Chinese and multinational corporations in the region which gives him a unique insight into the world's second-largest economy.Having written numerous books and reports on China's economic landscape, Ngai's expertise has been recognised by accolades from the likes of Forbes China and Bloomberg.In this interview, we hear his thoughts about how the Chinese market has changed in the 25 years since the country joined the World Trade Organisation, and on how AI is developing and managing tensions with US competitors.Thank you to the Asia Business team for their help in making this programme. The Interview brings you conversations with people shaping our world, from all over the world. The best interviews from the BBC, including episodes with tech billionaire Reid Hoffman, director Chloé Zhao, and Dr Ngozi Okonjo-Iweala, head of the World Trade Organisation. You can listen on the BBC World Service on Mondays, Wednesdays and Fridays at 0800 GMT. Or you can listen to The Interview as a podcast, out three times a week on BBC Sounds or wherever you get your podcasts. Presenter: Maura Fogarty Producers: Ben Cooper and Jaltson Akkanath Chummar Editor: Damon RoseGet in touch with us on email TheInterview@bbc.co.uk and use the hashtag #TheInterviewBBC on social media.(Image: Joe Ngai. Credit: Getty)

Der deutsche Mittelstand diskutiert Künstliche Intelligenz vor allem als Effizienzthema, während das Umsatzpotenzial kaum eine Rolle spielt. Gleichzeitig fehlt vielen Unternehmen der Zugang zu den Methoden, mit denen die deutsche Tech-Szene in den vergangenen Jahren Milliardenbewertungen aufgebaut hat.Mein Gast ist Thuy-Ngan Trinh, Geschäftsführerin von A11. Mit ihr spreche ich über ihren Weg von Zalando bis in die Geschäftsführung von Project A, darüber, wo der Mittelstand bei KI heute wirklich steht, warum sie ein europäisches Palantir bauen will und noch viel mehr.Wir beleuchten in dieser Episode:warum A11 aus Project A entstand,wie A11 sich bewusst von McKinsey abgrenzt,wo der deutsche Mittelstand bei KI wirklich steht,warum die KI-Debatte das Wachstumspotenzial ausblendet,wie der Verband Übergeber mit Gründern zusammenbringen will,und vieles mehr...Viel Spaß beim Hören!***(00:00:00) Intro(00:01:56) Aktuelle Projekte(00:07:29) Familie & Medienpräsenz(00:09:25) Kindheit in Dresden(00:18:17) Studienwahl & Weg nach Berlin(00:20:56) Einstieg bei Zalando(00:23:11) Aufstieg bei Project A(00:28:55) A11: Geschäftsmodell & Namensherkunft(00:34:23) Abgrenzung zu Strategieberatungen(00:37:20) Claim We build Unicorns & Zielkunden(00:39:38) Vergütungsmodell & Tagessätze(00:43:31) PE-Kunden & 100-Tage-Pläne(00:44:43) KI-Reifegrad im Mittelstand(00:50:06) Palantir & europäische Alternative(00:53:17) Belegschaft bei KI-Einführung(00:54:53) Gründung Die Mittelständler(00:59:22) Abgrenzung zu bestehenden Verbänden(01:02:47) Mitglieder des Verbands(01:06:12) Drei Säulen des Verbands(01:12:31) Nachfolge-Matching***Alle Links zur Folge:Kai Hesselmann auf LinkedIn: https://www.linkedin.com/in/kai-hesselmann-dealcircle/CLOSE THE DEAL auf LinkedIn: https://www.linkedin.com/company/closethedeal-podcastThuy-Ngan Trinh auf LinkedIn: https://www.linkedin.com/in/thuyngan-trinh/A11 auf LinkedIn: https://www.linkedin.com/company/a11-global/home/Website CLOSE THE DEAL: https://dealcircle.com/ClosetheDeal/***DUB.de ist Europas führende Plattform für Unternehmensnachfolge. Schaut vorbei, wenn ihr euer Unternehmen schnell, sicher und kostenfrei zum Verkauf inserieren wollt oder als Käufer auf der Suche nach passenden Deals seid:www.dub.de***Du bist M&A-Berater im Small- oder Midcap-Segment und suchst einen Überblick über alle relevanten Deals? Jetzt schnell den

Send us Fan MailLast year, 500 students on 100 teams competed in the Case Competition World Cup. Before they saw the case, coach Divya – 8 years at McKinsey – taught them the first move that separates winning teams from the rest.It's the day 1 answer: a hypothesis you lock in before you have the data, even though it feels premature. But skip it, and teams start boiling the ocean – expanding the question until there's no path left to a real recommendation.This fall, the competition returns with two tracks – undergraduate, presented by Grant Thornton Stax, and graduate, presented by Adobe – co-hosted with Case Questions and Marc Cosentino, author of Case in Point. Any current student can apply – completely free. Application deadline: September 13, 2026.Resources:Undergrad students: apply for the Case Competition World Cup – Undergraduate Track, presented by Grant Thornton StaxGrad students: apply for the Case Competition World Cup – Graduate Track, presented by AdobeLooking for more case competitions? We keep a running list of competitions across the US and internationallyConnect 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

My guest today is Jan Petke, a dynastic architect and strategic consigliere to sovereign and leading global entrepreneur families, who designs continuity architectures so that power, capital, and culture compound across generations — not just portfolios.3:00 — Jan traces his path from a McKinsey-spinoff consultancy through private equity (Commonwealth Bank of Australia's First State Investments) to advising “centi-millionaires” — first-gen tech entrepreneurs with liquidity events over €100 million.5:25 — Jan rejects “advisor” and “wealth manager” as labels: “wealth has nothing to do with money” (6:14).7:35 — The shift from “next generation” to “rising generation,” and from financial capital to human and intellectual capital.11:04 — The “meteor” metaphor: inherited wealth arrives with a weight of responsibility most heirs are unprepared for (12:55).20:43 — On the shirtsleeves proverb: “This proverb is real and serious, because that is physics” — though every family has “free will” over whether it repeats (21:45).25:04 — Jan's own 100 Year Family Project, built with his four children: “my mantra is I eat my own cooking.”32:25 — Declining birth rates and families transforming into institutions.38:53 — New “tribal” dynasties forming around purpose, not bloodline. 2,000–5,000 new dynasties expected within a decade — 40% female-led (41:19).43:51 — Women as an “underestimated” force in the wealth transfer.50:43 — Bringing elders into governance through an “elder council”: “you can't Google wisdom” (54:12).54:51 — The 1,000-year vision — inspired by Hong Kong's Lee Kum Kee family and echoed across scripture.58:42 — Why Jan avoids “legacy” in favor of “lineage impact.”1:03:20 — On success: “if I can inspire someone to do better.”Podcast Program – Disclosure StatementBlue Infinitas Capital, LLC is a registered investment adviser and the opinions expressed by the Firm's employees and podcast guests on this show are their own and do not reflect the opinions of Blue Infinitas Capital, LLC. All statements and opinions expressed are based upon information considered reliable although it should not be relied upon as such. Any statements or opinions are subject to change without notice.Information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. Investments involve risk and, unless otherwise stated, are not guaranteed.

„Nie ma czegoś takiego jak dostatecznie dobre rozwiązanie. Zawsze można lepiej, zawsze można głębiej.” Co się dzieje, gdy z pozycji prezesa w jednej z największych instytucji finansowych świata przechodzisz do organizacji, która działa w tempie startupu i od pierwszego dnia każe kwestionować status quo? 

This week I sat down with Dr Jemma King, and this one is going to change the way you think about sleep forever.Jemma is a behavioural scientist and sleep researcher with a PhD in Human Behaviour, a Research Fellow at The University of Queensland School of Psychology and a specialist external advisor to McKinsey & Company. Her brand new book Sleep First is out now through Wiley.65% of Australians report that poor quality sleep is affecting their focus and wellbeing. Yet despite endless wellness advice, most of us still don't understand what is actually happening in our brains and bodies when we sleep. Irregular sleepers carry roughly a 50% higher all-cause mortality risk than consistent sleepers — not people sleeping less, but people sleeping at different times. There is even a name for the weekly version of this: social jet lag.Jemma is sharp, practical and genuinely one of the best communicators I have spoken to on this show. This one will stick with you.In this episode we cover:Jemma's journey into sleep science and human behaviourWhy 65% of Australians are struggling with poor quality sleepWhy your brain needs to clean itself every nightWhy waking at 3am happens and what your body is trying to tell youHow caffeine, alcohol, screens and late meals disrupt sleep qualityBuilding a personalised sleep formula for energy, focus and recoveryHer new book Sleep First and what's inside itJemma's Book — Sleep FirstJemma's Website https://www.jemmakingbio-pa.com.au/Follow JemmaInstagram https://www.instagram.com/dr.jemma.king/Connect with Cooper Workshop and Speaking Enquiries https://form.typeform.com/to/DSPSnvEH 1% Good Club Book https://booktopia.kh4ffx.net/e1xrkr https://amzn.to/46ve1i2 Instagram https://www.instagram.com/cooperchapman/ TikTok https://www.tiktok.com/@cooperchapman_ LinkedIn https://www.linkedin.com/in/cooper-chapman-08a278151/ The Good Human Factory Instagram https://www.instagram.com/thegoodhumanfactory/ The Good Human Factory https://www.thegoodhumanfactory.com THE GOOD HUMAN FACTORY™️ 2020 Hosted on Acast. See acast.com/privacy for more information.

This week I sat down with Dr Jemma King, and this one is going to change the way you think about sleep forever.Jemma is a behavioural scientist and sleep researcher with a PhD in Human Behaviour, a Research Fellow at The University of Queensland School of Psychology and a specialist external advisor to McKinsey & Company. Her brand new book Sleep First is out now through Wiley.65% of Australians report that poor quality sleep is affecting their focus and wellbeing. Yet despite endless wellness advice, most of us still don't understand what is actually happening in our brains and bodies when we sleep. Irregular sleepers carry roughly a 50% higher all-cause mortality risk than consistent sleepers — not people sleeping less, but people sleeping at different times. There is even a name for the weekly version of this: social jet lag.Jemma is sharp, practical and genuinely one of the best communicators I have spoken to on this show. This one will stick with you.In this episode we cover:Jemma's journey into sleep science and human behaviourWhy 65% of Australians are struggling with poor quality sleepWhy your brain needs to clean itself every nightWhy waking at 3am happens and what your body is trying to tell youHow caffeine, alcohol, screens and late meals disrupt sleep qualityBuilding a personalised sleep formula for energy, focus and recoveryHer new book Sleep First and what's inside itJemma's Book — Sleep FirstJemma's Website https://www.jemmakingbio-pa.com.au/Follow JemmaInstagram https://www.instagram.com/dr.jemma.king/Connect with Cooper Workshop and Speaking Enquiries https://form.typeform.com/to/DSPSnvEH 1% Good Club Book https://booktopia.kh4ffx.net/e1xrkr https://amzn.to/46ve1i2 Instagram https://www.instagram.com/cooperchapman/ TikTok https://www.tiktok.com/@cooperchapman_ LinkedIn https://www.linkedin.com/in/cooper-chapman-08a278151/ The Good Human Factory Instagram https://www.instagram.com/thegoodhumanfactory/ The Good Human Factory https://www.thegoodhumanfactory.com THE GOOD HUMAN FACTORY™️ 2020 Hosted on Acast. See acast.com/privacy for more information.

Send us Fan MailIf your case framework doesn't pass the toothbrush test, it's too generic for McKinsey, Bain, and BCG.Ex-Bain coach Abi Chen walks through the toothbrush test, the 3 mistakes that cost most candidates their offer, and the 4-step process to build strong frameworks.Finally, she walks through two full framework examples – an M&A case and a pharma product launch.Resources:If your frameworks keep failing the toothbrush test, Black Belt is how you fix the processWant to build a framework like this on a real client problem? Apply for the Case Competition World CupConnect 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

700 CEOs have gone through McKinsey's Bower Forum, and the data points to one uncomfortable truth: the best leaders spend less time telling people what to do. Ramesh Srinivasan, McKinsey senior partner, dean of the Bower Forum, and co-author of The Journey of Leadership, joins Ashish Kothari to unpack how top CEOs practice vulnerability in leadership without losing authority and why one of them was told he should fire any leader who says "I have no clue" in a crisis.You'll discover the to-be list that reshapes how you show up in your biggest meetings, the 15-second reframe elite athletes use under pressure, and why feedback you ask for is 10 times more effective than feedback you're given. If you lead people through uncertainty and want psychological safety at work that actually produces results, this conversation is your playbook.What You Will Learn:How to write a daily "to-be list" that decides how you show up in your biggest meetings, not just what you accomplishWhy the best CEOs spend less time telling people what to do and what they do insteadHow to practice vulnerability with judgment: when "we don't know yet" builds trust, and when it should get a leader firedThe "five sources of meaning" that mobilize a whole workforce beyond shareholder valueHow to make feedback ~10x more effective by asking for it first and cascade that habit through your teamHow to metabolize stress with Ramesh's "fear in the backseat" model, so purpose drives and fear keeps only a voiceEpisode Chapters: 04:49 Why leadership begins from the inside out07:44 How leaders can reconnect with their values and purpose09:57 Shareholder value, stakeholders, and the business case for purpose13:16 Moving from constant doing to reflection and “to-be” leadership16:43 Creating the emotional conditions for difficult conversations18:55 What today's uncertainty demands from leaders19:28 Humility, vulnerability, truth-telling, and fearless learning23:29 Building a culture where people can learn from failure27:18 What vulnerability really means for leaders32:38 Making stress an ally rather than a source of burnout37:44 What gives Ramesh hope about the future of leadershipResources:Connect with the GuestLinkedIn: Ramesh SrinivasanRecommended Reading: The Journey of Leadership How CEOs Learn to Lead from the Inside OutConnect with the HostLinkedIn: Ashish KothariWebsite: Happiness SquadBook: Hardwired For HappinessYouTube: Happiness Squad ChannelTEDx: How to make flourishing your competitive edgeIf this conversation sparked something for you, please subscribe and leave a review, it takes 30 seconds and helps more people discover the show.

FAILURE IS AN OPTION: Silicon Valley CEO Mike Grossman Reveals the Truth About SuccessWhat does entrepreneurship really look like when you remove the highlight reel?On this episode of Diversified Game, Kellen Coleman, M.A. sits down with Silicon Valley entrepreneur, six-time CEO, author, and former McKinsey consultant Mike Grossman, author of Failure Is an Option: Reflections of a Silicon Valley CEO.Mike breaks down the side of entrepreneurship people rarely post online: failure, bad timing, mental pressure, investor expectations, legal mistakes, family sacrifice, luck, and the difference between a good process and a good outcome.He shares how one company reached about a $30 million run rate before Congress changed the rules around its business model, while another company facing a disrupted IPO during COVID was unexpectedly acquired for roughly $400 million.The conversation also covers when entrepreneurs should quit or pivot, why “hope isn't a strategy,” how acting as his own lawyer nearly cost Mike millions, why ownership matters, how his wife helped make his entrepreneurial career possible, and why many CEOs struggle privately with mental health.• Control effort and process, not outcomes.• Failure does not automatically mean incompetence.• Know when persistence becomes denial.• Hire experts where your expertise ends.• Ownership and long-term thinking matter.• Entrepreneurship is emotional as well as financial.• Never confuse the Silicon Valley highlight reel with reality.03:01 Mike introduces Failure Is an Option05:51 Outcomes vs. effort07:00 The $400M acquisition10:06 Hope isn't a strategy15:20 Mike's four tests before starting a company27:34 His biggest business mistake34:59 Ownership, debt and long-term wealth38:19 Marriage and entrepreneurship45:59 CEOs and mental health52:50 Focus on what you can controlMike GrossmanBook: Failure Is an Option: Reflections of a Silicon Valley CEOWebsite: https://FailureIsAnOption.comLearn the mindset and moves that lead to real results. Please visit my website to get more information: http://diversifiedgame.com/

The International Risk Podcast with Lucy WarkIn this episode, we explore how artificial intelligence is actually reshaping labour markets, not the headline version where everyone loses their job overnight, but the messier, still-unfolding reality visible in the data so far. We break down what economists mean when they say a job is "exposed" to AI, why that word gets misread as a prediction of job loss, and why the real question isn't whether AI is powerful but whether it's being used to replace workers or make them more productive. From junior employees in software engineering and customer support to freelancers on gig platforms, we look at who is actually losing ground right now, and what career strategies still hold up in a labour market being rewritten in real time.We discuss:Why "AI exposure" doesn't mean what most headlines imply, and the real difference between automation and augmentationWhy we're still in the "first innings" of understanding AI's impact on labour marketsThe five things to track separately: capability, exposure, adoption, economic impact, and people impactWhy adoption of AI tools is "a puddle, not an ocean," despite near-universal awarenessWhy AI's economic impact is still barely visible in GDP, productivity, and wage statisticsThe "canaries in the coal mine": emerging evidence that junior workers in AI-exposed fields are already losing employment"Seniorization" — why entry-level roles increasingly expect mid-level outputEarly signs of decline in freelance marketplaces, and why freelancers may be hit firstWhich career strategies, like corporate ladder-climbing and credentialism, no longer hold upWhat's replacing them: platform building, proximity, and leverageWhat AI is doing to critical thinking, and how educators are respondingHow Lucy Wark uses AI in her own research and writing process, and where she still insists on doing the work herselfAbout the guest: Lucy Wark is a former McKinsey consultant and serial entrepreneur, co-founder of career-skills company Fuzzy and sexual wellness brand Normal. She writes the Substack series How Not To Lose Your Job, which examines the evidence behind AI's impact on labour markets and recommends career strategies for building an AI-resilient career. She studied Politics, Psychology and Sociology at Cambridge and Social Science at the University of Chicago. In this conversation, Lucy draws on labour market research and her own experience coaching career strategy to break down what's actually happening in the data, and what individuals should do about it.Lucy's Substack: https://lucywark.substack.com/About the host: Dominic Bowen is Head of Strategic Advisory and Partner at one of Europe's leading risk management consulting firms. He advises CEOs, boards, and senior executives on crisis management, geopolitical risk, operational resilience, and strategy, drawing on decades of experience across government, humanitarian operations, and corporate leadership.

Barry Rosen has spent decades at Interaction Associates, a firm he joined in 1984 after being drawn to their focus on making meetings more effective. He began his career training teams at Ford, Dow, and DuPont during the early era of quality initiatives, teaching engineers and project managers how to facilitate meetings and navigate interpersonal dynamics. He went on to lead the training division at Interaction Associates for a decade, building out programs in facilitative leadership. Over the years he has trained consultants at firms including McKinsey, Bain, and PricewaterhouseCoopers, helping highly analytical professionals strengthen the human side of their work. His current focus is Essential Facilitation for Project Managers, a program built around the growing number of project managers seeking these skills. What You Will Learn Listeners will hear why facilitation is a teachable skill rather than an innate trait, and how it applies directly to running better meetings and better projects. Barry explains the three dimensions every skilled facilitator manages: results, process, and relationship. He and Michael discuss how artificial intelligence is changing the analytical side of project work while making the human and emotional side more important than ever. The conversation covers why so many AI initiatives stall, often because teams never clarified their outcomes or ownership before deploying the technology. Barry also walks through how project managers are evolving into process consultants who understand stakeholder needs, build agreements, and guide teams through structured problem solving rather than jumping straight to solutions. Episode Highlights Barry traces his path from joining Interaction Associates in 1984 to training engineering teams at Ford, Dow, and DuPont during the early push for quality and consensus based collaboration in American manufacturing. He describes the moment facilitation and collaborative leadership merged into a single discipline, and how that shift fueled a decade of growth in his training programs. Michael shares a personal story about a healthcare clinic project that had to be rebuilt in six weeks after a change in scope, illustrating how communication gaps derail even well managed projects. Barry connects this to his concept of collaborative intelligence, the ability to build agreements and reach outcomes that work for a group rather than any single person. The discussion turns to AI agents joining meetings as active participants, with Barry predicting this will become a normal part of how project teams operate. He closes by describing the upcoming Essential Facilitation for Project Managers program, set to launch in September. Guest Contact Information Barry Rosen, Interaction Associates Upcoming webinars and programs: https://interactionassociates.com/events Call to Action If this conversation on facilitation and collaborative leadership resonated with you, visit https://www.breakfastleadership.com/leadershipos to schedule your Leadership Diagnostic and find out where your organization's coordination gaps really are. More from Barry Rosen: https://www.interactionassociates.com/resources/blog/author/barry-rosen

In this episode of Ikigai with Jennifer Shinkai, Jennifer sits down with her longtime friend and colleague Helen Iwata, a bilingual leadership and communications coach with over 35 years of experience in Japan. Helen opens up about the difficult seasons she has navigated in both her business and personal life, including a significant financial setback after working with a business coach that shook her confidence deeply. She shares her journey through bitterness, self-blame, and the slow, gradual process of finding her way back to joy. Helen and Jennifer explore the concept of "divine timing," the power of patience, and the importance of sitting with difficult emotions rather than bypassing them. They also discuss Helen's evolving professional identity, the philosophy of "less effort, more impact," the concept of mottainai as it applies to talent and energy, and the 10th anniversary of Helen's book Eigo no Shigoto Jutsu. The conversation is honest, warm, and deeply relatable for anyone navigating a season of transition.If you enjoyed this episode and it inspired you in some way, we'd love to hear about it and know your biggest takeaway.In this episode you'll hear:How Helen lost her sense of joy during a difficult few years and how she is finding her way backWhy taking 100% responsibility is so hard, and why it matters more than playing the victimHelen's philosophy of "less effort, more impact" and how it applies to leadership and communicationThe concept of mottainai applied to talent, energy, and unsolicited adviceWhy action brings clarity, and why you can't do what you don't know if you keep doing what you do knowThe 10th anniversary of Helen's book Eigo no Shigoto Jutsu and her new podcast and YouTube seriesAbout Helen:Helen Iwata is a bilingual leadership and communication coach from the UK with over 35 years' experience in Japan, helping managers and executives in Japan—especially women—lead and communicate confidently in global business settings.During her 10 years with McKinsey & Company, she served as Manager of Client Communications, coaching consultants and clients in leadership, communication, and high-stakes presentations.As the founder of Sasuga Communications K. K., she partners with multinational organizations to design and deliver leadership and communication development programs for rising leaders through to seasoned executives across the APAC region.Helen is a TEDx coach and speaker, Nikkei Online columnist, author of Eigo no Shigoto-jutsu (Shogakukan), host of the Sasuga! Podcast, and serves on the Executive Committee of the British Chamber of Commerce in Japan.She is also a wife, mother, and karate world champion.6 Weeks To Clear, Confident Communication For Women In BusinessHelen has launched a new program to help women managers and executives in Japan to speak more clearly and confidently in global business settings, so they can create greater impact through their work while staying true to themselves.Learn more: sasugacommunications.com/interestConnect with Helen:Sasuga Communications: https://sasugacommunications.com/LinkedIn: https://www.linkedin.com/in/heleniwata/Instagram: https://www.instagram.com/heleniwata/YouTube: https://www.youtube.com/@HelenIwataConnect with Jennifer:Linked In: https://www.linkedin.com/in/jennifershinkai/Facebook: https://www.facebook.com/jennifershinkaicoachWebsite: https://jennifershinkai.com/ Instagram Coaching and Podcast: https://www.instagram.com/ikigaiwithjennifershinkai/Instagram Artist: https://www.instagram.com/jennifershinkai/YouTube: https://www.youtube.com/c/ikigaiwithjennifershinkai/Things mentioned in this episode:Eigo no Shigoto Jutsu by Helen Iwatahttps://www.amazon.co.jp/%E8%8B%B1%E8%AA%9E%E3%81%AE%E4%BB%95%E4%BA%8B%E8%A1%93-%E3%82%B0%E3%83%AD%E3%83%BC%E3%83%90%E3%83%AB%E3%83%BB%E3%83%93%E3%82%B8%E3%83%8D%E3%82%B9%E3%81%AE%E3%82%B3%E3%83%9F%E3%83%A5%E3%83%8B%E3%82%B1%E3%83%BC%E3%82%B7%E3%83%A7%E3%83%B3-%E5%B2%A9%E7%94%B0-%E3%83%98%E3%83%AC%E3%83%B3/dp/4093884560Sasuga Podcasthttps://sasugacommunications.com/category/podcast/Jim Fortin's programhttps://www.jimfortin.com/jims-products/

There is a woman holding an entire family together with her own body, and everybody is calling it love.On the surface nothing is wrong. The family is close. Everyone gets on. But she is tired in a way sleep doesn't touch, she gets sick, she burns out — and underneath all of it, unseen and unintended by anyone, she is being eaten from.In this episode Jess draws the line between the two ways a woman can hold money: the servant and the steward.The servant is Cinderella. She brings in the resource and everyone else goes to the ball on her energy. She has to keep showing up, keep producing, keep pouring in — because the moment she stops, the story she's built collapses. And the ones feeding from her don't thrive either. They're eating from a rotten core.The steward is the matriarch. Whatever comes in, she grows. She builds structures that hold without her, so what everyone eats from isn't her body. She gets stronger, and so does everyone around her.None of this shows up in the personality. Nobody is being cruel on purpose. This is soul contract territory, running quietly underneath the loveliest families in the world — which is exactly why women miss it until something breaks.Jess also goes into why extraction happens to women who aren't earning at all, the McKinsey restructure day that taught her what taking a leadership position does to fear, the animus as the source of matriarchal strength, and her own childhood of three pairs of jeans and cushions instead of a sofa — and what a mother's refusal to want costs everybody around her.Because a woman's desire is not greed. It's the thing her whole family gets to live inside.Servant or steward — same family, same personalities, completely different energeticsCinderella and the ugly sisters: extraction dressed up as a loving homeWhy everyone feeding from a servant eventually suffers tooBurnout, sickness, depression and anxiety as signals of where you're being extracted fromSoul contracts inside families that look perfect from the outsideThe Titanic lifeboat: why leaders self-select, and what happens when they doThe McKinsey testing day — stepping into leadership and the archetypal field it opensFeminine leadership vs bossiness, and why one of them worksThe animus as the matriarch: the inner masculine as source of strengthThe woman receiving tens of thousands a month who was still a servant — and still sickWomen in their nineties who are still glowing, and what's standing behind themThree pairs of jeans, no sofa, and a mother who didn't want moreDesire as inheritance: everyone eats from what a woman allows herself to wantWhy stewards become generous and the extracted-from hoardThe nine-to-five as the purest servant contract there is-----------------------------------------------------The VesselThe servant has to keep pouring. That's the whole problem — the money comes out of her body, every day, forever, and it stops the moment she does.The steward builds something else. A structure that receives what she loves and keeps paying whether she's in full flow or resting. And then a second vessel behind that one, where a portion of everything that comes in is set aside and left to compound in the dark, so that after ten years — even seven — she can stop contributing entirely and be paid for the rest of her life.That is what The Vessel is. A year of live, personal work building a membership around the thing you'd talk about all day anyway, shaped to your Gene Keys and Human Design rather than someone else's curriculum. Built so it holds without you. Built, if you ever want it, to be sold.The oil was never the problem. The vessels were.→ spiritualised-the-vessel.netlify.app or write to Jess directly: jess@goinward.co.uk

Episode Summary Employee engagement and mental health are often treated as separate line items on an HR dashboard, but they are actually two sides of the same coin. With global engagement falling to just one in five employees and stress levels rising, CEOs must recognize that disengagement is frequently a symptom of unaddressed psychological strain. In this episode, we dive into why traditional "wellness perks" aren't enough and how structural changes—from manager workload to AI deployment—are the real keys to a high-performing, healthy workforce.   Key Topics Discussed The Hidden Link Between Engagement and Mental Health: Why disengagement is often a symptom of chronic stress rather than a lack of motivation. The Manager Factor: How manager burnout and excessive "span of control" (more than 10-12 direct reports) act as a systems failure that erodes team health. Psychological Safety as a Foundation: Drawing on Harvard Business School research, we discuss why interpersonal risk-taking is the strongest predictor of both engagement and well-being. The "AI Factor": How deploying AI without clear communication about job security and new skill paths creates deep-seated anxiety and trust issues. Leadership and AI Deployment: Insights into Michael Levitt's approach to a "LeadershipOS," where technology change management is treated as a mental health intervention. Moving the Needle: Why organizations that pair mental health investment with structural changes like flexible scheduling and manageable workloads see significantly higher retention. Actionable Insights for CEOs Audit Manager Workload: Treat manager capacity like a production line; reduce the number of direct reports and give them the authority to adjust workloads without red tape. Cross-Reference Your Data: Pull your engagement surveys and layer them over absenteeism and turnover data to find exactly where your organization needs the most help Structural Safety: Build psychological safety by rewarding managers who surface problems early and creating forums where employees can raise concerns safely. The 90-Day Pilot: Commit to one structural change—whether it's a new AI communication protocol or reducing span of control—with a designated owner and a clear measurement data Resources Mentioned 3 Ways To Boost Employee Engagement In Your Workplace 6 Ways To Embrace Mental Health In Your Company Employee Retention: Calculating The True Costs Of Burnout And Turnover Research References: Gallup State of the Global Workplace, SHRM Workplace Research, and McKinsey workforce data https://BreakfastLeadership.com/

Send us Fan MailBates White let us inside a real economic consulting case interview.Annie Olecki, a senior consultant in Bates White's antitrust practice, ran a live case interview with a volunteer from the MC community. And economic consulting cases don't look like the strategy cases at McKinsey or Bain.The case: a phone manufacturer suing its battery suppliers for price-fixing. The candidate has to size the damages, then revise the number - twice - as new evidence shifts the picture.That's the instinct Bates White is testing for. Annie wanted to see if the candidate would revise the estimate once new information proved it wrong.After the case wraps, Annie and Bates White recruiter Julian Pritcher take audience questions - interview rounds, what stands out in a resume, and R vs. Python.Join Bates White:Bates White's summer consultant program is open for applications. If you're an undergrad rising junior graduating Dec. 2027 through spring 2028, apply hereNot that class year? Bates White keeps a running list of openings. Submit your resume and cover letter and the firm will reach out if a role fitsGo deeper on Bates White – our full firm profileResources:Join the Black Belt program to build killer case instincts like KunalCase Competition World Cup – Fall 2026Applications are open. Free for all students. Apply by Sept. 13.Graduate Track – Presented by AdobeConnect 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

Employers could wind up in court if they outright dismiss workers who request a faith-based exemption from using AI. In a businessinsider.com article, Ashley Herd, a former McKinsey counsel and head of North American HR, emphasized this newer risk for businesses.  According to the article, one Unitarian Universalist has already received a religious exemption from her employer because of her ... The post Religious Exemptions for AI? appeared first on Unconventional Business Network.

We featured a special keynote from Walker & Dunlop's Summer Conference with Aditya Sanghvi, Senior Partner at McKinsey & Company and leader of the firm's global real estate practice. Aditya cut through the AI hype to explain what today's breakthroughs actually mean for real estate. Drawing on McKinsey's work with leading organizations, he explored why so few companies are realizing meaningful value from AI, how "agentic AI" is transforming everything from leasing and maintenance to investment decisions, and why data—not technology—will be the defining competitive advantage. He also shared why this is ultimately a CEO-led transformation and what business leaders should do today to stay ahead. Learn more about your ad choices. Visit megaphone.fm/adchoices

As we continue to work on some new episodes for you, please enjoy this episode from June featuring Sami Inkinen, the co-founder and CEO of Virta Health.Summary:The medical establishment spent decades telling patients that type 2 diabetes is a chronic and irreversible disease. Today's guest decided to prove them wrong.Sami Inkinen is the co-founder and CEO of Virta Health, a company using a combination of nutrition science, remote monitoring technology, and individualized coaching to help patients reverse type 2 diabetes, obesity and other metabolic conditions.  Previously, Sami co-founded Trulia, the online real estate marketplace, serving as COO and president through its IPO and eventual sale to Zillow. He has also held roles at Microsoft and McKinsey, and rowed from California to Hawaii with his wife to raise awareness of the dangers of sugar.Sami joins us to talk about how his own health journey influenced his decision to start Virta, the challenges of scaling in the health space, and the incredible success they've had in treating metabolic disease. Highlights:A personal pre-diabetes diagnosis (2:35)Lessons from Trulia (6:00)Why reversal, not management (9:30)Clinical results and outcomes (12:47)GLP-1s and Virta's approach (15:26)Technology and personalization (17:33)Selling to employers (20:17) Overcoming the status quo (22:33)Building a full-stack team (25:15)Rowing California to Hawaii (28:30)Goals for ‘26 into ‘27 (30:58)Links:Sami Inkinen LinkedInVirta Health LinkedInVirta Health WebsiteICR LinkedInICR TwitterICR Website Feedback:If you have questions about the show, or have a topic in mind you'd like discussed in future episodes, email our producer, joe@lowerstreet.co

"The biggest risk today is not making the wrong AI decision. It is making no decision at all while everyone else is learning." Samir Khushalani, Senior Advisor, Art of Procurement Procurement leaders now face more technology choices than ever, with new AI-enabled solutions emerging constantly. In this environment, picking the right tools can be overwhelming, and procurement often struggles with knowing where to start, how to avoid analysis paralysis, and ensuring their tech choices drive real business outcomes.  In this episode, Philip Ideson speaks with Samir Khushalani, Art of Procurement Senior Advisor and a former McKinsey digital procurement leader. Samir has guided Fortune 500 companies and is helping to shape the ProcureTech100, the industry's top guide to procurement technology. He breaks down how to navigate a fragmented market, balance risk and urgency, and scale impact without getting stuck in "pilot purgatory."  In this episode, Samir covers how to:   -Take practical steps to avoid technology indecision   -Identify true AI-native solutions versus "AI-wrapped" legacy tools   -Partner with providers who aim for business impact, not just automation   -Build a flexible procurement tech stack for lasting competitiveness  Links: Samir Khushalani on LinkedIn: https://www.linkedin.com/in/samirkhushalani/  Art of Procurement Welcomes Samir Khushalani as Senior Advisor: https://artofprocurement.com/blog/blog-art-of-procurement-welcomes-samir-khushalani-as-senior-advisor  Download the 2025-26 ProcureTech100 Yearbook: https://artofprocurement.com/procuretech100-2026  Subscribe to the AOP Newsletter: https://resources.artofprocurement.com/art-of-procurement-podcast-subscribe  Subscribe to Art of Procurement on YouTube: https://www.youtube.com/@ArtofProcurement   

Send us Fan MailMost 2nd-year MBA candidates have 2 to 4 weeks to get case interview-ready this cycle, not the usual 6 to 8.More cases won't close that gap for McKinsey, Bain, and BCG.Former Bain interviewer and LBS MBA Mitali Jalan compressed her prep into under 4 weeks and landed her offer. This session is her plan for doing it on a short runway.The fix isn't more volume. It's knowing what to drill, and when. Listen for:Mitali's 4-step sequence for compressing 6 to 8 weeks of prep into 2 to 4Why 30 cases with a partner can still hide the mistake that costs an offerBusiness acumen: the one skill interviewers spot instantly, and most candidates never buildResources:Black Belt pairs you with a coach who catches what a case partner can't – 80% land at least one offerConsulting Deadlines:McKinsey, Bain, and BCG deadlines hit August 11 – 13 (and more are coming) – get interview-ready fast with Black BeltConnect 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

In this episode of the Programmatic Digest, Hélène Parker sits down with Dr. Augustine Fou, founder of Fou Analytics, to unpack the realities of ad fraud, attribution, AI, and programmatic optimization. Dr. Fou challenges some of the metrics and tools our industry has relied on for years, explaining how bots can manipulate signals like CTR and how algorithms can unintentionally optimize toward fraudulent inventory. The conversation also explores the limitations of traditional fraud detection, the importance of independent verification, and how traders can use more granular data, including placements and Seller IDs, to better understand where their budgets are actually going. At the heart of the conversation is a simple question: Are we optimizing for metrics, or are we optimizing for real business outcomes? Key Takeaways Question vanity metrics: High CTR and other engagement metrics don't always mean better campaign performance. AI is only as good as its signals: If algorithms optimize toward manipulated metrics, they can unintentionally send more budget toward fraudulent inventory. Look beyond standard fraud reports: Fraud percentages only reflect what verification technology is able to detect. Audit your placements: Regularly review where your ads are running and whether those environments make sense for your audience. Pay attention to Seller IDs: Seller-level data can provide another layer of transparency when evaluating programmatic supply. Consider independent verification: Post-bid data can help validate what actually happened after an impression was served. Quality matters more than volume: Fewer, higher-quality impressions reaching real humans can be more valuable than maximizing cheap reach. Keep the human in the loop: Automation can make traders more efficient, but critical thinking, QA, and active optimization remain essential. Optimize toward business outcomes: Ultimately, campaign success should connect back to real results, not just what looks good in a DSP report.   About Us: We help historically excluded individuals break into programmatic media buying and land jobs they love. Through our Reach and Frequency® program, coaching, and community, we make learning programmatic clear, practical, and welcoming. Join once, stay learning forever. Past workshops, paid gems, and every new recording + resource added as we go. This library isn't a one-time thing, it's the Foull vault plus all Fouture trainings, recordings, and guides. Access it here: https://www.heleneparker.com/library

Guest Full Name: Dr. David-Alexandre (“DA”) C. Gros, MD CEODA's Bio:Dr. Gros has served as Chief Executive Officer and a member of the Board of Directors of Eledon Pharmaceuticals, Inc. since September 2020. He joined Eledon Pharmaceuticals from Imbria Pharmaceuticals Inc., where he served as Co-Founder, Chief Executive Officer and Chairman of the Board of Directors. Prior to Imbria, Dr. Gros was President and Chief Operating Officer of Neurocrine Biosciences, Inc., Chief Business and Principal Financial Officer of Alnylam Pharmaceuticals, Inc., and Chief Strategy Officer of Sanofi, S.A. Before joining Sanofi, Dr. Gros held leadership positions in healthcare investment banking at Centerview Partners, LLC, and Merrill Lynch, Pierce, Fenner & Smith Inc., and in healthcare consulting at McKinsey & Company. He previously served on the Board of Directors of Eliem Therapeutics, Inc., a biotechnology company which he co-founded, and is currently the Executive Chairman of Saint Jean Groupe, S.A., a leading French manufacturer of pasta products since 1935.Dr. Gros earned his Doctor of Medicine from The Johns Hopkins University School of Medicine, a Master of Business Administration from Harvard Business School, and a Bachelor of Arts from Dartmouth College.Company: Eledon Pharmaceuticals, Inc.Ticker: ELDNWebsite: https://eledon.com/About the Company:Eledon Pharmaceuticals, Inc. is a clinical stage biotechnology company that is developing immune-modulating therapies for the management and treatment of life-threatening conditions. The Company's lead investigational product is tegoprubart, an anti-CD40L antibody with high affinity for the CD40 Ligand, a well-validated biological target that has broad therapeutic potential. The central role of CD40L signaling in both adaptive and innate immune cell activation and function positions it as an attractive target for non-lymphocyte depleting, immunomodulatory therapeutic intervention. The Company is building upon a deep historical knowledge of anti-CD40 Ligand biology to conduct preclinical and clinical studies in kidney allograft transplantation, xenotransplantation, islet cell transplantation, and amyotrophic lateral sclerosis (ALS). Eledon is headquartered in Irvine, California.

“It was the most fun role I think I'll ever do”. How do visionary founders build teams to protect their time for big ideas? Katie Cirulli (Chief Emerging Brands Officer & fmr. President, Grüns) joins Connor Rolain (Head of Growth, HexClad) and Cody Plofker (Advisor & fmr. CEO, Jones Road). She joined Grüns as employee four and rose from Chief of Staff to her current role. Before that, she spent years at McKinsey and Meta. She explains why founders need integrators, and how AI powers Grüns. She walks through the chief of staff role she built with Chad Janis. The CPM arbitrage test was an early swing that never scaled, unlike the LTO strategy that followed. Grüns now runs five emerging brands through dedicated marketing pods. Paid media, creative, and CRO, all guided by the same paper wall mindset. Powered By Motion https://9ops.co/motion-runneth Haus https://www.haus.io/operators NeonPixel https://9ops.co/neonpixel Richpanel https://9ops.co/richpanel-mops Proppel https://9ops.co/weareproppel Aftersell https://9ops.co/aftersell-mops Operators Newsletter https://9operators.com/ 

Show Notes Clare Scherrer outlines her career journey in three main chapters: 25 years at Goldman Sachs in Investment Banking, a number of years as a public company Chief Financial Officer, and her current role as a director on two public company boards of directors. Clare also shares her life immediately post-graduation, including getting married and completing McKinsey's Business Analyst program in New York City. Love at First Blind Date Clare recounts her initial post Harvard plan to join the Foreign Service and how a blind date led to her getting engaged and pivoting her career path. She describes the decisive nature of her engagement and how it shaped her life and career.   McKinsey, HBS, & the Pivot to Investment Banking Clare reflects on her years at McKinsey, emphasizing the importance of critical thinking and learning from her engagement managers. She also explains how her experience at McKinsey influenced her pivot to investment banking during her time at Harvard Business School. Relationship Building in Investment Banking Clare details her summer internship at Goldman Sachs and how it led to a 25-year career at the firm. She highlights the various roles she held at Goldman Sachs, including managing client relationships, co-leading a global team, and co-chairing the IPO committee.  Clare discusses the skills that contributed to her success, including work ethic, critical thinking, and building trust. She emphasizes the importance of running toward problems and the value of trust in client and colleague relationships. Clare shares her approach to communication, stressing the need for over-communication and the importance of truly understanding how critical business decisions are influenced and taken.   Becoming CFO of Smiths Group Clare recounts how a long time client approached her about the opportunity to become the CFO of Smiths Group, a global engineering company. She initially hesitated but was encouraged by her husband to embrace the opportunity. Clare describes the company's products and services when she was CFO; including energy efficiency, safety, and connectivity solutions. She highlights how much she valued the experience of being both the CFO and a board member, which gave her a deeper understanding of the importance of public company governance. Pursuing a Portfolio of Board Directorships Clare explains her decision to pursue a portfolio of board directorships after her tenure as CFO.  She currently serves on the boards of Legrand, a leading electrical and digital infrastructure company; and Shell, an integrated energy company. Clare also discusses that she sets aside some time to coach next generation finance executives in the US, drawing parallels to her experience developing talent at Goldman Sachs. She emphasizes the importance of developing and retaining talent, even outside of a full-time executive role. Returning to the U.S. Clare describes her typical work week, including the imperative to stay current on relevant financial markets, industry, and company developments. She also shares her current plans to move back to the U.S. after 15 years in London. Clare also reflects on the importance of consciously investing in personal growth and adopting habits that challenge as well as encourage reflection.   Harvard Reflections Clare recalls her most challenging course at Harvard, which was Russian, and how rewarding the class and learning process was, despite it not being directly linked to her career pursuits after Harvard. Clare also shares how energizing she finds her weekly tennis match. She encourages others to find a pursuit outside of work that is energizing and allows you to laugh at yourself and with others. Timestamps: 04:02: First Date and Early Career Decisions 07:03: McKinsey, HBS, & the Pivot to Investment Banking 13:38: Relationship Building in Investment Banking 19:39: Transition to CFO Role 26:06: Board Membership and Coaching 28:45: Personal Growth 36:25: Most Memorable Course and Personal Interests Links: LinkedIn: https://www.linkedin.com/in/clare-scherrer-651396b1/   *AI generated transcript and show notes.    

Send us Fan MailMcKinsey screens candidates with a video game – McKinsey Solve – before they ever see a case interview. Most candidates either try to copy other people's answers or panic because they don't know what it's measuring.So here's the breakdown: what Solve is, what McKinsey is testing for inside it, and how to approach it.The answer isn't Solve-specific prep. It's the same problem-solving fundamentals that carry you through the entire McKinsey recruiting process.We cover:What the Solve scenarios look like and how the timing worksThe 5 cognitive abilities McKinsey is measuring – and why they map directly to what consultants actually doHow to prepare without wasting time on things that won't transferResources:If you want coaching from an ex-McKinsey interviewer – plus access to a practice Solve simulation – Black Belt is the program that top candidates turn toNew to case prep? Start with the Case Foundations course – freeConsulting Deadlines:McKinsey, Bain, and BCG deadlines hit August 11 – 13 (and more are coming) – get interview-ready fast with Black BeltConnect 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

In this episode of Trending in Education, host Mike Palmer sits down with Mike Peng, Founder and Managing Partner of Weatherstone Capital Partners, to explore the evolving intersection of education, technology, and capital markets. After missing a meeting at ASU+GSV in San Diego, Mike and Mike reconnect to unpack what it takes to scale educational ventures past the startup phase and navigate the broader macroeconomic shift from venture capital to private equity in EdTech. Drawing from his unique career journey—from engineering at UT Austin and strategy consulting at McKinsey to leading rapid growth at Block Renovation and earning an MBA at Stanford—Peng shares why Weatherstone focuses on partnering with operators in the 1-to-10 scale stage ($1M to $10M EBITDA range). Together, they examine the real "moats" in the age of AI (data ownership and customer relationships over UI), why corporate L&D and continuing certification are outperforming traditional K-12/Higher Ed models for private equity, and how simulation tools and micro-learning are reshaping workforce upskilling. Peng also offers vital advice for founders assessing whether they are the "limiting factor" in their company's growth and how to navigate tight capital markets. KEY INSIGHTS: 0-to-1 vs. 1-to-10 Leadership: Building a product from scratch requires a scrappy, zero-to-one mindset, whereas scaling from 1 to 10 demands processes, enterprise workflows, and founders willing to look in the mirror to ensure they aren't becoming their company's limiting factor. The Capital Shift from VC to PE: With EdTech valuations down ~60% from 2021 peaks and market maturity kicking in, 2024 marked a pivot where private equity outpaced venture capital in EdTech funding—shifting the focus from hyper-growth to unit economics, profitability, and sustainable scale. Redefining AI Moats: User interface (UI) and simple API connections to large language models are no longer defensible differentiators. True AI moats reside in owning proprietary data, maintaining deep customer trust, and controlling end-to-end customer relationships. Corporate L&D and Reskilling Demand: While K-12 and Higher Ed present longer sales cycles and risk aversion, Corporate L&D—particularly recurring certification, micro-training in daily workflows, and AI simulation (e.g., bedside manner nursing)—presents massive opportunity as 85% of employers seek to reskill their workforce by 2030. Founder Discipline in Tight Markets: Bootstrapping and pivoting quickly are more viable than ever thanks to AI MVP acceleration. Founders must plan capital runway at least a year in advance and regularly "come up for air" so market evolution doesn't leave their business behind. TIMESTAMPS: 00:00 – Introduction & Connecting Post-ASU+GSV 01:00 – Mike Peng's Journey: UT Austin, McKinsey, Block Renovation, & Stanford MBA 02:30 – Inside Weatherstone Capital Partners: Long-Term Platform Investing 03:30 – 0-to-1 vs. 1-to-10: Passing the Founder "Mirror Test" 05:30 – Takeaways from ASU+GSV: AI Undercurrents & Modern Moats 07:30 – Career Readiness, CTE, & The 1,400-Tool EdTech Stack 09:30 – Data is the New Oil, AI is the New Electricity 11:30 – Managing Hallucination Risk & Trust in Classroom Tech 13:30 – Segmenting EdTech: Why Capital is Moving from VC to PE 18:00 – The Future of Work: LXP, Micro-Learning, & AI Simulations 23:30 – Personal AI Tutors, Spatial Hardware, & Final Advice for Founders 26:00 – Wrap Up & How to Connect with Weatherstone Subscribe to Trending in Ed wherever you get your podcasts to stay ahead of the curve in learning, media, and the future of work.

Rajiv Parikh talks with Andrew D'Souza about building Boardy, an AI superconnector that scales warm introductions while protecting its own reputation and the network's goodwill. We dig into why Boardy rejects SaaS norms, how the team trains an autonomous AI to say no, and what it takes to hire imaginative builders for an AI-native company.Boardy.ai: https://www.boardy.ai/• why reputation-weighted introductions beat open messaging• how Boardy works through phone calls, WhatsApp, and email instead of dashboards• using the film Her as a model for shared AI presence• go-to-market lessons from cold start growth and a crafted personality• training Boardy to preserve goodwill and push back on bad asks• combining ML engineers with character design to make the persona feel real• hiring framework focused on imagination, agency, and ambiguous problem solving• monetization paths through Boardy Pro and deeper funnel support beyond intros• managing disagreement when an autonomous AI brings data-backed recommendationsYour next breakthrough might be one introduction away, but most networking platforms confuse access with trust. We sit down with Andrew D'Souza, founder and CEO of Boardy, to unpack what it looks like to build an AI superconnector that behaves less like software and more like a principled relationship driven matchmaker. Boardy operates through live phone calls, WhatsApp, and email, making double opt-in warm introductions across a massive professional network while putting its own reputation on the line.We get specific on product design and go-to-market: why Andrew rejects the usual SaaS playbook, why he thinks the “agentic AI” label misses the point, and how the movie Her helped shape a shared AI that can be deeply present with thousands of people at once. From the cold start grind of getting the first 1,000 users to the craft of an Australian-accented persona, this conversation breaks down what actually creates adoption when the interface is simply a conversation.Then we dig into the hard problem: network goodwill. Andrew explains how Boardy learns to say no without alienating users, how it reasons about mutually beneficial outcomes, and how Boardy Pro pushes beyond introductions into real follow-through like scheduling, prep, and closing the loop. We also talk hiring for imagination over pedigree, treating AI like a teammate in standups, and what a symbiotic future with “a new species” could require from all of us. Subscribe, share this with a builder who cares about real connection, and leave a review so more founders can find the show.Andrew D'Souza: https://www.linkedin.com/in/andrewdsouza/Andrew D'Souza, the Founder and CEO of Boardy, an AI "super-connector" which recently raised its own $8 million seed round through autonomous pitching and even launched its own AI-led venture fund, Boardy Ventures.  A serial entrepreneur, Andrew is perhaps best known as the former Co-Founder and CEO of the fintech unicorn Clearco. Before building his own unicorn, he served as the COO and CRO of Top Hat, President of Nymi, and an advisor to major tech players like Wealthsimple and Kik.  Born in India before moving to Chicago and eventually the Toronto area, Andrew began his career as a Business Analyst at McKinsey & Company after earning his degree in Systems Design Engineering from the University of Waterloo. #ai #professionalgrowth #networking #entrepreneur #growth #sales #technology #innovatorsmindset #innovator #product #revenue #revenuegrowth #management  #founder #entrepreneurship #company #process #processimprovement #value #valuecreationWebsite: https://www.position2.com/podcast/Rajiv Parikh: https://www.linkedin.com/in/rajivparikh/Email us with any feedback for the show: sparkofages.podcast@position2.com

In this episode of The Confidence Doc®, host Dr. Vinaya Rednam sits down with Dr. Sarah Rav; a former medical doctor turned McKinsey consultant, personal branding strategist, and entrepreneur . Together, they break down the heavy expectation high achievers face when walking away from prestigious titles and why changing your mind isn't a failure, but an evolution . Dr. Sarah Rav opens up about her transition out of medicine in Australia, how she navigated burnout and grief, and how she combined her medical background with content creation to build a thriving business helping physicians build their professional reputation online . In this episode, they discuss: The unique psychological challenge of walking away from a medical degree and title Dr. Sarah Rav's journey: From graduating med school at 23 to McKinsey and full-time entrepreneurship How physicians can navigate the fear of appearing "unprofessional" on social media Why patients value storytelling and human connection over clinical lectures How introverted physicians can build confidence and take control of their online visibility ⏱ CHAPTERS 00:00 – Teaser & Episode Intro: Changing Your Mind as a High Achiever 01:25 – Early Aspirations: Doctor, Astronaut, or Hairdresser? 02:47 – How the Medical School System Works in Australia 03:31 – The "Glass Shattering" Moment in Medical School 05:12 – Early Side Hustles: Ebooks, Health Supplements, & Tutoring 06:18 – Transitioning to McKinsey: Trading One Prestige for Another 08:04 – Overcoming Burnout, Personal Loss, & Taking the Entrepreneurial Leap 09:19 – Uncoupling Your Identity from Being a Doctor 12:12 – No Experience Is Wasted: Creating a Personal Branding Niche for Doctors 13:03 – Facing Hospital Pushback & Social Media Stigma 14:16 – Combating Medical Misinformation & Evolving Patient Expectations 17:07 – Using Storytelling Over Lecturing to Connect with Patients 20:16 – Personal Branding for Introverted Physicians 21:07 – Gender Dynamics in Medicine & Social Media Commentary 24:26 – Behind the Scenes: The Public Duality of an Online Brand 27:32 – Building the Muscle of Visibility & Self-Confidence 28:48 – How to Connect with Dr. Sarah Rav & Final Thoughts

Send us Fan MailGeorge Cary spent five years as a McKinsey EM. In this live case, he coaches candidate Harvey through a real McKinsey market entry study: should a diesel truck manufacturer build and sell electric trucks.Harvey builds a framework, runs the full cost-of-ownership math, and lands a final recommendation. George pauses after every section to break down good vs. great in real time.You'll learn:Why McKinsey calls it "problem solving," not casing – and the vocabulary that signals you already think like a consultantHow Harvey turns a good, structured framework into a great, distinctive one The full math behind pricing an e-truck – and how to talk through your logic instead of just stating the numberResources:Harvey turned 3 weeks of coaching into a case that sounded ready for the real thing – Black Belt pairs you with a coach like George who breaks down your good from your great, session by sessionConsulting Deadlines:McKinsey, Bain, and BCG deadlines hit August 11 – 13 (and more are coming) – get interview-ready fast with Black BeltConnect 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

Send us Fan MailSharon had everything going for her. Top-tier MBA. MBB interview invites across the board. She'd done 50–60 cases – but didn't make it past a single first round.What held her back wasn't her profile. It was her approach.So she came back the next year when the stakes were even higher. This time, she did it differently – and landed McKinsey and Bain.Katie breaks down what shifted and what re-recruiters (and first-timers who want to avoid the same trap) can take from Sharon's story.Resources:If you're re-recruiting and want a real plan this time, Black Belt is where candidates like Sharon get the structure and coaching they were missing the first time aroundNot sure if Black Belt is right for your situation? Book a free 15-minute call with Katie and find outConsulting Deadlines:McKinsey, Bain, and BCG deadlines hit August 11 – 13 (and more are coming) – get interview-ready fast with Black BeltConnect 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

Too many clients panic when they are managed out of McKinsey, BCG or Bain. They assume the worst and imagine a tattered reputation. This could not be further from the truth. In this podcast, let's revisit a Case Interview & Management Consulting classic where we explain why it is in McKinsey's and BCG's best interest to never disclose you were managed out. It is part of their business models that the market never knows you may have been the world's most ridiculous consultant. So, if you are being managed out, relax.​ You will be ok. Here are some free gifts for you: Overall Approach Used in Well-Managed Strategy Studies free download: www.firmsconsulting.com/OverallApproach McKinsey & BCG winning resume free download: www.firmsconsulting.com/resumepdf Enjoying this episode? Get access to sample advanced training episodes here: www.firmsconsulting.com/promo

Moritz Baier-Lentz is one of the foremost investors in gaming, AI, and frontier technologies—including companies like OpenAI, SpaceX, Palantir, Etched, Decart, and Recursive. He founded Goldman Sachs's global gaming practice and was previously a partner, IC member, and head of gaming at Lightspeed. Moritz is part of the founding team of General Intuition, an AI research lab training agents on video game data, which has raised a $133M Seed round and a $320M Series A. He is also a senior advisor to OpenAI, McKinsey & Co., and TPG Capital.In this episode of Summation, Moritz and Auren discuss:Why video games are the best data set for the next phase of AIThe idea that humans only truly learn during playWhy Germany's fear of risk is culturalGetting into Stanford with an essay about Diablo IIYou can find Auren Hoffman on X at @auren and Moritz Baier-Lentz on LinkedIn or his website.

[English as below]Tập 402 phiên bản tiếng Anh của Vietnam Innovators đón chào Stephen Turban - Co-founder & CEO của Lumiere Education, đồng thời là gương mặt quen thuộc trên sân khấu hài độc thoại Saigon Tếu. Chuyến đi 2 tháng đến Việt Nam năm 2017 đã hoàn toàn thay đổi quỹ đạo sự nghiệp của cựu nhân sự McKinsey, đưa anh vào hành trình xây dựng một tổ chức giáo dục toàn cầu mà không phụ thuộc vào dòng vốn mạo hiểm. Trong cuộc trò chuyện cùng host Hảo Trần, Stephen chia sẻ về chiến lược quản trị đội ngũ đa quốc gia và tầm quan trọng của việc xóa bỏ tư duy coi nhân sự từ xa là "nhân công giá rẻ". Anh khẳng định chìa khóa để bứt phá quy mô nằm ở việc chiêu mộ top 5% nhân tài xuất sắc và trao cho họ môi trường phát triển bình đẳng như tại các trung tâm lớn như New York hay London.Bên cạnh câu chuyện kinh doanh và bài học đắt giá về kỷ luật bám sát thế mạnh cốt lõi, Stephen còn mang đến lăng kính thú vị về việc tách biệt rành rọt giữa vai trò CEO và niềm đam mê diễn hài - chứng minh rằng một nhà lãnh đạo không nhất thiết phải "năng suất hóa" mọi sở thích cá nhân để đạt được thành công bền vững. —EP 402 of Vietnam Innovators (English Edition) welcomes Stephen Turban - Co-founder & CEO of Lumiere Education, and a familiar face on the Saigon Tếu stand-up comedy stage. A two-month trip to Vietnam in 2017 completely reshaped the former McKinsey consultant's career trajectory, embarking him on a journey to build a global education enterprise without relying on venture capital.In conversation with host Hao Tran, Stephen shares strategies for managing a multinational team and the importance of moving past the mindset of treating remote talent as "cheap labor." He emphasizes that the key to scaling lies in recruiting the top 5% of exceptional talent and offering them an equal growth environment on par with major global hubs like New York or London.Beyond business insights and the discipline of staying true to core strengths, Stephen brings a fresh perspective on keeping a clear boundary between his CEO role and his passion for comedy - proving that leaders don't necessarily have to "productivize" every personal hobby to achieve sustainable success.-Listen to this episode on ⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠And explore many amazing articles about the pioneers at: ⁠⁠⁠⁠⁠https://vietcetera.com/vn/bo-suu-tap/vietnam-innovator⁠⁠⁠⁠⁠-Feel free to leave any questions or invitations for business cooperation at ⁠⁠⁠⁠⁠team@vietcetera.com

Competing in a Future World of Infinite Intelligence Navigation: Intro From Knowledge Workers to Judgment Workers The AI-Native Company: Org, Hiring, Culture The Human Element: Are We Underestimating It? Scenarios Our Take Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show:   Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Nuno Gonçalves Pedro Introduction Welcome to episode 79 of Tech DECIPHERED. Today, we take a leap into the big unknown. This is a thesis episode, not your classic analysis, in-depth sharing episode. The big idea for this episode is that we may be approaching the cognitive age, and how would one, or how would a company compete in a world of infinite intelligence? The big idea, again, is that intelligence, which has been mostly scarce and expensive for all of human history, might become abundant and cheap. If that happens, what happens to work, what happens to companies, what happens to society? This episode will be really framing a lot of these discussions. From knowledge workers to judgment workers, addressing the AI native company and how does that change, going into the human element and whether or not we’re underestimating it, and finally, ending up going into scenarios, feasible scenarios of a future where, well, intelligence is abundant. Intelligence is quasi-infinite or infinite itself.Bertrand Schmitt Yes. Big questions for this episode 79. From Knowledge Workers to Judgment Workers We can start with from knowledge workers to judgment workers. Let’s go back first to how came the knowledge worker. It’s a 20th-century invention from Peter Drucker in 1959. The idea here is that that category might be splitting. The production of knowledge itself is on its way to being commoditized by AI. However, our perspective is that judgment around production of knowledge is not disappearing and is staying for a bit control managed by humans. What’s your take on this, Nuno? Do you agree with this split?Nuno Gonçalves Pedro I think it’s a little bit more profound than that. It’s not just judgment. Definitely, human judgment will be needed. We’ve seen agents perform all sorts of funny things in the wrong way when left alone to their own devices. Even some very well-known AI researchers coming forward and saying, “Hey, I tried to use this myself, and actually I messed up some of my systems,” or “I messed some of my code. I messed up some of my flows for a period of time.” I think just having human-in-the-loop from a judgment standpoint will be needed for a significant amount of time. That is something you can’t just delegate into machines, into algorithms, et cetera. The second part is, ultimately, there needs to be contextualization, and that contextualization, I think, comes from two forms. One from actual data, where the machine, I think, at some point will catch up, or the machines will catch up. The algorithms, at some point, on the data analysis will get better and better and have probably the closest to the truth that you can get, minus all the biases that are in the data, just to be clear, because data has a ton of biases. We’ve looked at this in the past and discussed it at prior episodes. But maybe on that, I think the machine has a chance to catch up, or the machines have a chance to catch up, so there’s less of distinctiveness from the human standpoint. But then, on just the attributes, the ability when you’re judging some situation, you’re in the middle of the situation. You’re judging the person and how it’s acting, in some ways, a lot of the things that end up happening, end up happening because there’s human interaction. There’s someone on the other side. I see how they’re delivering the message, how they’re implicating. We’ll talk about it later in the context of the organization and what changes in companies. I don’t think it’s just judgment. I think there’s a little bit more than that. One of the reasons I went to the dark side of management early on in my career from being an engineer was Peter Drucker and this notion of the knowledge worker, which he later on reemphasized with the publishing of his book, which for me was seminal and defined a lot of my career in life, the post-capitalist society, which is this notion that information rich and information poor is going to be the key distinctiveness that will happen in the world. The two big camps, information rich, information poor, which links back to this invention of the term knowledge worker, that knowledge is going to be key in some ways. I think that’s what we’ve seen for the last decades. Again, I think judgment is not going anywhere, but I think it’s beyond judgment. There’s elements of humanity and involvement that won’t go away anytime soon, where human-in-the-loop are particularly critical. We’ll discuss later some scenarios, but for me, that’s my stick in the ground. I think human-in-the-loop is going to be critical for many decades to come.Bertrand Schmitt While we are talking about all of this, and we share some possible scenarios, there is always that question. This is moving so fast right now. If you think about AI 10 years ago, AI 5 years ago, AI with the launch of ChatGPT 3, and then AI the past 2 years, now we have agents that are running at scale. Things are moving very fast. I can tell you, me in 6 months, the change has been pretty dramatic in terms of what I can use AI for. There is always that question that whatever we are thinking about cannot just be connected to what we were able to do 6 months ago or even today, we have to think and project ourselves at least in the next 6–12 months. Of course, we can go beyond that, and we will do that with some future scenarios, but it’s a very fast-moving, and it’s not clear yet where are the limits.Nuno Gonçalves Pedro I think that’s a very fair point. Let me try to analyze things that I don’t think will change anytime soon for the next few years. Agreed with you that many things will change, and we’ll have a lot better tools, platforms out there. That will be difficult to predict what exactly won’t change. I think there’s elements of humanity, and some of them do relate to judgment, like having good or bad taste, having a view on it, on whether something looks good or bad. Obviously, all of this sometimes is subjective, but some of it may not be as subjective as people think it is. The elements of contextualization. I think a little bit going back to what we did at Chamaeleon ourselves, where we built this platform, Mantis, and the objective of building Mantis was not really to replace us, was that it was a core augmentation layer in some ways that we would use investment or investor judgment as humans in the loop to systematize pattern recognition and a variety of other things, but that Mantis would really elevate all that judgment, not just in terms of timing, us being more productive, but also in terms of the quality of the decisions we’re making. Think of it as a little bit like having our human judgment in the context of operating Chamaeleon at a higher altitude, where we are more aware of the things that are happening and how they actually happen. The ability to really get to the data pieces and then make decisions on top of that that generate the needed alpha in our case for investors. What I mean by this is I think there’s always going to be core elements of humanity that I do think are going to be difficult for the machines to replace. For example, the taste piece people are like, “I can figure out what’s the taste in the market.” Yeah, but that’s mainstream. That doesn’t identify what’s the next big thing, which normally doesn’t start from mainstream. It starts from something else. It could start from opinion leaders and influencers. It could start by someone having a different way of addressing a problem and having a solution that hasn’t been thought through. For example, elements of creativity, I think, in human judgment and in human operations is something that I feel the machine will still have difficulty to replace.Bertrand Schmitt Let’s not forget how today current algorithms are working by feeding them enormous quantity of data, actually as much data as we can find. Finding more data is becoming a limitation these days. What it means is that it’s very hard for AI to think beyond its training data. There is some level of logic that’s being added, but at the same time, take the launch of the iPhone. What was the opinion before launch? Is that no, it doesn’t make sense. Not enough battery life, no keyboard, no this, no that. If you just base your analysis on what’s written out there, what’s being sold out there, you would just say, “It’s going to fail.” AI might really follow that more generic advice and perspective because that’s what in the training data and that’s what they’re in volume. It’s, of course, raising a lot of questions of, how do you improve the quality of the training data? How do you separate the weed from the chaff? There are a lot of questions there, and obviously, it will get better over time. But it’s still a critical part of how it’s working today. It won’t be that easy to change. I really like your point regarding Mantis, and I will say in general, platforms that you build with AI or leveraging AI capacity. Because when we say knowledge production is going to disappear, but we’ll keep judgment, it will be a different type of judgment because the quantity and quality of knowledge we will have in front of us to build our judgment will be very different. If suddenly we have for free the work of 10 interns or 5 junior analysts or whatever, and you can run that on nearly anything you do in life or at work, it’s completely dramatic. Your judgment was not used to be exercised so often because often you were missing quality data to have a judgment. Before it was a lot of finger in the wind and trying to smell something, but you didn’t have enough to make a serious analysis. Except if you are working as a strategy consultant, as you used to do, Nuno. That part is actually quite interesting. That the judgment itself will be exercised much more often and hopefully on the base of much more in-depth analysis for a lot of things. We will work very differently.Nuno Gonçalves Pedro We will go in-depth, faster and more fact-based, more data-based along the way. The question some of you might have right now is, is there some judgment that’s going to go away? Is there some judgment? We seem to be defining that there’s this organization, we’ll talk about it later, that goes from doers more into deciders. I think there’s some nuances to that, so I’ll just hit pause on that. In terms of judgment, obviously, there’s judgment that has been hidden over the years under the pretense of being wisdom, but it’s actually not wisdom. It’s just repetitive tasking, and it’s rules-based for the most. There’s a lot of judgment done, in particular in the white-collar space, that you could say it’s just reps. People have been doing it all along like that, and so therefore to say, “I’ve done it before like this, so I’ll do it the same way.” There’s actually no best in class, no analysis, no nothing. It’s just, “I’ve done it like that before.” I think that type of judgment will disappear because, again, algorithms will be as good, if not much better at that. They’ll be better at figuring out, actually, this would be the better way to do this. That’s how you play it forward. Then the question is, if there are fundamental, wise people in the organization, people that can really take that more complex elements of judgment, how do you go from the world we have today, which is a world of apprenticeship, where people come out of college, they go and work, and they learn their way, and therefore, hopefully over time, some of them, not all of them, we know that, but some of them will develop that wisdom to be great decision makers 15, 20 years down the road? How do we do that in a world that now is saying, “I don’t need people out of college because I can do it myself, and I can do individual contributor, and I can have agents doing the work that would require some manifestation of management in the middle.” Basically, “I don’t need this stuff. I don’t need you.” It’s a little bit the story we’re in. How do you create then this apprenticeship? How do we create then wisdom? My two cents on that is that wisdom, because of what we were just discussing and what, for example, myself and Bertrand was just saying, because of more often interactions with more data-stressed information and insights, what will happen is people will get better through their own reps in whatever form they’re doing, in day-to-day life, in internships, et cetera. In some ways, that will create the accelerated growth. It’s a little bit the interactions with agents and the interactions with our beloved AI algorithms that will create that growth over time and maybe not as much with other people. That still leaves the question around social interactions, but that’s probably the way this gets sorted. Apprenticeship gets sorted through the machine and the human having more interactions in effect.Bertrand Schmitt I agree with you because when we talk about apprenticeship, in some ways a lot of time was wasted on stuff that were not that important. But in a way, that was the price you had to pay in order to be there when people make the big decision to try to get some wisdom from that one hour of interactions that’s really useful and make a difference out of your full week. But the rest of your full week was just basic stuff that you had to do like a machine in a way. Why not let a machine do that? That, for me, is a big question. You could argue there is a transition period where it could be hard. For instance, if you can work hand in hand with AI smartly while you are doing your 4, 5 years of universities, you could graduate with a very different knowledge, perspective, judgment, skill set than anyone who graduated 5 years ago. I think that part will require a question around, “How do you change education?” You see what I mean? If you keep education the same way, expecting that the output is someone that should go now into 5 years of apprenticeship, that’s not going to work because companies will be, “No apprenticeship anymore.” On the contrary, you have to come much more knowledgeable and ready to use the tools. The tools are so efficient that the bar pretty high. You need to come already very well-grounded. If the education is not doing their job, that will be trouble. That part for me, I think is often forgotten. In some ways, the new-found importance of universities as a place to, and not just universities, the trade to really deliver people who are ready for the workforce. If on the business side, the expectation can change, of course, you have to change the education on the other side. My worry probably right now is that it doesn’t look like universities are in touch with what businesses are looking for, businesses are working on. Of course, that’s very worrisome because the cost of university has increased very significantly. It’s not clear quality of education has improved at all. If anything, it could be the opposite. It’s pretty scary. Of course, it’s going to raise a lot of questions. How much is education worth in that type of situation? Maybe another point because we talk a lot about apprenticeship, how this stuff was useful, but at the same time, if we go back in time, not long ago in the ’50s, if you wanted to be a developer, for instance, ’50s, ’60s, the job was very different. There was barely any programmation language out there. You had to use punch cards. Your time truly spent doing the coding was very limited. Once you had your stuff working, then, the debugging was a total nightmare. My point is that no one is looking back to that time saying, “You know what? It was great. It was a great way to learn and to do an apprenticeship for 5 years. To do that crappy job of punching cards for the boss.” There was little value in this. Guess what? Everyone is happy it’s not being done anymore by anyone. I think we also have to see what AI is bringing in a similar way is that everyone’s job is going to become quite different. There are a lot of big parts of the job who are not going to look back with fondness. Just looking back as, “Wow, that was very machine-like type of job. I’m glad I’m done with it.” People will want to jump directly to the next step. You don’t need to go to the punch card phase to be able to be a good developer for the past 40 years. I guess it will be the same with AI.Nuno Gonçalves Pedro I think so. The difficulty we have as humans is to also visualize dramatically different scenarios and landscapes, professionally. It’s difficult for us to anticipate what are the jobs of the future. Jobs have changed a lot in the last few decades, not even the last century. What people do, the migration initially from the agricultural society to then the industrial society to then the services society, and in some ways, the shift within the services industry, and now we’re seeing another shift, so we can’t really anticipate what those jobs look like. Back to your point on education, because I think that’s a very important point. If you’re right now an undergraduate student or a postgraduate student, for that matter, and you’re not figuring out your own mechanisms of learning outside of your syllabus, outside of what your professors are telling you, et cetera, you’re going to face very difficult times. If you’re not right now using all these AI tools proficiently, all these cycles of vibe coding, co-working, et cetera, with agents in the mix, you’re going to have a really tough time. If you’re not at this point in time as proficient as someone like myself or Bertrand, and given that we’re nerds, we’re relatively proficient with a lot of these tools that are out there. On top of it, some of us have our own platforms in-house. If you’re not as proficient as we are with those tools, you’re going to have a very difficult time because then people like us won’t need you. I think that’s the sad truth. It’s like at some point, if you’re not needed, you’re not needed. Then again, you may find something else that’s more interesting for you to do. Start your own company, go join a new exciting job doing whatever it is that you need to do next, et cetera. But again, I think the bar is very high. If you’re in college right now, again, undergrad, postgraduate, this is the time of transition. This is the worst time. It’s not the best time, it’s the worst time. Because education and all these institutions haven’t adapted to it yet. You need to adapt. You need to adapt. You need to adapt. If you don’t, you’re going to pay for it, not just in the loans you need to repay, but also in terms of actually having difficulty finding your career path in those first few critical years.Bertrand Schmitt You need to be especially proactive when you’re facing this type of period where businesses are adapting as fast as they can because they all know it’s going to be survival of the fittest very quickly. Universities typically are working on a very different pace, and it’s pretty guaranteed they are not going to have adapted as fast as businesses. In time of big dramatic change, it will be trouble. It will be trouble. Yes, you will have not fun. Not saying it was part of the deal when you sign up for that loan and decided to go for university. But that’s life. There has been issues before. It’s not the first time. You have to do something about it. You talk about your perspective about, “Hey, why do we need you if you are not already fluent and very efficient with these tools and stuff?” The truth, in some ways, it’s even worse than that. Each time we spend with someone who is not efficient with all of this is less time we spend with the tools that are already providing magic for us.Nuno Gonçalves Pedro Exactly.Bertrand Schmitt It’s a very big choice of, “Hey, do I spend more time training this person?” Do I just… there is an opportunity cost. Or, do I spend more time staying at light speed? Why do I slow down to do something else in the hope that maybe I will get to return versus the light speed I’m already on? It’s a lot of tension. Again, it’s certainly new. But if we want to look back, I think you talk about the switch from agriculture and society, industrial society, and now the service industry. The reality is that, yes, we have made dramatic changes in the past before. 140 years ago, we were 90% agricultural society in Europe, in the US, 90% of us. Today, it’s what? 2%. So my point is that that’s a normal evolution. There is no progress without change. Sometimes the rate of change is soft, and sometimes you have a step function. Now it’s a step function, and it’s also a pretty fast step function. Before, it could take decades to get new stuff being put in place, to have electricity come up, this or that. Now we see that the rate of investment in AI is insane, way beyond anything we have seen before. Two, in a way, a lot of the architecture behind the scene was already there to support an even faster transition. What’s new might be the pace of the transition, how unnatural it might look. But at the same time, if you put yourself in the shoes of someone who lived 150 years ago, I mean, this was also a dramatic change for them. From horses to cars to planes to rockets, pretty big change, maybe even bigger change.Nuno Gonçalves Pedro Maybe the silver lining, just to bookend this section, is one, there will be new roles. There are a lot of things we can’t anticipate. There will be new roles, there will be new jobs being created, and new things that we can’t really quite grasp yet. The second part is that the rules are changing, and they’re changing, I would say, in general, for the better. If you are a decision-maker or an organization, and you still have your job, you’re probably making more important decisions with more data, with more tooling around you, with less red tape, hopefully over time. I know that will not hold true for all the big corporations out there that are listening to us, but it is starting to happen. Things are making an impact on how decision-making is made. There’s less and less red tape along the way in certain organizations. There are more and more fact-based discussions happening as we move along. The silver lining is better jobs, more jobs, different jobs in the future, hopefully as well. Secondly, the second part of the silver line is that the jobs that exist today, hopefully, will be more interesting, certainly on the knowledge space and on this judgment space that we’re now introducing as part of this episode. The AI-Native Company: Org, Hiring, Culture Switching gears, maybe to how does that shift? How does the company of the future look like? How does an AI native company look like? I feel there are a lot of discussions on, “Oh, you only need one person to run everything.” Let’s not go to that level. We’ve had a couple of episodes where we focused on AI as your co-founder and a couple of other elements that you guys can go back to. Let’s focus on a more evolutionary view of what’s happening to organizations, and maybe start with the org structure. In general, we should see more flat organizations where mid-level managers have to justify their pay in some ways because middle management are routers. They are normally routing tasks. It’s sometimes aggregating it, synthesizing it, and pulling it back up. Guess what? AI and agents in general are very good at that. The synthesis piece, et cetera, is not as well needed. One could say there are several elements of middle management that are valuable, like the coaching of people, the creation of apprentices, and the accountability that comes with some of middle management. But lo and behold, most of middle management is seen as a little bit of a thin line that doesn’t need to necessarily exist. I feel we’re moving into a world of smaller teams, more senior teams, where there’s more judgment at the top, where you’ll have people that both do a mix of what we used to call management in its new form, but also a lot of individual contribution. If you’re not used to that, if you’re not used anymore to be an individual in the future, again, and if you’re a very senior in an organization, maybe this is the right time to either reinvent yourself, find some other job that doesn’t require as much of that, which we’ll have plenty of those jobs for the next few decades, or maybe retire. I’ve actually, shockingly enough, seen people who have said, “You know what? This thing is changing too fast, too dramatically. My industry is changing quite aggressively right now. I’m about to retire in a couple of years. I’m just going to retire now.” I’ve literally met two people who have done that. Again, there’s nothing wrong about it. I think we’re, again, going through a step function and a huge shift, but figuring out where you fit in this new model of organizations, more senior at the top, smaller teams, more of a mix of individual contribution with management than ever was done before.Bertrand Schmitt I agree with you. In some ways, I’m not surprised that some people might say, “You know what? It’s now time to retire.” I feel a bit sad, maybe because it means you don’t like to keep reinventing yourself and changing your habits and thinking about new stuff. You were a creature of habits, I would say, if that’s your conclusion. But everyone is entitled to their own opinion, obviously, and a way of life. I guess that’s what happened, again, at regular times in the past in terms of big change. What I can see is that the rise of, you can call it the full-stack individual, someone who will have multiple roles inside the team. Before, you had to really separate the role. Especially in the US, there is such a clear separation between every role you can have in a company. Let’s take a tech company. You will have people doing design, people doing different types of designs, people doing front-end development, back-end development, and operations. You see step-by-step hyper-specialization. I have seen that, and it’s true that the level of complexity you had to deal with at some point requires some level of hyper-specialization because it will take you 6, 12 months in order to be really, really strong on a specific topic, a specific language. God forbid, trying to go deep into something that you had no real experience into. But I feel with AI, it’s a big change, actually. It’s the opportunity to go beyond that. It’s the opportunity to do more, to touch more. You can combine designing and shipping code, product managing and shipping code, being an analyst and deploying. Of course, we have to think how it works because putting a marketer shipping code to production, maybe that will get you into trouble. But I think that there must be some change. We see it changing dramatically, how fast we can get into something, something different from what we are used to. I think it would be crazy not to take that opportunity to dramatically change the scope of many positions and put an end to that hyper-specialization. I think for me, in some ways, hyper-specialization was bad. There is only so much you want to be a specialist in because a lot of things, a lot of opportunities are actually coming from the mixing of many different ideas, many different perspectives, and you lose if you go to hyper-specialization.Nuno Gonçalves Pedro I don’t think the age that is coming is the age of the generalist. I think it’s going to be the age of the multispecialist. We’re going to go into an age of multispecialization, which is a little bit, we’ve mentioned it as well in the past, what Amazon defines as an athlete or T-shaped or pie-shaped people, people that have on top an amazing ability to do general management, strategy, managing teams, et cetera, then have spikes. Spikes into business development, corporate development, product management, whatever it is. With AI and with agents, the development of those spikes, as we’ve been discussing in this episode, will actually be easier. It’s almost like a given. If you want to go deeper and deeper into a certain area, you can go much faster. I think that level of multispecialization is going to be really cool to observe. I’m not sure we’ve had an age of multispecialization over the years. Maybe people would point out, well, the Da Vinci example, people that are great across very different areas. Maybe that’s an example of multispecialization. But honestly, from my perspective, this is going to be an exciting time because of that, because you’ll have people who, instead of being just focused on this area of sales, and I only do that, they can actually and should actually do a lot of other things. So the work, as we were talking before, can be more interesting. More demanding as well, because the judgments you need to make are more complex. The context you need to actually gain needs to be gained much faster. At a level of magnitude, you haven’t been able to do it before. Talk about information overload. But actually, ultimately, the roles can be a lot more interesting, a lot more exciting, because I can jump around. If I’m an investor, in this case, we have two investors on this conversation. But if I’m an investor, one of the things that we start looking at is actually not just looking at a startup as, is this startup doing something in AI or not? Is it AI-enabled or not? Is it an AI platform or not? But actually, more fundamentally, is this an AI native startup? Meaning, organizationally, culturally, is this the company that’s already in the AI age? How is the team working? How are they defining things? It’s not just that they only have two or three people. It’s like, what are those two or three people doing? How are they doing it? What cadence are they doing it on? What tools are they using? How are they making decisions? I feel we’re still actually relatively early on that track. It’s very interesting because we’ve had all these companies raising mega rounds. First round out, we invested in one of them, but there have been many frontier labs out there raising a ton of money. But a lot of them don’t have a fundamentally different way of doing business. Of organizing themselves, of how they do the day-to-day. Although they’re working on cutting-edge stuff, with very notable exceptions, they’re actually not using it themselves. They’re not actually shifting how they do stuff themselves.Bertrand Schmitt For me, that’s very interesting because in the past, I used to be quite conservative on how you manage and run a company in the sense that if you’re already in tech, if you are already on the cutting edge of what technology can deliver, and this and that, don’t waste time trying to invent a new org structure. Just focus on delivering something great, amazing, and be great at technologies. That’s already your huge differentiator. At the time, there was no real reason to innovate on the team organization. I have seen so many teams that tried to innovate, and it was just catastrophic because there was not much to innovate on, because we had decades of optimization that we could leverage. There was no reason to invent. But here it’s very different. There is a dramatic shift in how you can organize differently a company. I don’t think there are any blueprints yet on what’s the best way to do it because it’s too new. But at the same time, I would feel very bad to invest or support a company that first is not focused on AI or AI-enabled, but at the same time is not trying to innovate on the team itself. Because if you don’t do that, you’re going to get killed by someone who is going to innovate better than you on not just the product, but on the org as well.Nuno Gonçalves Pedro Indeed. The shifts are pretty substantial. If you look, for example, just at hiring, what do you hire for? Certainly, there’s this element of the multispecialized orchestrator, which normally will be someone with quite a lot of wisdom and expertise. It doesn’t necessarily mean someone who’s old, but someone who has the ability to work with all the AI tooling and platforms out there and be an orchestrator of agents. Why do they make judgments, make decisions, move stuff forward really, really, really quickly? Again, those jobs are going to be the best jobs. The second part, I think that is very interesting, around hiring, is you’re going to skew towards the elements that are potentially either very aligned with the use of AI tooling and platform, AI expertise, or being AI native, or someone who’s used to using AI. That’s one side of the fence. On the other side, you’re going to actually be optimizing to hire people that have the characteristics that will be difficult for AI to replace immediately, like taste and the notion of fundamental accountability and notion of implications, the notion of how you affect change in organizations, how you affect change in individuals, the elements of coaching, and beyond coaching. You’ll be optimizing for those kinds of hires as well. Then, last but not least, for me, I feel that there is a momentum already happening. I think it will happen even more, which is the tendency to under-hire rather than over-hire. The moment of the good old days of blitz scaling, “Oh, let me go and hire 300 people to scale my go-to-market and just land grab market.” Now, that’s not how it’s going to work. People are going to try and first get the efficiencies in-house with top talent and see if there’s, at the end, the need to hire more people or not, rather than the other way around. I think the issue here is a little bit of what we alluded to before in this episode. There is a tax on individuals. If you hire more people, you’ll have to manage people, you’ll have to work with them, et cetera. If I don’t need to, I might as well work with the agents that the tools and platforms that I use give me access to. Because that’s a world that’s much more efficient, right?Bertrand Schmitt I’m in total agreement with you on this. It’s definitely raising way more questions than before because, again, on one side, you have the product, the technology used to build products that are completely different. At the same time, all of this is also enabling new ways to design organizations and to scale differently, especially in a world where, as we have seen in 3, 6, and 12 months, stuff that you thought were impossible are suddenly becoming possible. So you’re, “Hey, I’m going to scale and burn a shitload of money for 6 months before I know if there is any return.” Versus, “You know what? Maybe I just wait 6 months. The AI has improved enough so that we don’t need this new team. We don’t need these people to do stuff.” Because actually, if you just wait 6 months, we will have stuff coming for free from either new AI models or new AI tools or this or that. If you remember, we used to say that in mobile, things were going three times as fast as on the web in terms of pace of innovation and speed of development and stuff. I mean, with AI, it’s 5X mobile.Nuno Gonçalves Pedro Maybe even more. Yes, well.Bertrand Schmitt Maybe even more, maybe 10X. Every assumption around blitz scaling or scaling in general was based on past assumptions. It’s not based on how is the industry evolving today. Might make more sense for you to really grow your agents and spend more money on more tokens. I remember, of course, Jensen is selling his business interest, but he was saying, “Hey, for each one of my 450K engineers, he better spend 250K in tokens a year.” I’m not saying it’s the right way to say it, but I think there is some truth in it, and that would be something to think about. Have we maxed out the token usage per employee? I’m not talking in a stupid way because token maxing and wasting money has no value and is as stupid as it gets. But if you are truly getting a return on these tokens, can you use more? Can you generate more? Can you create more loops so that one engineer manages not just 10 agents, but 50 agents, but 200 agents? I think that’s the big question. We’re trying to add more people. More people means more management, more issues, more this, more that. That would be a fair question. Another piece of the puzzle is how do you build in a way your… I don’t know if it’s a digital twin, but more like the digital version of your companies represented by agents. How do you make sure that everything you do as a business is truly captured, is truly leveraged so that your agents are getting better and better? Not just because the model gets better, but because you are putting more data into it, because it has more opportunity to learn, and as a result, gets better at your specific business.Nuno Gonçalves Pedro The next big thing is culture. How does culture change? I think the biggest shift that I see is, why would you do meetings all the time?Bertrand Schmitt Yes.Nuno Gonçalves Pedro At least at Chamaeleon, we have a very small team, just by the way. We have a very small team at Chamaeleon. We’ve reduced by way more than 50% the time we spend on meetings between each other across the board, one-on-ones, partner meetings, et cetera. I think we’re really pushing to be more and more asynchronous. There’s stuff you can process via message. I was just asking one of my colleagues, “Can you just send me that prompt for that so I can just do that on CoWork?” Or “Can I just go on Mantis and do this? Can you tell me the cycle?” Or vice versa. Basically, it’s a little bit like you’re just going to do it. I don’t need to meet. I don’t need to meet all the time. There are some things where we still need to meet and interact, and we need to brainstorm at times, and we need to go to a different level of abstraction on the top end. Then on the lower end, there might be things that are a little bit more specific and governance-related and operational-related that we need to agree on that are more sticky. But otherwise, the culture is going to be biased towards build. “Go and do it,” rather than, “Let’s do a meeting.”Bertrand Schmitt Yes.Nuno Gonçalves Pedro Async is the thing. I’m more and more like we have a couple of interns this summer. “Can we async this?” They’re like, “What does that mean?” “Can we make this interaction asynchronous?” Because synchronous interactions for me are very expensive. Can you send me something that I can process, and then I can send it back to you? We don’t waste time on you giving me context and whatever. Then I’m not ready quite yet because I need to process it. Maybe I’m in between two meetings that I’m actually thinking about other things in my mind.” Again, I feel that shifts how stuff is done. One, build rather than meeting. Two, asynchronous versus synchronous. In some way, millennials had it right when they shifted a lot to messaging and stuff like that. Let’s do more asynchronous rather than synchronous, those two elements from just an operating model of the company are significant. Maybe this is a good time for me just to put one parenthesis because there’s this thing that’s bugging me as we’re talking here. Everyone who is listening to us at this point in time might be saying, “Cool, but I work for this large organization. We’re just now…” Everything we’re saying here is contextualized by time. We’re giving you extreme situations. We’re looking into the future. Some companies that we’re talking about might be doing this already as we speak. Some of them might be in the process of doing this and might in the next couple of months be doing it like we are describing it here. Some of them might take years to get there. Then again, some of the companies that might take years might actually be destroyed in between or meanwhile, and be disrupted. Some of them might not because they’re in very legacy businesses, and it’s fine, and it’s okay. Again, don’t take everything that Bertrand and I are saying today as this is gospel, and it’s going to happen tomorrow, and why the hell are we not doing it? We think that aspirationally, this is where you should be moving to as an organization, whatever size you’re at. Speed will matter, as we discussed before, but not everyone, obviously, is going to move as fast as we’re describing it here.Bertrand Schmitt Yes. Me, for instance, take inspiration often with what some of the AI labs, frontier AI labs, are doing, the way they are working, especially in OpenAI and Anthropic. They are clearly at the top of the spear in terms of what is it that you can do because they have access to models we don’t have access to, because they have unlimited tokens they can use for tasks. They hire people who are, of course, 100% on AI. They are the best example of what is achievable if you have the top minds, if you have the latest models, if you have unlimited tokens. From there, you can take that for our needs and for our situation, and others in industries that are not as advanced. Definitely, you have some time. But as you say, things are moving fast, things are changing. Wall Street is going to expect better returns because when we discuss all of this, the conclusion is that you should be able to do more with less. That’s as real as it gets at some point. By the way, that’s what you see. You see better performance, a better business performance right now. So even if you might not get disrupted, you’d better start there. For some, it might take more time, and they might still be fine.Nuno Gonçalves Pedro Maybe to bookend this section, clearly what we’re saying is organizations are going to change. Their MOs are going to change, the structures are going to change. There are elements of what we discussed before in terms of judgment that are fundamental to this. The ability that in some ways, one would say a lot of the technique of getting solutions out there, even in brainstorming or problem-solving, is going to get democratized. The algorithms are able to do that. On the other hand, having points of view and having wisdom is not necessarily democratized, necessarily by the machines. It can be facilitated, it can be more productive in achieving that level of wisdom, but wisdom still will matter at the end of the day. We’re not saying that’s out of the question. Actually, that’s going to be the asset. People who have fundamental wisdom that can come to the table and frame things. We see this even today in prompt engineering, on just creating prompts. The better your prompt is, the better the outcome is going to be, the result that you get from the algorithms. That’s not going to change, in my opinion, anytime soon. That UI interaction piece is not going to change anytime soon. Again, if you’re an organization thinking through organizational structure, culture, if you’re thinking through hiring, these are some of the elements that we think will give you an opportunity, but I would actually go one step further. On the positive side, I would say, they give you arbitrage. If you’re able to move faster than your competitors and really adapt your org faster, you’ll reap the benefits faster as well. That’s what many still say and relate to as the word innovation. That’s how innovation gets accelerated. I think there’s a huge opportunity right now for arbitrage. If you move fast, experiment, experiment on new org structures, experiment with talent, you’ll know that some of them will work well, some of them will fail miserably, so you can’t experiment on literally everything. On the other side, I think the doomsday scenario is if you don’t, if you’re on the other side and your competitor is outpacing you on trying these different organizational models, structure, hiring models, and operating models, they’ll potentially just disrupt you. They’ll do stuff that you thought you had the moat on, and lo and behold, you don’t anymore. Sometimes it comes just from org, just from injection of people with a different MRO, different operating model.Bertrand Schmitt The Human Element: Are We Underestimating It? Maybe we can move to our next section about the human elements. Are we underestimating it or are we overestimating it? The three things that are a big part of the human elements, emotion, creativity, and synthesis. Is it just soft skills, replaceable part? On the contrary, is it the durable part now that we have automated intelligence?Nuno Gonçalves Pedro I’ll start with emotion first because I think it’s probably the easiest of all the ones you’ve mentioned. Emotion is key. Many of you listening to us will know this. The way you deliver a certain message, the emotion that you have when you deliver it, just in and of itself, this could be a sentence, it’s something verbal, et cetera. Makes a difference between the person or the people on the other side actually adopting it or actually just resisting it. Emotion is critical. It’s what runs the world. Everyone talks about a bunch of things, but emotion is a currency that is still naturally human. It will be, I feel, difficult for these AI tools and platforms to recreate it fully until there’s some literally very high-definition manifestation of them as avatars or some physical manifestation of them as robots and all that stuff. It will take a while for that emotion to be manifested. Emotion, I think, is still something that we as humans have as a moat, and it’s critical. As you mentioned before, I was a strategy management consultant at McKinsey, and getting people to action is actually 80% about the delivery, communication, the emotion that you surround the project itself, more than sometimes the truth. It’s great to have the truth and to have something that is similar to the truth in terms of analysis, but in some ways, that’s not what really moves change. Change is moved by, I would argue, a significant amount of emotion and alignment on emotions.Bertrand Schmitt You could argue that’s something that most politicians have perfectly understood. If you look at most campaigns these days, everything on emotions, maybe the tagline might be one word. It’s interesting when you see from that perspective that actually it’s very little on facts, very little on all of this, but more about emotion. You could argue it’s the same for businesses in the future? That’s a fair question. I think creativity is another one that’s quite important. At the same time, it’s not so easy because I must say I’m quite amazed when I’m looking for creativity from AI, either to generate the image, to generate video, to generate audio, or to generate text. AI can be pretty creative. I still think you need to control its creativity; you need to understand what’s good, what’s bad, what’s quality, but at the same time, I can see even in creative tasks, AI can be a very strong partner. I’m talking about any creative task, like invent a name for a product, let’s brainstorm the mission for the company. AI can actually be doing a pretty impressive job. That’s the type of job where you will hire experts, where you will use some of the best people in your team to help you for days. We say, “You can do quite a lot.” It’s an interesting one because I think there is some unique human creativity, and at the same time, AI can be pretty strong at creative task as well.Nuno Gonçalves Pedro I agree. In particular, if it represents benchmarking, if it represents repetition, if it represents seeing the world and then coming up with something that presents itself as creative, to be honest, it can actually outpace humans. If it’s like genuine light bulb moments of creativity, angles that haven’t been tried before, certainly not in the same way, I think humans still have the advantage. To your point, I agree. This is not a humans-win situation. On the previous one, on emotion, still, part of it is because, also on emotion, there are exchanges. You and I might be looking at each other, and from the facial expressions and the reactions, where you judge that for AI to get there, it’s going to take a long time. There’s going to be a lot of very complex algorithmic stuff put into that for AI to be able to create synthetic emotional behaviors, but creativity, I agree with you. There are a lot more nuances to it today, where AI does have significant advantages at the end of the day. Synthesis depends. Synthesis, I feel, if we’re talking about holding a bunch of messy assumptions, contextualized inputs with different layers of data adjacent to them and then trying to create and form one coherent, fully accountable point of view that you stake something on, like a decision, a company, a business unit, whatever, I think humans have the advantage. Part of it is the complexity of what we have today with generative, pre-trained transformers, today with GPTs, where the hallucination comes through, where it’s really more statistical analysis. Over time, maybe synthesis will be a forte for AI. Right now, I think we still have that ability to really be the ultimate decision-makers and judge-makers and have that wisdom put at the table to make those decisions. Honestly, models are very good on balancing both sides, so ended up, as we say in Portuguese, neither fish nor meat. It’s to balance both sides’ answers. That’s not helpful in most cases. When you’re in a difficult position where, for example, the future of a company, company is almost dying, what do you do? I’m not sure your AI algorithms that are going to give you a great solution. Because it will give you a median or average solution, which likely will lead you to a median or average outcome, which in this case would be failure. Again, on synthesis, there are some areas of advantage for human beings. If you are looking for clearly synthesized perspectives on certain elements that are maybe less edge-focused, they’re more than the normal part of the normal distribution, then probably AI agents are brilliant at that. All the tools we have today are pretty good at that, and I think they’ll just get better over time. That’s how I see synthesis.Bertrand Schmitt I think a lot of improvements will come with a better fine-tuning of agents to what’s special about your company. Because if you just take a general agent, there is only so much. It can understand your industry, your company, and your way of working. I think that part of making sure your agents are finely trained, finely tuned on your own business, so that they can give you a really well-calibrated feedback, will have a lot of importance.Nuno Gonçalves Pedro I think that’s absolutely spot on. Maybe to end it, what is definitely different about humanity? Definitely, emotion, as we discussed, some pieces of synthesis. Creativity, maybe the light bulb creativity, not the more repeatable creativity, the one that you can put and encapsulate into processes in some ways. There are elements of us being physical, which robots can’t still recreate. That’s definitely an advantage. The embodied, we’re embodied. That’s obviously a huge advantage. With that also comes advantages because we have to interpret each other, and we have to see the complexities in physicality that land to it. Is human and the human element categorical difference? If we’re having a more philosophical discussion around this, I think it is. I think it will be for at least the foreseeable future and maybe decades to come, even in whatever scenarios we’ll discuss, which is our next section, scenarios.Bertrand Schmitt I would say projecting beyond 10 years is always pretty hard on this because, again, some of the improvements we are talking about we can imagine based on how it has evolved, but at the same time, there will be disruptions in AI. Stuff that we take for granted in terms of weakness, especially, might not be there in a few years from now. Either because it has been solved through brute force or because the field will have made significant change and improvements and discoveries, making some of our points moot. If we talk about embodiment, obviously, robots are coming. How fast, how cheap? That will be a big question. Right now, they’re not very smart. They’re usually very specialized. The more we move to a more general form factor, humanoid form factor, the more I think it will change. Also, another piece of the puzzle is that we have the assumption of agents having trouble to convince humans and stuff. At some point, we keep assuming that humans in the loop. If we’re talking about agents convincing another agent, not having embodiment might be even more efficient. That will be another perspective. Going forward, we will have not just agents we control who are doing a job and scanning the job, but agents truly interacting with other agents. You have agents controlled by one person, one team in your company, working either together or maybe not confrontationally, but trying to think and having different perspectives with another agent, controlled by other teams. I don’t think we have seen much of that now. We have seen mostly agents that are controlled by one team doing one job in one direction. Not multiple teams agents working together, or against or in parallel with another team agent. I think we will see some interesting things coming out of that.Nuno Gonçalves Pedro Scenarios Switching to scenarios, we love our two-by-twos. We haven’t done one in a while. This time it’s a two by two. We have four scenarios. I think on one axis, we would have potentially the capabilities of AI. One side would be more incremental. The other side would be the extreme full AGI. I’ll define it in a bit so that we can at least have a little bit of a definitional view on what the AGI is. Then the other axis would be how gains are distributed, concentrated versus broad. Obviously, if they’re very concentrated, it’s more unequal. It only goes to a few companies, a few people, a few individuals. If it’s broad, it’s much more dispersed through society, et cetera. AGI, just to try to define it, the formal definition of it is that it’s a hypothetical AI that matches or exceeds human capabilities across virtually all cognitive and practical tasks. In some ways, AGI can learn, reason, and adapt to novel situations across any domain. Then there are several mutations on this, but there’s one notion, or rather, there are three notions that normally are across a lot of these definitions. One is generalization, ability to seamlessly transfer knowledge from one domain to another without needing retraining, which is a very impressive skill that we humans still seemingly have. Autonomy in agency, the capacity to operate independently, set goals, plan and execute complex tasks. I think AI is their issue with agents to a lot of that extent. Then, last but not least, human parity, performing economically valuable work at or above the level of a typical human knowledge worker. If you listen to one of our last episodes, you’ll realize that Bertrand and I have slightly different views on AGI, and if it’s already here or not. I think, definitionally, maybe we have slightly different views on what the definition actually is. For me, maybe AGI is a little bit more what some would call superintelligence and generalized superintelligence. Strict to census, Bertrand is more connecting to AGI as in its prime definition. It behaves as well or better than a human thing. Maybe that’s what’s leading us to differences on whether AGI has arrived or not.Bertrand Schmitt Personally, I will have a different scale where I will put AGI, as you just said, in some ways, relatively similar in performance to your average human being. On top of it, it’s able to touch different domains that most humans are not able to do. Usually, there is some level of specializations where in AI, it can be more generic. I will put ASI, Artificial Superintelligence, as clearly the step beyond. Something that, on any dimension you pick, it’s able to beat a human expert. From my perspective, I think we already discussed that, but we are at AGI already. We have AI that can do way better, not just way better, but at least as well as humans on many topics, sometimes better. Yes, there are some topics that are not for AI yet. Embodiment, for instance, to flock with your humanoid robot in 2026. For me, we are partially there or fully there in AGI. If we take the stricter definition, ASI, we are definitely not there, but my guess is that it’s moving quite fast. We might be there in a few years from now. I don’t think we are talking about multi-decades. It’s 5 years, maybe 10. Of course, there are questions because people will say, for instance, “Hey, how do you become truly super-intelligent when all your training is based on human data?” That’s not an easy one because how do you train on that? To be way better, not just a bit better, but way better. Maybe I’m going on a tangent, but some are looking at AI learning from AI, AI being taught from AI, AI fighting with AI, AI challenging AI. The same way we saw this AlphaGo moment where AI was not trained anymore, like in chess with human moves, but has been trained to play against itself. That’s when it reached superintelligence in Go. It reached superintelligence by playing against itself and basically letting go of that human baggage, if you want, and going to the next level. What I found interesting in that, actually, first, that’s what happened, but two, there was some analysis that the average level of Go players and the top players went up after AlphaGo because AlphaGo, in a way, opened doors that humans didn’t believe were open in front of them, or they didn’t see them. They didn’t see these doors, so they didn’t bother to open them. AI opened new doors, but interestingly enough, humans improved after that, thanks to AI. You see what I mean? It was an interesting, okay, that self-learning from AI was the way to go beyond the current level of human knowledge and human expertise, but at the same time, humans were able to follow up. It was not like suddenly humans are totally useless crap. They improved. Did they still beat AI? Maybe not, but it was definitely also helpful.Nuno Gonçalves Pedro Back to our scenarios. We’re going to take the definitional extreme just for argument’s sake for scenarios. We’re going to talk about maybe what you were saying, ASI rather than full AGI, but like ASI. Again, artificial superintelligence as the extreme on the one hand. Let me talk about maybe the first scenario that would come to mind. Maybe we can call it the plateau scenario. All of this was great, but it was all smoke and mirrors. They were great at some cognition stuff. They’re a great tool. At some point, they’re going to hit a wall. Hallucinations are never going to be a thing of the past. We can’t fully trust them on really hardcore stuff. We’ll gain productivity enhancements. We’ll keep gaining those productivity enhancements, but at some point in time, we really won’t reach ASI. We really will be stuck with what we have. It’s a little bit like we get the next big thing, the next big spreadsheet, the next big internet, but it’s not going to change the whole world beyond just productivity, enhancements, and amazing tools that we have available to us that makes us much better. In that scenario, the winners will continue being fast adopters, probably small and medium businesses, because there won’t be a push for maximum speed either, so they’ll catch up at some point. Then AI native companies will be better companies than other companies, but not necessarily overall disruptors across the board. It’s not necessarily a new species of companies. It’s just companies that are a little bit better at doing stuff, which we also saw during the internet phenomenon and that first big push forward and then bubble, where we had some companies that were fundamentally different on how they operated. It took us another couple of decades for companies to be more and more digitally native along the way. Basically interesting, but it’s boring. It’s like, cool, we got tools, we got promised the world. What are the implications? All these companies that are worth trillions and trillions of dollars are not worth trillions and trillions of dollars. Because at some point we’ll face competition, commoditization. It will just be tools and platforms. They will not unlock that next stage. Therefore, this will have been a bubble, and likely it would be a hard landing to that bubble. That’s the implication.Bertrand Schmitt I would just say that, yes, I agree with you, but I would just say overall, even if it stopped today in terms of quality improvement, speed or stuff, or it barely improves, I still think we will have 10 years of madness just to leverage everything that we have today.Nuno Gonçalves Pedro Understood, Bertrand. This is a scenario. I understand, but maybe we’re going to hit a wall, and we’re going to hit that wall next year, or we’re going to hit that wall in 2 years or whatever.Bertrand Schmitt Possibly. I’m just saying we still have 10 years of goodness from that big push in AI we experienced the past few years.Nuno Gonçalves Pedro Absolutely. Agreed, but it’s boring.Bertrand Schmitt It’s boring. It’s a plateau.Nuno Gonçalves Pedro It’s a plateau. The second one is more of something that we have AI, but humans in the loop are going to be critical along the way. The judgment work that we described earlier in the episode is going to be critical to everything that happens. It’s, I would call it the augmentation scenario. The AI will be a great augmentation tool for humans, but humans will never really quite stop being in the loop. Some of the gains that AI has are broadly distributed in society and in the startup, big corporation and small medium business world. Everyone will have access to them. We humans, are still very important. We have all these augmentation things, and AI is mostly benign. There will be a couple of issues, but honestly, at the end of the day, we’re just better. We’re better, faster, more data-driven, more factually current. We’re doing stuff faster, but humans

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The aviation industry is grappling with an array of challenges, from a backlog of planes, to safety concerns, and widespread labor shortages. WSJ aviation reporter Ben Katz joins host Luke Vargas to discuss how the sector is thinking about AI, plus the latest technology on display at the Farnborough International Airshow in the U.K. Further Reading Aerospace Startup JetZero to Start Building Futuristic Planes in North Carolina Airbus Comes for Boeing in Battle Over World's Biggest Jets Boeing Chooses Palantir to Boost AI Adoption in Defense, Space Unit Honeywell Aerospace CEO Says AI Works for Blueprints but Isn't Ready for the Cockpit Sixteen Airbus A380s to Undergo Inspection After Cracks Found on Airplane Wings Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.