Podcasts about Excel

Before we dive into the grim reality of the Russian collapse, a quick note on the channel art. I've been listening to your feedback regarding our AI thumbnails. The community poll was an absolute dead heat at 52% vs 48%, so we had to find a middle ground. We are shifting the visual baseline to a highly stylized, character-free 2D Anime aesthetic. It removes the uncanny valley, avoids the public figure issues, and gives us a distinct, unified look. It might not be a perfect solution for everyone, but it's a solid half-step compromise to keep the show looking sharp while we focus on the actual journalism. Let me know what you think in the comments.Now, onto the nightmare.In Episode 2.34, we document a state legally canceling its own existence. While the Western media panics over fake Excel spreadsheets, the Russian reality is terminal. We break down the 10% macro-drop in petroleum products and the glorious return of Soviet-style 20-liter gas ration cards in occupied Crimea. The Ukrainian Armed Forces aren't just holding the line; they have turned the R280 logistics highway into a mechanical graveyard using advanced drone swarms.But the real fatal damage is happening in the rear. We cover Finance Minister Siluanov's desperate 16-trillion-ruble sequester of the civilian economy, the mafia-style raid on Wildberries, and the absolute absurdity of Putin's own regional proxy having a daughter who is actively funding the Ukrainian military from Georgia. And the ultimate punchline? Russian oligarchs are now buying heavy anti-aircraft weapons to build their own PMCs. They aren't preparing for NATO; they are arming up for the post-Putin Civil War.The Empire of Clones is burning. Welcome to the GonzoLab.[SUPPORT THE SHOW & THE RESISTANCE]Car4Ukraine "Summer Sunshine" Campaign: Head over to https://car4ukraine.com and donate to my specific campaign. If you do, you will receive an exclusive, limited-run "Three Brothers" (Old Riga) steel badge minted specifically for listeners of this show. Let's put some trucks on the road!

In 1996, Ireland launched its first television channel broadcasting exclusively in the Irish language. Teilifís na Gaeilge, later renamed TG4, went on air on Halloween night. It aimed to appeal to both native and non-native speakers. The launch followed decades of campaigning for more Irish-language broadcasting in the country. Sinéad Ní Ghuidhir was the first presenter to speak on the new station. She speaks to Lorcan Clancy about the excitement of opening night.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Broadcast from Teilifís na Gaeilge (TG4). Credit: TG4)

In this episode of the Whole Systems Hospitality Podcast, host Kathy Sue McGuire sits down with Paul Marquez, Global Head of Specifications and Sustainability at Excel Dryer, to explore how restroom design connects to sustainability, public health, operational efficiency, guest experience, and whole systems thinking.From reducing paper waste to improving hand hygiene and lowering operational costs, this conversation highlights how overlooked guest touchpoints can become opportunities for more sustainable hospitality operations.CHAPTER BREAKDOWN00:00:32 — Day in the Life of a Paper TowelThe environmental journey of a paper towel—from forest to landfill in less than 24 hours.00:04:22 — Better Alternatives to Paper TowelsKathy introduces the environmental impact of paper towels and welcomes Paul Marquez.00:05:06 — Sustainability & Community ImpactHow Excel Dryer supports sustainability education and partnerships.00:06:00 — LEED, WELL & Green GlobeA look at Excel Dryer's certifications and sustainability commitments.00:06:41 — Transparency & EPDsWhy life cycle assessments and third-party standards matter.00:09:11 — Solar & Recycled MaterialsPaul discusses solar panels and recycled materials.00:10:25 — Understanding WELL CertificationKey considerations for building owners pursuing WELL certification.00:11:21 — XLERATOR & Performance StandardsHow standardized testing supports transparent product claims.00:12:45 — Indoor Air Quality & HEPA FiltrationA discussion on restroom air quality and filtration systems.00:14:48 — Clean Hands Save LivesWhy proper hand drying matters in public health.00:15:36 — The Hybrid Restroom ApproachBalancing reduced paper towel use with accessibility and guest preferences.00:17:40 — Cost Savings & ROIHow reducing paper towel use lowers operating costs.00:19:09 — Hidden Costs of Paper TowelsPlumbing issues, clogged toilets, and restroom downtime.00:20:26 — Addressing Noise ConcernsHow adjustable sound controls improve guest comfort.00:22:39 — ADA Compliance & Design FlexibilityAccessibility and high-traffic restroom considerations.00:23:45 — Community Art PartnershipsHow Excel Dryer partners with Artists for Humanity.00:25:42 — Life Cycle Assessment DataWhy measurable environmental impact matters.00:28:20 — Sustainability Awards & RecognitionHow third-party recognition validates environmental commitments.00:29:39 — The Future of Commercial Hand DryingIntegrated sink-mounted dryers and evolving restroom design.00:33:43 — Whole Systems Thinking in PracticeKathy reflects on Excel Dryer's sustainability approach.⸻

In the 1950s, Dutch journalist Willem Sassen recorded hours of interview with the Nazi war criminal Adolf Eichmann about his involvement in the Holocaust, before his capture in Argentina by Israeli agents.Willem's daughter Saskia Sassen tells Louise Hidalgo about the tapes, her memories of their secret visitor and the night the Israelis snatched Eichmann off the streets of Buenos Aires. This programme was first broadcast in 2015.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Nazi war criminal Adolph Eichmann during his trial. Credit: GPO via Getty Images)

Mental Models for Exceptional Capital Allocation by Mohnish Pabrai at Heilbrunn Center for Graham and Dodd Investing on April 21, 2026. (00:00:00) - Introduction (00:02:03) - Charlie Munger's mental models (00:03:54) - Model 1: The Bedrock model: Take a simple idea and take it seriously (00:04:51) - Model 2: Ben Graham's three ideas on markets (00:05:28) - Model 3: Do not overdose on Ben Graham; Poor Charlie's Almanack, Philip Fisher, and Pulak Prasad (00:06:27) - Model 4: Buffett's lifetime 20-punch card (00:07:15) - Model 5: Stay in the epicentre of your circle of competence; John Arrillaga (00:09:09) - Model 6: A high error rate is guaranteed in investing (00:09:26) - Model 7: Circle the wagons: the 4% rule (00:10:36) - Berkshire's 12 best decisions in 60 years (00:12:02) - Mistakes in investing: Ferrari, Progressive Insurance & Goldman Sachs (00:12:55) - Model 8: Do not cut flowers and water weeds; The Nifty 50 crash in the 1970s & Walmart (00:15:34) - Model 9: Be a shameless cloner; VIC & Dataroma; Gimat Gross (00:16:43) - Model 10: History does not repeat itself; Investing in Turkey & Reysas (00:19:50) - Model 11: Explain your investment thesis in 3-4 sentences to a 10-year old (00:19:58) - Model 12: You always need a rope to get out of the deepest well (00:23:14) - Model 13: Nick Sleep; Zen and the Art of Motorcycle Maintenance (00:26:52) - Model 14: Thou shall not use Excel (00:27:17) - Model 15: Use a pre-investment checklist (00:28:06) - Model 16: Be singularly focused like Arjuna (00:29:27) - Read the footnotes; Turn every page: Robert Caro (00:31:16) - Model 17: Enjoy hunting for needles in haystacks; Buffett's childhood entrepreneurial adventures (00:33:40) - Japanese Company Handbook; My introduction to Charlie Munger & Debbie Bozanek (00:37:27) - Model 18: Your deepest desire is your destiny (00:38:53) - Model 19: You should always have someone to discuss your investment ideas with; Li Lu (00:40:45) - Model 20: The mistress is always hotter than the wife!  (00:41:12) - Model 21: Neither a short-term borrower nor a long-term lender be (00:41:33) - Model 22: Introduce randomness into your life; Peter Lynch's One up on Wall Street (00:43:11) - Model 23: Be a Swiss Army knife (00:43:24) - Model 24-26: Focus on spin-offs, uber cannibals & spawners; Alpha-Metallurgical Resources (00:44:02) - Model 27: Arbitrage is wonderful; Transocean vs. Valaris (00:44:17) - Model 28: Heads I win, Tails I don't lose much!; IPSCO and CONSOL Energy (00:46:10) - Model 29: Focus on low-risk; high uncertainty bets (00:46:45) - Model 30: Do not skim off the top (00:47:23) - Book recommendations: Poor Charlie's Almanack, Influence & Excellent advice for living (00:47:41) - Investing in Turkish vs. Indian markets (00:50:17) - Follow your passion  The contents of this website are for educational and entertainment purposes only, and do not purport to be, and are not intended to be, financial, legal, accounting, tax or investment advice. Investments or strategies that are discussed may not be suitable for you, do not take into account your particular investment objectives, financial situation or needs and are not intended to provide investment advice or recommendations appropriate for you. Before making any investment or trade, consider whether it is suitable for you and consider seeking advice from your own financial or investment adviser. Views expressed on Chai with Pabrai are exclusively those of Mohnish Pabrai and not of any affiliated firm or organization.

A lot of leaders talk about “finishing well” like it is a slogan. Rob Acker has lived it, from a youth group of eight kids to decades of pastoral leadership, church planting, and the slow work of staying healthy. JD and I start with a personal story of how our lives crossed, then Rob takes us back to the roots: simple discipleship, opening the Bible as a teenager, and the way the local church quietly forms a leader long before anyone gives you a title. Rob closes with a leadership framework that sticks: character, knowledge, and skills, plus the daily practices that protect the character piece. If this conversation helps you, subscribe, share it with a leader you respect, and leave a review so more church planters and pastors can find it.Send us Fan MailWe want to help you find your next steps in ministry.Connect here with EXCEL. 

Gareth McGlynn speaks with Nate Weeks, Director of Estimating at Jewett Construction, a commercial general contractor based in Southern New Hampshire with operations across New England, upstate New York, and into the mid-Atlantic. Jewett has been in operation for over 50 years and remains family-owned into its second generation.Discussion Highlights:Career Progression: From zero estimating background at 27 to Director of Estimating in under a decade.The Shift to Leadership: Setting clear expectations, delegating effectively, and developing the team.Planning as a Sales Tool: Using a dedicated planning manager and Giraffe software to help developers optimise land use before estimating begins.Tech Stack: Builder, HubSpot, Building Connected, Procore, and Excel for estimating.The Bid Leveling Gap: Data entry from subcontractor bids as the biggest time drain, and what a real solution needs to look like.AI in Preconstruction: Using AI as a research aid while staying cautious about its reliability for cost decisions.You can connect with Nate via his LinkedIn: https://www.linkedin.com/in/nate-weeks-2409385a/More great conversations ahead. Stay connected with The Preconstruction Podcast for weekly episodes featuring voices from across the industry.

Are you a business owner feeling like the biggest bottleneck in your own company? Do you dream of financial freedom but find yourself buried in 20−an−hourtasks?InthisinsightfulepisodeoftheSpeakingPodcast,wesitdownwithBlazMarolt,anex−militaryofficerandWestPointgraduatewhohastransitionedhishigh−stakesleadershipexperienceintoamissionforbusinesssystematization.Blazhelpsentrepreneursscalingpastthe20-an-hour tasks? In this insightful episode of the Speaking Podcast, we sit down with Blaz Marolt, an ex-military officer and West Point graduate who has transitioned his high-stakes leadership experience into a mission for business systematization. Blaz helps entrepreneurs scaling past the 20−an−hourtasks?InthisinsightfulepisodeoftheSpeakingPodcast,wesitdownwithBlazMarolt,anex−militaryofficerandWestPointgraduatewhohastransitionedhishigh−stakesleadershipexperienceintoamissionforbusinesssystematization.Blazhelpsentrepreneursscalingpastthe500k mark to build robust operational infrastructures, allowing them to stay in their "zone of genius." We discuss the "two-week vacation test," the 80/20 rule of profitability, and why even the most successful companies often operate in a state of hidden chaos. Whether you're a solopreneur or leading a team of 20, Blaz provides actionable strategies to fix your systems, empower your team, and finally achieve the freedom you started your business for.     Timestamps Timestamp Topic Description 0:00 Welcome & Introduction to Blaz Marolt 0:45 Blaz's Mission: Helping business owners stay in their zone of genius 1:56 The Bottleneck Founder: Why things break down after $500k 2:43 Military Roots: Graduating from West Point and the Slovenian Military 3:42 Transitioning to Business: Boosting production by 50% in electronics 4:34 The IT Leap: Getting hired with only Excel, PowerPoint, and Word skills 5:21 Scaling a Food Delivery Giant: Growing 59x in the Balkans 6:22 The Chief of Staff Role: Doubling revenue for a US coaching company 7:03 The Young Founder Challenge: Overcoming perceptions in leadership 8:16 Military vs. Business Organization: The shocking reality of corporate chaos 9:53 The 80/20 Rule in Sales: Identifying loss-makers vs. profit-makers 11:37 Minimum Order Quantities: Why selling 100 components can be a disaster 12:54 Educating the Sales Team: Making them suffer through the production process 14:13 The Key Person Risk: Why your business shouldn't depend on one individual 15:52 The Soviet Machine Analogy: Planning for capacity and quality 31:19 The 250-Page SOP Trap: Why simple, one-page processes win 33:05 AI in Business: Using it as an assistant, not a replacement for thinking 35:01 The Amazon AI Mistake: Why quality assessment still requires humans 38:42 The 90-Day Operational Audit: What to expect in the first three months 40:53 Educating Employees: Why change management takes longer than system setup 42:52 The 20-Time Rule: Why you have to repeat instructions to be heard 60:42 Blaz's Final Advice: Defining your goals as a founder 61:16 Where to Find Blaz: LinkedIn and networking conversations 61:42 Outro: RoyCoughlan.com and the PodFather Network      

Today on The Gist, its Funny You Should Mention with comedian Janet McNamara discusses her YouTube special Not Smart Enough, opening up about her viral 2010 American Idol audition, navigating corporate accounting with dyslexia and ADD via advanced Excel automation, and her multiple clinical evaluations for autism. Also, a breakdown of why modern office social niceties fail neurodivergent workers, exploring the evolutionary shift from paper ledger bookkeeping to computerized workflows, and why the imminent rise of automation makes creative stand-up comedy a safer career harbor than corporate finance. Produced by Corey Wara Video and Social Media by Geoff Craig Do you have questions or comments, or just want to say hello? Email us at ⁠⁠⁠⁠thegist@mikepesca.com For full Pesca content and updates, check out our website at https://www.mikepesca.com/⁠ For ad-free content or to become a Pesca Plus subscriber, check out ⁠⁠⁠⁠https://subscribe.mikepesca.com/ For Mike's daily takes on Substack, subscribe to The Gist List https://mikepesca.substack.com/ Follow us on Social Media:⁠⁠⁠⁠ YouTube https://www.youtube.com/channel/UC4_bh0wHgk2YfpKf4rg40_g⁠⁠⁠⁠ Instagram https://www.instagram.com/pescagist/ X https://x.com/pescami TikTok https://www.tiktok.com/@pescagist To advertise on the show, contact ⁠⁠⁠⁠sales@amplitudemediapartners.com Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In 1997, Titanic, one of the most successful films in movie history, and one of the most expensive, was made in Mexico.  The director James Cameron and his production team built an almost full-size replica of the ship in Rosarito, Baja California, in the world's biggest water tank. Over the seven-month shoot, the budget soared to more than $200m, and there were worries about recouping costs. But when it opened, Titanic became the first film to gross over $1bn at the box office, and in 1998, won 11 Oscars.Luisa Gomez de Silva, then an assistant co-ordinator in the art department, talks to Jane Wilkinson about working on set.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Leonardo DiCaprio and Kate Winslet in Titanic. Credit: CBS/Getty Images)

Just before dawn, on 19 November 1984, an explosion at a gas plant in San Juanico, Mexico killed hundreds of people, injured thousands and destroyed buildings.Virginia Martínez Tellez was a young teenager at the time and talks to Jen Dale about how she and her family escaped the intense heat and fire of what's considered one of the world's deadliest industrial gas accidents.This programme contains distressing content.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: The San Juanico explosion. Credit: GDA/Associated Press)

Burnie and Ashley discuss Steam Deck, Existential Horror Technology, Stan Lee resurrected, YOU ARE A BRAIN IN A TANK WAKE UP, toddler sports day, Lego City Skylines, Minecraft vs Lego Worlds, and the Champion mindset.

In October 2014, indigenous women in Mexico won a landmark victory in their struggle for political rights. It came after years of campaigning by Eufrosina Cruz Mendoza, a Zapotec woman who had been prevented from becoming mayor of her local community. She believed a system of special laws, allowing indigenous communities to self-govern with their own traditions, had allowed men to maintain their patriarchal positions but left women marginalised. After Eufrosina challenged those traditions, the Mexican Senate amended the constitution to ensure indigenous women had the right to vote and stand in elections. She speaks to Jacqueline Paine. Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Eufrosina Cruz Mendoza. Credit: Pedro Flores Belmonte)

有位外語系同學提問：「家境不好，是不是畢業後該先工作，不要急著念研究所？」Joe 的回答是：家境好或不好，都該先出來工作。這一集，Joe 先從大學生與新鮮人的角度，分析畢業後到底該不該繼續讀研究所，以及在什麼情況下，「先進職場」反而是更聰明的選擇。到了 AI 時代，當學歷光環不再，職場上更看重的又是什麼？ ​ 延伸閱讀 〈人多的地方不要去（特別寫給還在學的讀者看）〉 https://www.darencademy.com/article/view/id/2731 ​ 相關集數 【EP301 我該念研究所嗎？什麼是大學時最該培養的能力？回應大學生的職涯煩惱！feat. 大人學 Jeremy】 https://youtu.be/FisOk2qLQss 【EP372 為何學歷的價值逐年降低？未來該怎麼證明自己的能力？】 https://youtu.be/cGJ1kxFx-AA ​ 大人學課程 【210 Excel 數據解讀與商業分析實戰工作坊】 https://reurl.cc/ppbXQa 【S003尋找天賦與熱情的系統化做法 (線上直播+實體演講同步)】 https://reurl.cc/YD5QZD 【V018用經營公司的思維經營你的人生】 https://reurl.cc/53La0V 【V040少年大人學：用遊戲思維建構人生策略】 https://reurl.cc/0mbnYl ​ 什麼問題想問Joe跟Bryan嗎？提問&合作信箱：podcast@ftpm.com.tw 如果你喜歡我們的節目，歡迎贊助我們：https://bit.ly/3kskVsZ 如果你喜歡這集節目，歡迎到Apple Podcast給我們五星評價，並留言給我們鼓勵！ ​ FB｜https://www.facebook.com/darencademy/ IG｜https://www.instagram.com/da.ren.cademy/ 大人學網站｜https://www.darencademy.com/ -- Hosting provided by SoundOn

Send us Fan MailMost new consultants walk in with work style blind spots they can't see – and their managers notice before they do.In this episode, Namaan – COO of Management Consulted – breaks down his framework for owning your first 90 days in consulting: how to identify your blind spots, read your manager, and carry yourself like someone who's been doing this for years.You'll learn:What your manager actually cares about (hint: it's not how hard you work)The 3 work styles that get consultants in trouble earlyHow to communicate answer-first and show executive presence from week 1Resources:Build your Excel and PowerPoint skills before day 1 with MC's flagship courseIs your team moving decisions or just moving slides? MC Executive Presentation TrainingFree Consulting Prep Just Got a Whole Lot BetterCreate a free MC account for access to step-by-step learning pathways, a brand new case prep course, and more. Download the MC app to prep anywhere.Connect 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

CRE brokerages have spent tens of thousands configuring Salesforce. Nobody uses it. The data is stale, the pipeline is fiction, and the analyst is entering last week's emails at 8pm to stay compliant.   Yaakov Zar, founder and CEO of Lev.com, has spent six years building a system to fix exactly that. AI-native deal management, not a retrofitted CRM. Lev ingests documents, extracts deal facts, resolves conflicts across sources, and surfaces a single source of truth - without manual data entry. The lender outreach problem is structural, not behavioral. Brokers don't fail to follow up because they're lazy; they fail because tracking 30 lender responses across email, Excel, and Salesforce is an analyst job that breaks at scale. Lev automates the intake, parsing, and quote matrix automatically. The platform is now open infrastructure. API, MCP connectors, and a CLI mean firms can build their own CRE operating system on top of Lev's deal data layer - rather than vibe-coding something that breaks under enterprise compliance requirements. Firms that keep running capital markets on spreadsheets are not just inefficient - they are building institutional knowledge in a format that walks out the door with every departing analyst. The structural advantage of organizations that systematize this data now will compound. For firms that wait, the gap will not close.   *** At GowerCrowd, we are bringing the most advanced AI tools to our clients for capital formation - and across other operational verticals too (like acquisitions). If you'd like to learn more about how we can assist you too, please reach out.   Subscribe to my newsletter and get access to this transformational intel before anyone else:  https://gowercrowd.com/subscribe Email: adam@gowercrowd.com Call: 213-761-1000  

How can Microsoft Loop make your team more productive? Richard chats with Karinne Bessette about the role that Loop components can play in making meetings where the agenda is live, generating work items in Microsoft Planner, and keeping key information up to date. Karinne talks about how Loop components can be connected to any M365 document, including Outlook, Word, Excel, and OneNote, but only for members of the M365 tenant. Loop is a powerful tool for productivity within the organization! Links Microsoft Loop Microsoft Planner Microsoft OneNote Power Automate Loop Components in OneNote Teams Polls Polls in Loop Loop Admin Policies Recorded April 27, 2026

In July 2000 an historic election in Mexico saw a change of government for the first time in 71 years. Vicente Fox of the National Action Party was elected president, defeating the Institutional Revolutionary Party, which had held power since 1929.Marketing strategist Francisco Ortiz worked on the Fox campaign. He speaks to Helen Ledwick about an election many thought impossible.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: A Fox supporter wears a Fox mask during election celebrations. Credit: Yuri Cortez/AFP via Getty Images)

Is AI really the next Google—or are investors repeating the last tech bubble? Blake and David dig into OpenAI's legal win, the accounting mechanics behind soaring AI valuations, and why cloud credits and paper gains may be inflating the market. They also explore what could make AI tools actually sticky for businesses, from workflow automation to personal finance and small-business use cases, and what all of this means for accountants.SponsorsDigits - http://accountingpodcast.promo/digitsR.E. Cost Seg - http://accountingpodcast.promo/recostsegOnPay - http://accountingpodcast.promo/onpay Maxima.AI - http://accountingpodcast.promo/maximaChapters(00:00) - TAP 488 (00:22) - Cash Flow Forecast Debate (00:29) - Road Show Updates (00:56) - Conference Rebrand News (01:31) - Nasdaq AI Summit Preview (04:29) - Livestream Check In (05:14) - Musk vs OpenAI Ruling (07:25) - AI Bubble Warning Signs (10:47) - Roundtrip Accounting Explained (15:38) - Paper Profits Hit Big Tech (18:28) - Do AI Giants Have Moats (27:15) - ChatGPT Personal Finance Push (30:54) - Agentic App Platforms (31:44) - Query Volume As Moat (33:00) - Claude Small Business Suite (35:20) - Cash Flow Forecast Debate (37:02) - AI Tax Workbook Example (41:03) - Personal Finance Is A Hobby (44:14) - Synthetic And Bench Lessons (47:16) - Why GLs Still Matter (50:43) - Klarna Rehires Humans (52:45) - Token Prices Will Rise (54:07) - Wrap Up And Next Time  Show NotesJury Dismisses Elon Musk's Lawsuit Against OpenAI Over Statute of Limitationshttps://www.technologyreview.com/2026/05/18/1137488/elon-musk-suit-openai-verdict/OpenAI Closes $122 Billion Funding Round, Largest in Silicon Valley Historyhttps://siliconangle.com/2026/03/31/openai-just-closed-record-breaking-122b-funding-round-brings-value-852b/Alphabet and Amazon Stakes in Anthropic Boost Profits by Billionshttps://www.bloomberg.com/news/articles/2025-10-31/alphabet-amazon-stakes-in-anthropic-boost-profit-by-billionsHalf of Google's and Amazon's 'Blowout AI Profits' Came From a Stake in Anthropichttps://fortune.com/2026/04/30/google-amazon-ai-profits-anthropic-stake-bubble-earnings-2026/What Microsoft's 10-Q Says About OpenAIhttps://om.co/2026/05/01/what-microsofts-10-q-says-about-openai/OpenAI Launches ChatGPT for Personal Finance, Will Let You Connect Bank Accountshttps://techcrunch.com/2026/05/15/openai-launches-chatgpt-for-personal-finance-will-let-you-connect-bank-accounts/Introducing Claude for Small Businesshttps://www.anthropic.com/news/claude-for-small-businessSasha Orloff (Puzzle) LinkedIn Post: Klarna, AI Agent Costs, and Accounting Quality Riskhttps://www.linkedin.com/in/sashaorloffKlarna Reverses Course on AI Customer Support, Resumes Human Hiringhttps://www.customerexperiencedive.com/news/klarna-reinvests-human-talent-customer-service-AI-chatbot/747586/Khosla Ventures Is Betting $10M on Ian Crosby, Whose Last Startup Bench Implodedhttps://techcrunch.com/2026/05/14/khosla-ventures-is-betting-10m-on-ian-crosby-whose-last-startup-bench-imploded/How Intuit Plans to Ride Out the 'SaaS-pocalypse' (CFO Brew Interview with CTO Alex Balazs)https://www.cfobrew.com/stories/2026/04/14/intuit-cto-alex-balazs-saas-pocalypseNeed CPE?Get CPE for listening to podcasts with Earmark: https://earmarkcpe.comSubscribe to the Earmark Podcast: https://podcast.earmarkcpe.comGet in TouchThanks for listening and the great reviews! We appreciate you! Follow and tweet @BlakeTOliver and @DavidLeary. Find us on Facebook and Instagram. If you like what you hear, please do us a favor and write a review on Apple Podcasts or Podchaser. Call us and leave a voicemail; maybe we'll play it on the show. DIAL (202) 695-1040.SponsorshipsAre you interested in sponsoring The Accounting Podcast? For details, read the prospectus.Need Accounting Conference Info? Check out our new website - accountingconferences.comLimited edition shirts, stickers, and other necessitiesTeePublic Store: http://cloudacctpod.link/merchSubscribeApple Podcasts: http://cloudacctpod.link/ApplePodcastsYouTube: https://www.youtube.com/@TheAccountingPodcastSpotify: http://cloudacctpod.link/SpotifyPodchaser: http://cloudacctpod.link/podchaserStitcher: http://cloudacctpod.link/StitcherOvercast: http://cloudacctpod.link/OvercastClassifieds REFRAME 2026 - http://accountingpodcast.promo/reframe2026Flowglad - https://cal.com/team/flowglad/flowgladWant to get the word out about your newsletter, webinar, party, Facebook group, podcast, e-book, job posting, or that fancy Excel macro you just created? Let the liste...

Mental Models for Exceptional Capital Allocation by Mohnish Pabrai at The University of Nebraska, Omaha on May 1, 2026. (00:00:00) - Introduction (00:02:11) - Charlie Munger's mental models (00:03:43) - Model 1: The Bedrock: Take a simple idea and take it seriously (00:04:06) - Model 2: Ben Graham's Fundamentals (00:04:59) - Model 3: Do not overdose on Ben Graham; Poor Charlie's Almanack, Philip Fisher, and Pulak Prasad (00:05:16) - Model 4: Buffett's lifetime 20-punch card (00:06:05) - Model 5: Stay in the epicentre of your circle of competence; John Arrillaga (00:07:52) - Model 6: A high error rate is guaranteed in investing (00:08:06) - Model 7: Circle the wagons: the 4% rule (00:08:44) - Berkshire's 12 best decisions in 60 years (00:09:41) - Mistakes in investing: Ferrari, Progressive Insurance & Goldman Sachs (00:12:10) - Model 8: Do not cut flowers and water weeds (00:13:02) - Model 9: Be a shameless cloner; VIC; Dataroma & SumZero (00:15:11) - Model 10: History does not repeat itself - but it does rhyme (00:16:16) - Model 11: Explain your investment thesis to a 10-year old in 3-4 sentences (00:16:41) - Model 12: You always need a rope to get out of the deepest well (00:20:50) - Model 13: Pursue quality intensely; Nick Sleep, Zen and the Art of Motorcycle Maintenance (00:25:31) - Model 14: Thou shall not use Excel (00:25:52) - Model 15: Develop and use a pre-investment checklist (00:27:54) - Model 16: Be singularly focused like Arjuna (00:29:31) - Read the footnotes; Turn every page: Robert Caro (00:31:44) - Model 17: Enjoy hunting for needles in haystacks; Buffett's childhood entrepreneurial adventures (00:33:41) - Japanese Company Handbook; My introduction to Charlie Munger & Debbie Bozanek (00:38:02) - Model 18: Your deepest desire is your destiny (00:41:15) - Model 19: You should always have someone to discuss your investment ideas with; Li Lu (00:42:53) - Model 20: The mistress always looks hotter than the wife!  (00:43:30) - Model 21: Neither a short-term borrower nor a long-term lender be (00:43:54) - Model 22: Introduce randomness into your life; Peter Lynch's One up on Wall Street (00:46:28) - Model 23: Be a Swiss Army knife (00:46:36) - Model 24-26: Focus on spin-offs, uber cannibals & spawners (00:47:18) - Model 27: Arbitrage is wonderful; Rupert Murdoch (00:48:26) - Model 28: Heads I win, Tails I don't lose much!; IPSCO and CONSOL Energy (00:51:43) - Model 29: Focus on low-risk; high uncertainty bets (00:52:56) - Model 30: Do not skim off the top (00:53:37) - Book recommendations: Poor Charlie's Almanack, Influence & Excellent advice for living (00:54:48) - Importance of the Bedrock model (00:55:30) - Finding great businesses (00:58:11) - Focusing on my deepest desire (00:59:23) - Berkshire Hathaway A-shares (01:00:35) - Intrinsic value of a company (01:02:17) - The Founders Podcast & Value Investors Club (01:05:34) - Pursue your passion (01:07:49) - Making of a Great American Capitalist by Lowenstein (01:09:05) - Family-run businesses; Walmart (01:10:24) - The Dakshana Foundation & Giving back (01:12:45) - Micron (01:13:43) - Warren's Too Hard pile & Charlie's pie-counter trips The contents of this website are for educational and entertainment purposes only, and do not purport to be, and are not intended to be, financial, legal, accounting, tax or investment advice. Investments or strategies that are discussed may not be suitable for you, do not take into account your particular investment objectives, financial situation or needs and are not intended to provide investment advice or recommendations appropriate for you. Before making any investment or trade, consider whether it is suitable for you and consider seeking advice from your own financial or investment adviser.

Eric Ries had a 40-page business plan. An Excel model so complicated it would crash Excel. A team of elite students, real investors, and a working product. What he didn't have was a strategy -- and he didn't realize it until after the startup collapsed. Episode page with video, links, and more The moment of clarity came in a Boston job interview. A panel of consultants asked what he'd learned. He gave them practical tips. They told him that wasn't strategy. Sitting there, he realized he didn't actually know what the word meant. That category error -- mistaking a polished plan for a strategy -- is the mistake that eventually became The Lean Startup. In this episode, Eric traces the line from that dorm-room failure to his new book, Incorruptible: Why Good Companies Go Bad and How Great Companies Stay Great. He argues that many of the so-called best practices founders are trained to follow aren't pillars of capitalism at all -- they're modern inventions with a poor track record. We get into the Whole Foods unraveling and why John Mackey couldn't simply cut prices, the prehistory of Costco through Sol Price's fiduciary duty to the customer, and what Jim Sinegal built into Costco's governance that has held for four CEOs and forty years. We also look at Novo Nordisk's industrial foundation structure -- a hundred-year-old design that makes companies six times more likely to survive fifty years -- and why most founders have never heard of it. A conversation about strategy, structure, and the quiet ways good companies go bad.

In 1944, as World War II was drawing to a close, the Mexican love song Besame Mucho crossed the Atlantic and became one of the most recognisable melodies of the post-war era. Its lyrics were daring for the time: an open plea for a passionate kiss.The song had been written years earlier by Consuelo Velazquez, a young woman who composed romantic melodies for pleasure but kept her authorship a secret, fearing it could damage her career as a classical pianist.When Consuelo's secret got out, her song Bésame Mucho topped the charts in the US and became one of the most covered songs in Spanish, with versions by The Beatles, Elvis Presley and Frank Sinatra.Stefania Gozzer speaks to her son, Mariano Rivera Velazquez, about his mother's unexpected worldwide success.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: A couple kiss by the West Gates at Pennsylvania Station, New York City. Credit: Three Lions/Hulton Archive/Getty Images)

What if the problem isn't your strategy, your people, or your tools, but the lens you're looking through? In this first conversation with Andrew Stotz, quality educator Balaji Reddie explains why so many organizations chase Deming's 14 Points and prizes but miss the philosophy underneath. He also gets into what changes once you start seeing your organization as one connected system. There are a few surprises along the way, like why his employees actually celebrated the day he got rid of performance appraisals. 0:00:01.9 Andrew Stotz: My name is Andrew Stotz and I'll be your host as we continue our journey into the teachings of Dr. W. Edwards Deming. Today I'm here with featured guest Balaji Reddie, who is an educator and trainer in teaching of Dr. Deming and quality management generally. Now the topic for today is a deeper perspective of the teachings of Dr. Deming. Balaji, how are you?   0:00:29.6 Balaji Reddie: I am fine. It's wonderful to see you this morning. I have been looking forward to this for quite some time now.   0:00:37.0 Andrew Stotz: Yeah. In fact, we've been talking back and forth in the past and then we had a meeting recently to get going on this because you've got so much to share. And one of the things I just said is a deeper perspective on the teachings of Dr. Deming. Maybe you could just give a little background of yourself for those people that have never heard of your journey. Maybe tell us a little bit about your journey, the Deming journey, as well as what you're doing now.   0:01:02.2 Balaji Reddie: All right. So I am an electrical engineer by profession and my first job which I got was in a lamp, a bulb manufacturing company which made automotive lamps. And that's where I chose to be in the quality department because I was being shunted around in all the different departments and the owner of the company asked me, "Where would you like to be?" and I said, "Quality." I don't know, when I look back why I chose. I think it appealed to me as an engineer and also the fact that I wanted to be a manager. It combined engineering and something to do with managing people. I don't want to sound dramatic, but I don't think I chose quality, I think quality chose me. But what I did after that was conscious. I did a postgraduate diploma in quality management, the first structured course in the country, and then went on to a Master of Science in quality management here in India.   0:02:00.2 Balaji Reddie: So that's been my journey here as far as working. I worked a lot. I used to teach part-time, but I made this switch 20 years ago to be an educator primarily and decided to put all my focus into creating the next gen of managers. At the same time, during the bit of a free time that I have, I do consult, but that's not the core profession of mine. So, yes, I'm an educator and a trainer. You can say that. I teach quality management, anything to do with operations, supply chain, et cetera, but there's always been a Deming slant to it. Along with that, I've also liked to... Because I went into the works of Dr. Juran, I got a good chance to meet with him and be in touch with him. It was only the last six years of his life, but I think he had very little time to give me, but he gave me time. So I have a good perspective of both these gentlemen. And if you know quality, they're the pioneers.   0:03:01.5 Andrew Stotz: Yeah. And I'm curious, when you first started out with the degrees and the, as you mentioned, getting a diploma and then a master's, was Deming front and center in there or was that a secondary thing? What was it like in the beginning?   0:03:19.6 Balaji Reddie: Oh, my entire focus was actually Deming. I needed to be qualified in that. I wanted to qualify myself in quality, that's what I meant here, because there was no... I was looking for a structured course on the subject. You had these training programs, certificate courses, but this one caught my attention when they said we have a diploma in quality. And part of the course was we had to, there was a project like a dissertation, and we had to show how we implemented this in our companies where we were working. And for those who were not working, they were provided companies where you go and actually implement these. So it was a win-win. So the company gained and you gained. That's how it was. That's what I liked about that course. Same with the masters. It was a complete two-year course. This was a year-and-a-half or three semesters. That was more elaborate, the masters. So, yeah.   0:04:18.0 Andrew Stotz: And what is the state of Deming and the teachings of Dr. Deming in India? We know that many companies in India have implemented the teachings of Deming over the years. But of course, there's a lot of people that just know nothing. I'm just curious, what is the state right now as far as the teachings of Dr. Deming?   0:04:40.3 Balaji Reddie: Oh, I'd like to... Just a slight correction there. We have the highest number of Deming Prize winners, but that does not necessarily mean that they're implementing the teachings of Dr. Deming. In fact, many of them after having got the prize... I worked in a company, we were suppliers to one of them. And when they came to do a vendor assessment to our factory, obviously there's a lot of buzz. Everyone in the company, they called me the Deming man. They used to call me that. And so when these guys came down and they were talking and when they gave their business card which had the Deming Prize logo, so they said, "Oh, we have... You know, Balaji is here and he's our Deming man." So who's he and what is this? And so they came and met me and they said that, "We got the Deming Prize." I said, "Excellent." But I said, "Just because you got the Deming Prize, I mean, have you worked on the Deming philosophy?" "Isn't this the same?" And I said, "No." And I, of course, joked with them, and they said, "So how do we learn?" And I said, "Pay me." [laughter] Anyway, yeah, then we got talking and they realized that there was such a big gap in what they were doing. For instance, when I spoke to them about performance appraisals and having quotas and things like that, they were like, "What?"   0:06:04.9 Andrew Stotz: Interesting. And when we talk about the Deming Prize, when I asked you that, we're talking about the Deming Prize which is offered by the Union of Japanese Scientists and Engineers through their Deming Prize Committee. This isn't something done through the Deming Institute.   0:06:12.3 Balaji Reddie: No.   0:06:19.7 Andrew Stotz: Yep. Okay. And do people study Deming there in India anymore or is it fading out or...   0:06:26.7 Balaji Reddie: Well, yeah, that's what I said, they do know. The good part is that because of the fact that the Deming Prize winners are there, at least they know about Dr. Deming. And then they're curious to know, "Oh, what did he teach?" Because again, they've been given that perspective that he taught, well, wrongly, PDCA, and he focused on the 14 points. And then when they read the 14 points and then they get... Because when you read it just without understanding, you can actually... It can put off certain people. You may get a little repulsed and say, "Oh, my God, what's he saying?" But then there are certain people who get intrigued and say, "Wait a minute. This is challenging. He's saying that we need not have quotas? Then how are you going to get work done?" And that's where the questioning begins. And there have been normally these trends where some companies where they called me over, I shall not name one of them, one of the students I was teaching in class and I was talking about the 14 points, and then she comes up to me and she says, "I've spoken about you to my father, and he's working in this company, and they're going for the Deming Prize. He wants to meet you." And then she brings him to the college the next morning and then we had a lovely discussion. And he said, "We've been discussing the 14 points." And I said, "You know what? You're putting the cart before the horse. You need to discuss profound knowledge first." So he said, "I'll put you in touch with my HR, the human resource." And then that lady got in touch with me, then we had a good chat and I explained to her and she understood very quickly. Incidentally, Andrew, that's something very amazing, when I speak about these things to the HR people, they take to it like a fish takes to water. They say, "You're right. What can we do about appraisals? Appraisals are wrong." But they also know they're shackled. They do not have the authority to break and come out of it. There have been some cases where they've been bold enough, but many of them... That's one of the things I've seen over these last 20 years that I've been teaching, that everybody principally agrees, but they also say that we're bound by it.   0:08:37.6 Andrew Stotz: That reminds me when I attended my first seminar when I was 24, and I was very intimidated by all the people in the room. I was just fresh out of university, working at Pepsi in Los Angeles. I flew into Washington, D.C., and so I sat right in the front row and I just decided I'm not gonna look at anybody behind me because they're all bigwig executives. But then when I heard Deming really show no mercy and really be tough to them, I was like, "Wow, wow, this is interesting." And he was getting to the... As a factory supervisor, which is what I was at Pepsi, I could just see he was getting to the heart of the matter. And so, yeah, a lot of things are very obvious to people in the factory, but then it's the leadership that is an issue. I'm curious when we think about... Let's imagine that someone listening to this has never heard of Dr. Deming and it's their first time, they stumbled upon this, they're hearing you speak. They're gonna ask the question, "Why does this matter? What benefit do I get from this?" How would you describe that to someone who knows nothing about Dr. Deming and his teachings?   0:09:59.3 Balaji Reddie: Oh, well, when you start getting aware of what this man had to say, let me tell you, when you start actually getting to it, you'll find that what you've been missing all this time in life. And then when you actually get to implement this, it'll be way, way better than where you are right now, sometimes totally in a very, very different direction. And you begin to realize that you had an illusion of knowledge, that you thought you were correct, and then suddenly a new perspective comes in. Just to make a point here, I don't want to be boastful about this, but I'm really proud to say this, that in all the companies that I worked, I removed performance appraisal. None of the companies I worked in had performance appraisal. And the day we removed it in one of the companies, there were actually celebrations.   [laughter]   0:10:56.7 Andrew Stotz: Yeah. Which for many people listening that don't know anything about the teachings of Dr. Deming may think, "That's crazy, because I thought that we run business through performance appraisals, KPIs, and the like." One of the ways I was thinking when you were just speaking was it's a little bit like Deming's... You're a fish, and Dr. Deming is a guy that's gonna come up and tell you, "Oh, by the way, you're surrounded by water." And you're like, "Wait, what do you mean? What's water?" And then all of a sudden he brings this awareness like, "What am I swimming in? I am swimming in something, and it's called water." And it's like everything that's going on, the concept of how we learn, the concept of variation, the concept of psychology, it's like all of these are foundational things that we've been swimming in, but we really haven't been paying attention to. And I think he woke me up to a lot of that. So what should we talk about today? What do you got on your mind?   0:11:55.7 Balaji Reddie: Well, I presume that the audience would be someone who's read about Deming, or if they have not read, I can go it either way.   0:12:05.9 Andrew Stotz: Yeah, I mean, I would say just let's go into what your learnings are and what you want to teach us today and share with us, and then people can follow along.   0:12:17.4 Balaji Reddie: All right. So let's begin with what he meant by Profound Knowledge, because that was something he put together only towards the end of his life. I'm reminded of a few things that led to me thinking about these things. One of the very first books that was written on him was by Mary Walton, The Deming Management Method. And with due respect, she was an excellent journalist, and so she followed him around. Everyone was intrigued to know who this man is because he had just gained popularity. If Japan Can... Why Can't We? And so she wrote this book, I think as early as '84, if I'm not mistaken. And she followed him around for almost three years before she actually published the book. So she attended four-day seminars, and she's trying to understand what this man was. So the biography bit of it was very nice. But if you go there in the preface and in one of the chapters, there's a very interesting conversation where she says, "I asked Deming that why don't you set up a body, an organization? Why are you doing this all alone?" And he didn't say a word to her, and he just mentioned to her, "I'm good." So I believe he was still looking for the answers to offer something to the world. He had it all in uncoordinated stuff here and there, but that came much later, I think in 1989, when he finally put it all together and called it Profound Knowledge. Because that was when a year, a month or so before he passed away, he set up the Deming Institute. I think he thought he was ready now to leave behind a legacy that others could build upon, right?   0:14:08.0 Balaji Reddie: And so that he called it... Again, I'm looking for the missing link here—. Apparently, when he wrote it, as he called it deep knowledge, but it was someone who gave him the word profound, and that's how the name stuck. So I'm still trying to find out who did that. I saw this in one of the letters to Henry Neave, where he was writing to all of his colleagues, he called them, and taking feedback from them. And in that, he said that, "I profess this is deep, this is wide." And somebody said, "It's profound." I forget. I really want to find out who it is. I asked Bill Scherkenbach, and he said, no, it wasn't him. Henry, of course, no. I asked Bill Latzko, and he said, "No way. I never said that." So I really don't know who said it, but he christened it "profound." And we all know now, it sounded very pompous to begin with when you hear profound, and then you say, "Wait a minute." When you start getting into it, you say, "He's right. There's no other word to describe this. It is profound." So what exactly is Profound Knowledge? Now, it's a different way of looking at things around you. And especially he designed this or created this for man-made systems, organizations that you and I work in, helping us to look at things differently, right? And that's why he said it's a different lens. And when you see things differently, you ask different questions, right? When you ask different questions, you get different answers. When you get different answers, you draw different conclusions. When you draw different conclusions, you take different decisions. And when you take different decisions, that's when you get different results. It's insanity to expect different results by asking the same questions every single time. All right.   0:15:53.8 Balaji Reddie: Now, what exactly is, again, what do you mean by this whole thing, the lens? He brought together four seemingly disconnected sciences, right? He never invented any single one of them, but he saw the interconnections. All right. And the four sciences, he felt that if you had good knowledge, working knowledge of these four sciences, you need not be an expert in them, just enough for you to understand what's going on around you. All right? And in no order of importance, he had his title for each of those sciences. One was he called it appreciation for a system, which I would like to say very simply is connectedness, right? Because when people say systems thinking, okay, then you have the systems thinking experts who jumped into the picture. And I think they were caught napping. To be quite honest, Andrew, I think the people from the world of management were suddenly caught napping, and the experts were completely caught napping because they realized they'd missed the bus. Here's this man who caught everything together and put it into place, right? And so when they were... When they said systems thinking, so the systems experts came in and started trying to find out, "Oh, but he missed out on this, and he's confusing this with that." That's where it is. Dr. Deming knew where to start. All right? He said, "Yes, of course, it's all about systems, appreciation for a system, the fact that nothing exists in isolation." So I would like to say connectedness. Everything's connected to everything. When you start having that systemic approach, you realize you're not dealing with events, you're dealing with eventualities, and that there are always a huge myriad of inputs that create the outputs that you see in front of your eyes, right? And there's so many other attributes that they're separated in time and space, et cetera. We can talk for this forever. But the short word here is connectedness. Second...   0:17:56.1 Andrew Stotz: And I would say that the systems experts retreated soon after because they're nowhere to be found when we look at it these days, because everything's divide and conquer.   0:18:07.6 Balaji Reddie: Yes. Yeah, because there were people like Russell Ackoff, Stafford Beer was mentioned many times, and then their books. Now, I went on to read their books and I found, yes, they were going deep, but Dr. Deming knew where to draw the line and said, "That's it. Please don't go beyond this," and it depends on where you are, what you want to study. So draw your line around that and say that's it. And I think that thinking came from the next science which I'm talking about, which is understanding of variation, right? Now, although we say understanding of variation and people talk about the control chart, I think that's just the manifestation. If you look at the philosophy behind it, what Walter Shewhart actually was trying to do was to draw a line between when to act on the process and when to leave it alone, right? He came out with... He demarcated, and that's where it turned into the control chart with data. But broadly, Deming started applying this everywhere, right? He said that there are some things which are in my control and some things out of my control, and so he drew a line. And same with systems thinking, that how big and how deep should I go? And that's why he said every system must have an aim. Without an aim... So the aim and the purpose decide where you're gonna stop. You can't just keep on saying, "Oh, yeah, finally, okay, the whole world is a system." Fine, great, I get that. But I'm trying to study this, okay? My company, my organization, this process, these people. So you draw the line and say, "This is my purpose, so let me restrict." Again, I repeat, he knew where to stop. People tend to go overboard. And so he always said, "Begin with the aim, begin with the purpose." The purpose is the reason the system exists, and the aim is the direction in which you're headed. So you keep going there, keep revisiting that to let yourself remind yourself that I need to stop right here. Okay, and that's it. When I come to it later, because he said... Coming to the third part of Profound Knowledge, where he said you must have a theory of knowledge.   0:20:13.4 Balaji Reddie: Now, when people hear the word theory they get very put off. At least in my country, the broad doctrine is that theory is the opposite of practice. And so they think that theory belongs to the books and theory belongs at home. And when you come into the company, we all believe in being practical, right? And as you go through what Dr. Deming had to say about theory, you realize theory is a guide to better practice. And all the great practitioners are actually theorists. It's just that they don't know it, and we need to remind them. I've had enough of experience on this in my own company. And I remember when I turned on the light bulb for one of the very, very senior people in my company, he went completely quiet. He did not say anything, but I loved the way he reacted or responded to this when he started doing things very differently after the interaction that we had once. So that's with theory of knowledge. And...   0:21:19.9 Andrew Stotz: And would you say that theory of knowledge, would you correct my description of it, which is that you need to have a method of... You need to understand how you acquire knowledge?   0:21:40.1 Balaji Reddie: Yeah.   0:21:40.2 Andrew Stotz: And you gotta figure out, because acquiring knowledge, for instance, as an individual, we can play around lots of different ideas and experiments and stuff like that, but acquiring knowledge within an organization is a much harder thing. And so first is the idea that there's a level of rigor that you need in an organization to make knowledge stick.   0:22:06.9 Balaji Reddie: I think it's more about awareness. When you become aware of how you're converting information into knowledge. When you... He makes you aware of that, right? Dr. Deming gets you aware, he makes aware, "Okay, okay, wait, what's happening here?" Now, that method and all turned out to be the Plan-Do-Study-Act, whatever you call it. But he helped you understand how you're doing this, right? And you become cognizant. You get your cognitive behavior, you get very aware of things happening around you, right? You start asking the question, "Why? Why is this happening?" And then you get to the bottom of it. "Oh, when I do this, I get this." And that's when it becomes powerful for you. And then you also, "When I do this, I do not get this." And the more the theory fails, the more powerful it gets for you, because you know where it fails. So that's the awareness thing. So connectedness, being aware of the fact that it's beyond just numbers. It's about where, the variation bit, the third bit is about awareness, like I said, about learning, and the fourth, of course, about people. And he said here that all of us are born with a learning system, right? Each one of us has a learning system, a system of learning, but every single one of us has a different system of learning. We learn differently, and we learn at different speeds, at different paces, right? And so understanding the learning process of a person and then putting that person on the right job, right? He said you have to stop that person from working, and that's where joy in work comes in. People enjoy their work. I think the bottom line there is empathy when you start understanding why people do what they do, whether it's your people in the company, the customers, your suppliers, the entire system. So he says the learning process of every person needs to be understood. You want to control the market, you need to understand what makes the customer tick. You want to keep the suppliers with you, you want to understand what makes the suppliers tick, right? And what makes them tick.   0:24:23.3 Balaji Reddie: So that's the fourth part, which I would put as the word empathy. Trying to empathize. So putting this all together, he said that's what he called as Profound. So if you look at it in a broad sense, connectedness and empathy are very philosophical, and the variation and theory are very scientific. So he wanted us to be scientific and philosophical simultaneously. It's not either-or, it's and. And that's difficult to do, right? You have the big divide. You have a set of people who say, "Oh, I believe only in data. Show me the data, show me the results." And then there's a whole other set of people who says, "You gotta feel. You gotta feel for the company. Motivate." Yeah, but neither is wrong, but neither is complete. And this is complete. So this is where I found that I think we could begin, that we need to look at all these four sciences together. And of course, then came the 14 points which he laid out for us. Now, these 14 points, now if you look at them, because I just discussed the four... Of course, I've not gone into depth of each of the sciences, but I think good enough to understand what we are trying to deal with here, then you'd see that the 14 points are actually 14 consequences of this way of thinking. That you don't try to do the 14 points. When you start thinking this way, you end up with the 14 points, right? And there are some things which need to be done, right, and we need to start somewhere with this. And one of the main things that he always said is that people need to be educated about this, that people need to learn about this. And so education and training is important even when it comes to profound knowledge. And he said someone has to take the lead, all right? Someone has to get things done. And so that was his point number 14, that create a critical mass of people in the company that understand, believe, and will work towards these 14 points, right? So I'm gonna begin right there.   0:26:43.1 Andrew Stotz: I was just thinking about his saying, "One need not be an expert in any one point, [chuckle] any one of these areas." With the System of Profound Knowledge, the more I've studied it recently, which I've been working on a project recently where I had to go back to the System of Profound Knowledge, you really see that he's trying to provide a coherent, holistic system.   0:27:16.1 Balaji Reddie: Yes. I call it as a theory of leadership and management.   0:27:23.6 Andrew Stotz: Yeah. And then you start to realize that if you can understand these four things, which isn't that... It doesn't have to be that complex, it can be pretty amazing. And I know one part of my business is investing, which I do on behalf of my clients. And one of the things that makes me stand out as unique is that I don't get distracted by the random variation in the markets. And so that doesn't mean that I'm gonna get it right all the time, but what it means is that my mind is much more clear when I understand. And as I tell people about variation, I say, if you think about just your birth, the beginning of your life is a random event. You had no influence over that, who you were born of. And therefore we at least know that randomness plays one role in your life. But when you start exploring the possibility that randomness is all around you just like water, it just wakes you up and you start to realize, "Aha, I've been reacting to things," and punishing and rewarding and all of that stuff that's happening in companies. And what I'm really doing is I'm just chasing my tail. Or as Dr. Deming would say, putting out a fire. A man could run... A manager could run... Could put out fires their whole career and never improve the system.   0:29:02.8 Balaji Reddie: Yeah. A lot of activity, no work.   0:29:04.5 Andrew Stotz: Yeah.   0:29:06.2 Balaji Reddie: Okay. Incidentally, when you said about investing, one of my students who did something fascinating, I've yet to get to the bottom of it, I never sat down and asked him how he did it, but he used control charts for the stock market. And one day he explained to me, he was trying to rather, because I never... I'm not into all of that investing. That's done by my wife. I just sign the papers and she puts it in. So I... I mean, I might as well be shown the Constitution and say, "Okay, this is what it is," you know? But yeah, so he... I remember sharing with him and he said, "Can I use this for stock market?" I said, "Look, son, I don't know how this works, but I presume what you can do is this. If you had yesterday's Sensex numbers and you have today's, then you can draw a control chart for the differences, you know? And then you get an upper limit and a lower limit. And then if today's closing is so much, it can rise up to the upper control limit, that is the difference. You can add the difference to today's closing and say it can rise to so much, it can fall by so much, and likewise to the lower control limit." And then his eyes just lit up and he said, "I know what to do." And that was it. And I didn't meet him for a week. And a week later, I meet him and he says, "I want to show you something." And he opened his laptop and there were control charts all over the place and I just couldn't figure out, "So what was all this?" And then he said, "I've been following these. There are some blue chip companies and there are some..." I don't know, I don't understand these things much, but he said that, "I'm drawing a control chart for these and so I know that when it crosses the upper control limits, that's the max I can get for the share, so I sell."   0:30:55.7 Andrew Stotz: Yeah. I mean, the hard part... The stock market is purely random most of the time and it's a challenge. But one of the things... I gave a speech to my investors and I did control charts and I did it as a way of helping them understand the markets.   0:31:04.2 Balaji Reddie: Okay.   0:31:12.7 Andrew Stotz: To predict the markets is hard.   0:31:15.7 Balaji Reddie: It's hard.   0:31:16.4 Andrew Stotz: But the control chart allows us to kind of.. It allows us to understand that most of the variation is just normal ups and downs.   0:31:24.8 Balaji Reddie: Yes.   0:31:26.5 Andrew Stotz: And so don't freak out about it. That's the first thing that really helps me. So that area of variation I find very fascinating.   0:31:34.7 Balaji Reddie: Very fascinating. I used it for COVID data, by the way. And there was a lot of criticism about that, but I knew I was going in the right direction because I was plotting the charts for the percentage positive and not the number of cases that were being tested positive every day. And so if the percentage positive lay within limits, then we were safe. I mean, everyone wants a zero, I get that. But I'm just saying here, having said that we're collecting the data and we are turning out so much of positive every day, then it should lie within certain controllable or predictable limits. And when it crosses the limit is when we get a little worried. And that's what I used this for initially. I remember it was Lloyd Provost who stood by me, whereas the other practitioners were saying, "No, you cannot use control chart for COVID and for data and for epidemic and pandemic." Whereas Deming himself used it for an epidemic of cholera somewhere. I read it in his work and where he used the c-chart and he saw that areas where the points were outside limits and then they tested the water and well, well, whatever it was, it turned out to be that he found the special cause and blah, blah, blah. So that's what gave me the idea of using the control chart for COVID and it was quite fascinating.   0:32:56.5 Andrew Stotz: Yeah. Yeah, unfortunately there wasn't a lot of independent thinking during that time.   0:33:02.5 Balaji Reddie: Yeah. [laughter]   0:33:03.0 Andrew Stotz: Real serious groupthink at that time. So I had my experience in my PhD research and my job as an analyst all my life where... And I teach my students believe nothing, believe no one, demand evidence. And so I'm constantly digging and that's just the heart of being an analyst. But when I go back... I want to go back to when I was starting at Pepsi. The reason why my boss recommended me to go to the Deming seminar was simple because I knew how to work a computer. And that was 1989 when I went to work at Pepsi. And what I had, all of these loaders that were loading up trucks with Pepsi each night. We would load about 80, 90 trucks each night. And in the heat of the summer, we would work till 2:00 or 3:00 in the morning, but generally we would finish at 11:00 or midnight. But they were just... I would go to the drivers in the morning and then the drivers would come back in the afternoon and complain that the product that they needed was not on the truck. And there was just... And I went to the loaders, they go, "I put it on the truck. I don't know what you're talking about." And so there was this battle between the night loaders and the truck drivers. And so what I just did originally was I just started... I did inspection. The first thing I did is I said, "Look, before you close the doors on the trucks at night, I just want to count myself to understand what's happening here." And then I started keeping a record of that and I put that in Excel, it was Lotus 1-2-3 at the time, and then I put up charts of each person's error rate each night. And so we had a long chart. And I never actually even told them what I was doing, I just put up on the wall. And then they started looking at it over time and talking about it and then asking me questions. And it wasn't for the purpose of blaming, it was the purpose of just understanding.   0:35:01.2 Andrew Stotz: But then what we really started to see was that some people were much more accurate than others. And then we started to ask the question, "Well, how are they doing it?" And then they explained how they kept records of what they were doing and all that. And so we started to see that we could improve this. And we started to improve those numbers quite dramatically until we got to the point where I told the loaders when they were done that they were to lock the trucks and seal them and the drivers were not allowed to open them. They had to take them as is. And when everybody realized we really have to build from the beginning that this is loaded right, then we started to have massive efficiency. In the number of... Let's say you have 50 or 100 truck drivers that come in at 5:00 in the morning. It could take you till 9:00 AM to get them out the door if they've got problems and they're checking their trucks and all that. But if you've got it set right and you've done it right, we were able to rush people through the door and the drivers would get out to the LA freeways much earlier and that makes a difference for the whole day. So that was my first experience with it all. And then my boss just said, "Well, seems like you know about statistical quality control." I said, "I have no idea. I have no idea what that is." But he said, "You should go to Washington, D.C. And study with Dr. Deming." And that's my little story.   0:36:20.4 Balaji Reddie: Oh, wow. Okay.   0:36:21.6 Andrew Stotz: So how would we... What's the best way to wrap this up and think about what somebody who doesn't really necessarily have experience with the System of Profound Knowledge, you've given them some good overview. What would you like them to take away from this?   0:36:39.2 Balaji Reddie: Well, if you have now come to know about what this is, I think you could go to the W. Edwards Deming Institute website and you could subscribe and start looking into the learning pathways, systems thinking, there are a lot of catalogs available there and they've done a great job of putting things together. So they could do that reading, of course, you need to start reading, but the danger in reading Dr. Deming's work is it could put you off sometimes. And I would recommend a good place to start reading and understanding the Deming philosophy would be Henry Neve's book, The Deming Dimension. It's a very good start, one of the best introductions. You could always build upon that. So along with having Out of the Crisis, The New Economics, and Essential Deming, which was put together by Joyce Orsini, these are the three essential Deming books which contain papers, his own works, and then use Deming Dimension as a guide, so to say. You could read the books together and you could read profound knowledge to begin with. And once you get a good idea about what there is, then the question comes is where do we start? And that's where I just ended by saying that we start at point number 14 about creating a critical mass and take on leadership, right? So somebody has to take the lead. So what we could do is, I think the next time we meet, we could begin with that, how do we start? So we'll talk about the principles of leadership that W. Edwards Deming spoke of and what did he expect the leaders to do once you've decided or you've started seeing things differently and you say, "No, I need to do something about this. I need to start somewhere." And so we'll start with the principles of leadership. That's the way I look at it.   0:38:44.5 Andrew Stotz: Fantastic. Well, I look forward to our next conversation, how we can start to think about how we take this information and make a better world and make a better company, feel better. And so from everybody at the Deming Institute, I want to thank you again for this discussion. And for listeners, remember to go to deming.org and jump into DemingNext to continue your journey.   0:39:09.7 Balaji Reddie: Yes.   0:39:11.1 Andrew Stotz: It's an exciting tool. And this is your host, Andrew Stotz, and I'll leave you with one of my favorite quotes from Dr. Deming, and that is: "People are entitled to joy in work."

If you have ever been to an Excel Discovery Center, then you have probably met today's guest. From its beginnings, Geoff Wells and his wife Sharon have been a part of Excel Leadership Network. As a retired Army officer, he is often referred to as "The Colonel." Geoff's life story is worth listening to. For anyone that has been lucky enough to meet him, you walk away from that meeting knowing that he is passionate about supporting church planters and how Excel plays a role in expanding God's kingdom. Listen and be encouraged.This episode originally aired on March 1, 2022Send us Fan MailWe want to help you find your next steps in ministry.Connect here with EXCEL. 

Learn how Claude can help Amazon sellers organize workflows, automate tasks, improve keyword research, build smarter systems, and save time in business and life. AI is no longer just a tool for writing quick prompts or brainstorming ideas. In this episode of the AM/PM Podcast, Bradley Sutton sits down with Andrew Bell and Zoe Lu to explore how Amazon sellers can use Claude to organize their business, simplify daily tasks, and create repeatable systems that save serious time. Bradley opens by sharing his own failed attempt at using Claude for a presentation, proving an important point: AI is only as good as the context, instructions, and structure you give it.   Andrew breaks down what makes Claude different from a basic chatbot experience. He explains how Claude Chat, Claude Co-Work, Claude Code, skills, sub-agents, and scheduled tasks can help sellers move from simple conversations to actual workflows. For Amazon sellers, this can mean pulling keyword data, organizing it into Excel, mapping search intent, building product truth cards, judging keyword relevance, and even using Claude to support listing optimization, PPC planning, and product research.   Zoe then brings the conversation back to a beginner-friendly level by explaining how sellers can get started. Her advice is to install the desktop app, use Claude Co-Work, create a “brain” folder with personal and business context, connect the tools you already use, and turn repeated tasks into projects, schedules, dashboards, or skills. From managing calendars and emails to organizing files, creating daily briefs, analyzing customer feedback, or preparing for meetings, Claude becomes more powerful when it understands your goals and connects with your workflow.   The biggest takeaway is that Amazon sellers do not need to become AI experts overnight, but they do need to start building AI into their operations. Claude can help reduce busywork, organize messy information, create smarter processes, and uncover insights faster when used correctly. For sellers who want to stay competitive, the opportunity is not just using AI once in a while, but building repeatable systems that help them work faster, think more clearly, and grow smarter. In episode 524 of the AM/PM Podcast, Bradley, Andrew, and Zoe discuss: 00:00 - Introduction 02:58 - Claude Vs. ChatGPT: What Amazon Sellers Should Know 04:33 - Claude Chat, Co-Work, And Code Explained 08:31 - Using Claude Skills Like Repeatable SOPs 12:49 - Turning Keyword Research Into Excel Workflows 16:18 - Product Truth Cards And Keyword Relevance Checks 19:02 - Helium 10 MCP And Faster AI Workflows 20:12 - Simple Life Automation Ideas With Claude 25:59 - Zoe's Beginner Guide To Getting Started 29:02 - Building A “Brain” Folder For Better Outputs 35:23 - Tasks, Projects, Scheduled Agents, And Dashboards 42:31 - Q&A: Helium 10 Claude Connector, Agents, And Claude Workflows

Get Mohnish's 9 investment principles: https://clickhubspot.com/kwdo Episode 827: Shaan Puri ( https://x.com/ShaanVP ) sits down with Mohnish Pabrai to break down the mental models that made him a billionaire value investor.   — Show Notes:  (0:00) Intro (1:25) Mental models of the top 1% (3:38) The mistress is always hotter than the wife (6:37) Introduce Randomness in your life (10:47)  Humans are poor at copying (20:13) Take a simple idea seriously  (23:02)  Be and inch wide and a mile deep (30:29)  Never use Excel (35:03) Wait for fat pitches (39:38) the stock market is like a church with a casino  (44:01) Paying $650,000 to have lunch with Warren Buffett (45:43) The cautionary tale of Rick Guerin (47:22) The inner score card (49:25) The future of Berkshire Hathaway (51:29) Mohnish's best investment (1:02:39) The hardest question (1:06:16) How to beat the index (1:11:25) Mohnish's stock picks for 2026  (1:22:26)  S&P 500 (1:24:57) life advice disguised as investing advice (1:29:32)  Studying the greatest investors  (1:37:51) if you remember nothing else, remember this  — Links: Mohnish Part 1: This Guy Copy-Pasted Warren Buffett's Strategy (And Became A Billionaire) Mohnish Part 2: Go from $10,000 to $1M in just 3 years  The Dhando Investor - https://a.co/d/0hkx1t8g  — Check Out Sam's Stuff: • Hampton (joinhampton.com): My community for founders. Average member does $25m/year. Many of the guests are members. Get after it...apply: http://joinhampton.com/mfm — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com  • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC • I run all my newsletters on Beehiiv and you should too + we're giving away $10k to our favorite newsletter, check it out: beehiiv.com/mfm-challenge My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano /

In 2000, contaminated drinking water in the small Canadian town of Walkerton triggered one of the country's worst public health disasters.Heavy rainfall washed E. coli bacteria into the town's water supply, but failures in testing and reporting meant residents continued to drink the water. Seven people died and thousands fell ill.Megan Lawton speaks to resident Bruce Davidson who experienced the crisis firsthand.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: A sign stating the water is find, on Knights of Colombus hall just outside of Walkerton, 2000. Credit: Peter Power/via Getty)

Montenegro achieving independence from Serbia in 2006 was the final part of the break-up of the former Socialist Federal Republic of Yugoslavia. Montenegro and Serbia had been joined since the end of the First World War, but after other Yugoslav countries broke away in the 1990s, an independence movement began to grow. In 2006, the people of the small European nation went to the polls and narrowly voted to become an independent country. Ivan Vujovic campaigned for independence in Montenegro with the Social Democratic Party. He speaks to Tim O'Callaghan. Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Pro-independence supporters celebrate the result of the referendum in 2006. Credit: Reuters/ Stevo Vasiljevic)

In this episode of FP&A Unlocked, Paul Barnhurst chats with Derek Baker, the Head of Strategic Finance at Circle, a growth-stage SaaS company. Derek shares insights from his experience in building strategic finance functions, scaling finance teams, and using AI to optimize financial reporting.Derek Baker is the Head of Strategic Finance at Circle, a growth-stage SaaS company focused on building an all-in-one platform for online communities. He has built the Strategic Finance function from the ground up, covering areas like pricing, sales compensation, investor due diligence, and AI-powered financial reporting. Prior to Circle, Derek co-founded The FP&A Hub with Paul Barnhurst and Liran Edelist to support finance professionals. His career spans FP&A roles across SaaS, marketplace, and biotech startups. Expect to Learn:How AI is transforming financial reporting and analysis in FP&A.The role of business partnering in aligning FP&A with strategic decisions.Derek's transition from spreadsheets to AI-driven financial models.How FP&A evolves as companies scale.Here are a few relevant quotes from the episode:“Spreadsheets are great for MVP models, but AI and data warehouses are the future for repeatable, scalable analysis.” – Derek Baker“AI can manage context better than prompts, and this is what drives its power in finance.” – Derek BakerDerek shares that the future of FP&A is all about embracing technology and innovation. He emphasizes that it's no longer just about spreadsheets and traditional methods; it's about leveraging AI and data to drive smarter financial decisions. By focusing on both the strategic and technical sides of finance, professionals can better align with business goals and create more impactful outcomes. Follow Derek:LinkedIn: https://www.linkedin.com/in/derek-d-baker/Website: https://community.thefpahub.com/home Earn Your CPE Credit For CPE credit, please go to earmarkcpe.com, listen to the episode, download the app, answer a few questions, and earn your CPE certification. To earn education credits for the FPAC Certificate, take the quiz on earmark and contact Paul Barnhurst for further details.In Today's Episode[00:00] – Introduction & Derek's Background[06:00] – What Does Great FP&A Look Like?[12:00] – Scaling Finance Functions in Startups[17:00] – The Role of AI in FP&A[22:00] – Building an AI-Powered Financial Reporting System[28:00] – Why Data Architecture is Key to AI Success[33:00] – The Future of Financial Modeling with AI[40:00] – Automating Monthly Finance Reports Using AI[45:00] – Data Integration and Financial Modeling for Future Growth[50:00] – Insights on Scaling FP&A Teams in Tech Startups[53:00] – Final Thoughts & Key Takeaways

Introduction What if the biggest gap in personal lines insurance technology isn't the consumer experience—it's the broker experience? Every major insurtech wave of the past decade has tried to disintermediate the agent. Jon Kelly thinks that's the wrong bet. In his view, the broker is the product in personal lines, and the tools they work with are embarrassingly behind. Kelly has been building at the intersection of insurance and technology since 1998, when he co-founded eCoverage—the first venture-backed startup to underwrite car insurance online. After selling SureHits in 2008, he spent years watching high-net-worth clients get onboarded with hundreds of questions spread across weeks of back-and-forth, proposals built in Excel, and data managed across disconnected systems. He called it "the Columbo experience"—always just one more thing. That frustration led him to co-found Kelly Klee Private Insurance in 2016 and build Discover, the platform powering it, from the inside out. Kelly Klee was acquired by Foundation Risk Partners in 2022. Now, as CEO of Modern Metric, he's selling Discover to the largest national brokers in the country. In this conversation, Josh Hollander and Kelly dig into the technology gap in personal lines, why enterprise-first was the right strategic bet, what it takes to hire high-agency people, and why trust is the ultimate product in this business. Guest Bio Jon Kelly is the Founder and CEO of Modern Metric, makers of the Discover platform for personal lines insurance distribution. His career began in 1995 at Mercer Management Consulting, advising Prudential, CNA, and Fireman's Fund. In 1998 he co-founded eCoverage, the first venture-backed startup to underwrite car insurance online, followed by SureHits (acquired by QuinStreet, 2008) and Kelly Klee Private Insurance (acquired by Foundation Risk Partners, 2022). He chairs Hometown Quotes, sits on the board of Great Range Capital, and earned a BA in Economics and Political Science from Stanford University. Key Topics • The missing layer in the tech stack — Independent agents have AMS systems for back-office accounting, CRMs for lead tracking, and form builders as pipes to carriers. But there is no purpose-built system for the client-facing workflow: data discovery, market presentation, and proposal delivery. That gap is what Discover was built to fill. • Relationship business vs. transactional business — The real split in personal lines isn't private client vs. mass market—it's relationship (multi-line) vs. transactional (monoline). Form builders work fine for monoline. They fall apart the moment complexity enters the picture. • Enterprise-first as a strategic decision — The most consequential decision at Modern Metric was targeting the largest national brokers from day one. Building for complex, enterprise-scale accounts forces architectural decisions that cannot be retrofitted later. You can scale down from enterprise; you cannot scale up from a form builder. Their first anchor tenant is a top-20 national broker. • The Uber Black analogy — If you order an Uber X and the Uber Black shows up, you're thrilled. If you order the Uber Black and the old Honda arrives, you're not happy. A platform built for simple transactions will never feel right in a complex private client context, no matter how much you add to it. • Hiring for high agency — The through line across all of Kelly's businesses: he hires for high agency. He looks for people who have clear motivations for every role on their resume. His favorite interview story: asking a candidate about their favorite exhibit at the natural history museum where they worked. The answer was "that was okay." They didn't get the job. • Trust as the ultimate product — Kelly's answer to what he'd want co-founders, teammates, and customers to say: that he delivered on what he said he would, that they got good value, and above all, that they can trust him. Trust is number one. Notable Quotes "I called it the Columbo because it was always just one more thing. Oh, your house is in a trust? Just one more question. I couldn't help think that maybe there were some issues with technology and personal lines, especially at the high end." "The whole process of how do you get the data in, how do you take that to market, how do you do your proposal—that's all done in paper and pencil, Excel and Word and Outlook." "If you order an Uber X and the Uber Black comes, you're thrilled. If you order Uber Black and the old Honda comes, you're not happy. You can't go from one to the other." "What I'd want them to say is that I delivered-that whatever I said I was going to do, I did, and that they got value out of it. More than anything, that they feel like they can trust me. Trust is number one." Resources Guest: • Modern Metric: https://www.modernmetric.com • Jon Kelly on LinkedIn: https://www.linkedin.com/in/jonkelly/ Host & Organization: • Joshua R. Hollander on LinkedIn: https://www.linkedin.com/in/joshuarhollander/ • Horton International (USA): https://www.horton-usa.com/ • Insurtech Leadership Podcast (LinkedIn Showcase): https://www.linkedin.com/showcase/insurtech-leadership-show Subscribe & Review If you enjoyed this episode, subscribe on your favorite platform and leave a review. The Insurtech Leadership Podcast is available on YouTube, Apple Podcasts, and Spotify.

Change management in manufacturing breaks down at the people layer, not the technology layer. This episode explains how engineering leaders actually drive adoption.Ronald Sherrod is a Staff Automation Engineer at Regeneron deploying a global event based architecture and Unified Namespace rollout across pharmaceutical operations. Ron, Vlad Romanov, and Dave Griffith dig into the parts of change management that rarely make it onto vendor decks. Subscribe to Manufacturing Hub for weekly conversations with industrial automation practitioners.Want to go deeper? Vlad and the team at Joltek have covered related topics here:Digital Transformation in Manufacturing: https://www.joltek.com/blog/digital-transformation-in-manufacturingMastering the Unified Namespace for Manufacturing: https://www.joltek.com/blog/mastering-unified-namespace-uns-a-guide-to-data-driven-manufacturing-transformationRon makes a point that is rarely stated this directly. The organization implementing the change is the one responsible for it. OEMs and system integrators deliver the box. Consultants help interpret it. Auditors do not call the machine builder when something goes wrong on the floor of a regulated pharmaceutical plant. They walk into the manufacturer and ask whether the audit trails hold up, whether the predicate rule was met, and whether the product is safe for patients. That responsibility cannot be outsourced, even when the technical work is.That framing changes how engineering managers should think about RFP scope. If the scope is loose, the integrator absorbs the risk and prices accordingly. If the scope is rigorous, bids come back tight and comparable. Negotiating power changes with the size of the buyer. A large pharmaceutical company can dictate hypercare windows, on site commissioning support, and structured training. A small to mid sized manufacturer often cannot, and the result is the metaphorical Ferrari on the plant floor that only ever gets used for grocery runs. Capital was deployed. The technology works. The operation never adopted it.The episode also goes deep on tribal knowledge and the industrial elder, the technical anchor who carries the institutional history of a unit or process and is often more valuable than the Excel file on a network drive. Senior operators know why a pipe was rerouted fifteen years ago and why a procedure looks irrational on paper but works perfectly in practice. With 59 percent of frontline skilled workers over 55 planning to retire within five years per the Schneider Electric 2024 workforce survey, capturing that knowledge is now a leadership priority, not an engineering task.On planning, Ron walks through how he runs user story workshops with operators, manufacturing leaders, engineers, and developers in the same room, producing a shared data contract that defines what information moves where, who needs it, and why. He cites a successful SCADA deployment that worked because the organization had inertia, operators had asked for the problem to be solved, and the team was closing a real gap rather than chasing a trend.Ronald Sherrod is a Staff Automation Engineer at Regeneron, a chemical engineer by training who moved from oil and gas into pharma and now works on event driven architecture, UNS, and robotics initiatives. Ron: https://www.linkedin.com/in/rdsherrod/Timestamps0:00 Welcome and Episode Intro1:50 Ron's Career: Oil and Gas to Pharma at Regeneron4:30 Defining Change Management and Its KPIs8:30 Change Management vs Operational Excellence11:50 Who Owns Change Management on Industrial Projects17:00 Negotiating Power: Large vs Small Manufacturers20:30 Why Capital Projects End Up Mothballed22:10 Tribal Knowledge and Learning From Operators26:00 Why Industrial Projects Fail29:00 The Industrial Elder and Passing Knowledge Through People31:30 AI Generated Documentation in Manufacturing35:50 Project Planning and the RFP Process47:50 A Successful SCADA Deployment and User Story Workshops54:30 Predictions, Career Advice, and Smart GlassesAbout Your HostsVladimir Romanov is a cohost of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Dave Griffith is a cohost of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub

In this episode, Swati Trehan, co-founder of Ema, breaks down what AI agents actually are, how “AI employees” work inside Fortune 500 companies, and why the future of enterprise software may look nothing like today's SaaS tools. Swati explains how Ema's platform orchestrates teams of AI agents that can autonomously handle HR, IT, finance, onboarding, payroll, employee support, and customer service workflows across massive organizations. She also reveals how companies like Hitachi are already deploying AI employees at scale, why traditional automation failed, and how enterprise AI is evolving beyond simple copilots into fully agentic systems. The conversation dives deep into the technical infrastructure behind agents, including memory, orchestration layers, knowledge graphs, model routing, and why Ema uses multiple LLMs simultaneously to optimize for cost, latency, and accuracy. Swati also shares why Excel remains one of AI's hardest unsolved problems, why video is the next frontier for agents, and how the “SaaS apocalypse” is reshaping software businesses. If you've been hearing terms like agents, autonomous workflows, AI employees, copilots, or agentic AI, this is one of the clearest explanations of where the technology is heading and what it means for the future of work. Key Topics Covered: What AI agents actually are (explained simply) The difference between copilots, agents, and AI employees Why traditional automation and RPA failed How Fortune 500 companies are deploying AI employees today Why HR is becoming the entry point for enterprise AI adoption How Ema orchestrates teams of agents across workflows The technical stack behind enterprise AI agents Why memory, context, and permissions are critical for agents The “mixture of experts” approach using multiple LLMs at once Why Excel remains surprisingly difficult for AI systems The next frontier: AI-generated video workflows The rise of the “SaaS apocalypse” Why solving business problems matters more than building features How AI is changing the way founders and engineers think Episode Timestamps: 00:00 - Intro 00:34 - What AI agents actually are 03:01 - The difference between agents and AI employees 03:25 - Liam's “light bulb” moment using agents 04:06 - Swati's realization that HR work could be automated 05:57 - The founding story behind Ema 08:20 - Why AI unlocks human creativity 09:20 - The technical infrastructure behind AI agents 12:12 - How Ema routes tasks across multiple LLMs 13:49 - Memory, context, and knowledge graphs for agents 16:35 - The biggest unsolved problems in AI agents 18:32 - Why video is the next frontier for AI 20:05 - Why Excel is still difficult for AI systems 21:00 - Who Ema's ideal customers are 23:27 - Why HR teams are leading enterprise AI adoption 24:25 - How enterprise AI implementation actually works 26:13 - Why modular agents matter 28:35 - What the employee experience looks like with AI agents 30:24 - Live demo of Ema's AI employee system 36:58 - How companies roll out AI agents internally 39:31 - Building AI employees in real time 44:01 - Ema's competitive moat in the AI race 47:46 - The “SaaS apocalypse” and future-proofing AI businesses 49:16 - Why Ema focused on product over hype 52:12 - How AI changed the way Swati thinks 55:07 - Why rapid problem-solving matters more than ever 57:27 - Living in London while building a global AI company 59:16 - Why Swati does what she does Swati Trehan's Socials: LinkedIn: https://www.linkedin.com/in/swati-trehan/ Ema: https://www.ema.co Partner Links Upgrade your AI toolkit: https://www.theaireport.ai/ai-executive-pass Subscribe to our free newsletter: https://newsletter.theaireport.ai/subscribe Join the community: https://www.theaireport.ai/leaders-launch-guide Learn more about your ad choices. Visit megaphone.fm/adchoices

In 1953, an Indian diplomat nicknamed the 'sombre porcupine' was given a rare opportunity when he was invited to the Kremlin to meet Joseph Stalin, one of the most controversial figures of the 20th century. Krishna Menon was a key figure in India's fight for independence from British rule, and was close to Jawaharlal Nehru, who'd become independent India's first Prime Minister. Reena Stanton-Sharma listens to archive recordings of Menon recalling his impressions of the Soviet Union's leader in a 1967 BBC interview. Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Krishna Menon. Credit: M Stroud/Daily Express/Hulton Archive/Getty Images)

Ag View Solutions: https://www.agviewsolutions.com/Farm Profit Manager: https://www.farmprofitmanager.com/Today's guest is Shay Foulk of Ag View Solutions and the Farm Profit Manager app. I've known of Shay for years as a podcaster and farm management consultant, and his presence on social media. Shay and I both have been a part of webinars for Fractal Ag in the past, and shout out to Ben at Fractal for helping to make today's episode happen. Some background on Shay: Shay Foulk is a farm business consultant with Ag View Solutions who works with operations to improve profitability and efficiency, manage risk, and grow. They offer this to farmers in the form of consulting, coaching, Peer Group facilitation and the Profit Manager app that we'll talk a lot about today. He grew up in NE Iowa working on a row crop and livestock operation with his father, uncles, and grandfathers. He attended Iowa State University where he majored in Agronomy. After graduating, Shay enlisted in the United States Army, and served 5 years with the 75th Ranger Regiment. He continues to serve with the Illinois National Guard out of Peoria. He also farms and runs Monier Seed with his father-in-law and wife, Hannah, near Sparland, IL.Shay's step dad, Chris Barron, started Ag View Solutions clear back in the mid 90s. He developed the foundation of what became what they called Profit Manager. He noticed that he knew his numbers a lot better on the hog production side of his farm, and wanted to apply the same business analysis to the crops side. So with his college roommate he developed the first version of Profit Manager on DOS. After years of consulting with farmers he turned it into an Excel-based tool. For years they have sold the tool and offered consulting services. Shay joined the business in 2019, and just this year they converted the Excel-based Profit Manager into this new app called Farm Profit Manager, and offered it for free.

Government contract bid opportunities on SAM.gov refresh every single week with 500 or more new sources sought notices spanning every industry imaginable, and most small businesses never see them. In this live session, Eric Coffie logs directly into SAM.gov, downloads the latest opportunities into Excel, and walks through dozens of real contracts available right now in fields from locksmith services and paper shredding to nursing staffing, call center support, cloud infrastructure, and demolition. If you have been waiting for the right time to get into federal contracting, this session shows you exactly where to look and why the timing has never been more urgent. What you will learn in this episode: How to pull Sources Sought notices from SAM.gov, filter by update date, and download them into Excel for fast, organized review across all industries Why the barriers you think exist in federal contracting, including licenses, certifications, and security clearances, are almost never listed as actual requirements on the solicitation How small businesses have a structural pricing advantage over large companies, and why large firms frequently skip contracts under $100K even when fully capable Why companies with the relevant skills (locksmiths, shredders, towing companies, nursing staffers) are not on SAM.gov, and how that gap is your direct entry point What the government actually evaluates when judging your readiness: your SAM.gov SBA profile completeness, your capability statement quality, and the recency and relevance of your past performance EPISODE CHAPTERS: 0:00 - Encore Funding sponsor intro and welcome 1:00 - Government contracting as an inflation hedge right now 4:35 - Why now is the time to enter federal procurement 7:30 - SAM.gov homepage walkthrough and search setup 8:45 - Why students are winning contracts directly from SAM 11:00 - Small business pricing advantage over large companies 17:00 - Why licenses and certifications are not required to bid 28:15 - How to filter Sources Sought and export to Excel 30:30 - Live review of real open opportunities across industries 36:15 - Locksmith services opportunity at Dept. of Homeland Security 40:20 - Towing and shredding contracts no one else is bidding on 54:25 - Why large competitors avoid SAM registration entirely 59:00 - Submitting a capability statement is all that is required 1:03:25 - Construction, call center, VA, and translation contract deep dives 1:20:30 - SBA profile comparison and what contracting officers actually check 1:23:50 - Closing message on capability statements and SBA profile readiness   Market Intelligence gives you the federal opportunities, agency signals, recompete intel, and pursuit briefs that tell you not just what contracts exist, but which ones to chase and how to win them. Sign up for free Daily Alerts and get opportunities delivered to your inbox before the day starts.

Adriel Hsu went from BRRRR investing to building $2M luxury homes in Texas with 230 transactions under his belt. Here's how he evolved his strategy.In this episode of RealDealChat, Jack Hoss sits down with Adriel Hsu, an engineer turned real estate investor and developer out of Houston, Texas, who has completed over 230 transactions across flipping, wholesaling, novations, multifamily, self-storage, and now luxury new construction.Adriel breaks down exactly how he adapted to every market shift since 2016 and why he is now focused on building $2 million custom homes.Topics covered:Why he started with BRRRR, pivoted to flipping, and why tenants were never the moveHow he sourced off-market multifamily deals (14, 21, and 32 units) while syndicators were getting burned in TexasWhy he exited the $300-400K starter home market and moved up to luxury buildsHis economies of scale approach to new construction (building 3-5 homes on one job site)How thinking outside the box on a problem lot turned into $112K profitSelling shovel-ready, permitted lots as a low-effort exit strategyThe difference between finish quality at the $300K and $2M price pointHow he structures private lender deals: first position liens for short-term investors, equity splits for longer-term capitalHow he hired his first VA to handle cold calling and what that did for lead flowHis custom deal analyzer built in Excel that lets him make offers in minutesThis episode is built for investors who want to understand how to evolve their buy box as markets shift and how to move up the value chain without overexposing yourself to risk.

The Great Talent Redistribution: Where is Talent Actually Going in 2026 and beyond?  Is the start-up compensation model broken? How about big Big Tech? How about non-tech small & medium businesses? What is happening to talent, going forward? This and many other topics in this episode of Tech Deciphered. Navigation: Intro The Broken Contract? The Great Unbundling The Three (?) Destinations Alternative Cap Tables, Alternative Compensation Models Investor Landscape Fragmentation Operator Playbook and Predictions 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 Goncalves Pedro Introduction Welcome to episode 77 of Tech Deciphered. This episode will focus on the great talent redistribution. Where’s talent actually going in 2026 and beyond? The Silicon Valley deal of the last 30 years, very low salary, stock options, you will either sell for a ton of money or IPO, and everyone gets rich, is seemingly broken. Or is it really? The dominant narrative says the tech middle class is dying. We disagree. There is obviously a lot of stuff going on whereby big tech is partially barbelling. There’s a superstar concentration on the top. There’s a bit of a seemingly allowing of the belly. We’ll come back to that. We don’t quite believe that is totally true. There’s a collapse at entry level. The belly is migrating into three, potentially even more, very different destinations: AI native startups, human-verified premium businesses, and the read the industrialized middle of the S&P 500 and SMB world. Each has its own cap table, each will have its own compensation model, and each will have its own investor profile. In some ways, this is the third episode in our Reset trilogy. We started with episode 75 on the SaaS-apocalypse. We talked about the great private capital reset in episode 76, and now we talk about talent redistributions. Bertrand, exciting times, not always positive times.   Bertrand Schmitt Yeah, it’s exciting times because it’s a time of change. Of course, we have the doomsayers. If you listen to Dario Amodei of Anthropic, every white-collar job on Earth is going to disappear. I think I strongly disagree, and I suppose you too as well, we strongly disagree. It’s going to be more of a redistribution. If you look at the history of technology, this is what always happened. We forget how many jobs have disappeared over the past 150 years. We move from a time of 150 years ago. People were mostly in agriculture. Then you had a lot of weird jobs that disappeared from people transporting water to people bringing ice from the pools to people doing the job of computers. People forget that computer was a title given to human beings. We’re doing calculations. Then, of course, secretory jobs in the ’80s, ’90s, where suddenly anyone can type using a word processor, the rise of Excel, that sort of stuff. Many things have changed. Some jobs have indeed disappeared. Some jobs have totally transformed. Where you do these jobs have changed. I think we are at a similar stage where, thanks to AI, and I would say for now, or at least the rise of AI coding, there is a dramatic change happening. I don’t think it means that people will be without a job. It just means, from my perspective, that jobs are changing. You are not just doing a lowly coding level task that actually indeed could be replaced, but you are going to have more of builder type of mindset, a product manager type of mindset going forward. We also expect that the distribution of jobs, depending on the type of business, will be quite different.   Nuno Goncalves Pedro The Broken Contract? Maybe let’s reset a little bit to the broken contract, or if it’s really a broken contract. There’s been this image in technology and tech that basically you get paid very little to work in tech. You get a bunch of stock options. The earlier you are in the company, the higher the level of stock option grants you get. Then you make a ton of money at some point because the company will either sell or IPO, and that’s heard of it. Obviously, there’s a lot of movements happening right now that are changing how these dynamics work. The first part is obviously AI, and in some ways, AI is shrinking companies. It’s not unheard of that companies with as little as four or five people reach 50 million in ARR. There’s companies with one person that have gotten bought for hundreds of millions of dollars or billion of dollars. Obviously, things are moving very, very fast, and therefore, there isn’t a large employee cap table. How would you share the upside? Would you actually give a couple of percentage points to an early employee rather than your 0.2-0.5% kind of thing for early employees? The second part is a little bit the other side of the table, which is the IPO market is seemingly in a drought. There’s not much happening in IPOs. Maybe 2026, at some point, there will be an unlock, but right now, it’s seemingly difficult to get your upside. Even if you’re an employee, you have to wait a long time. The median time of IPO has climbed over 10, 11 years, the longest in over a decade. Basically, not only you have to wait a long time as if there is an IPO drought, like we might be going through right now, when do I actually get my cash back? Unless the company gets bought, maybe there are secondary transactions along the way, maybe there’s something else. But obviously there’s a little bit of a reduction and lowering of the upside seemingly for this contract and for this place. The easy conclusion that I think many are taking is, because of all of this and all the layoffs that are happening, even in big tech, that serve the tech middle class is dying, that basically AI screwing the workers, et cetera, there’s also a lot of discussion that even it might be affecting the entry-level jobs as well. Everyone coming out of undergrad right now can’t get a job, et cetera. There’s this doomsday scenario that you’re alluding to that everything is changing. We have a slightly different perspective. We think there’s a realignment of market. In layoffs, there was a lot of layoffs that were warranted. Big tech, in particular, had actually hoarded a lot of engineering capacity over the last decade or so. There’s a little bit of a realignment that needed to happen in any case. When everyone’s saying, “Well, AI is compressing everything,” well, it’s compressing right now, but we don’t think actually it’s going to compress over time. You’ll still need engineering and science talent to come on board for you to be able to scale up. It’s not like AI is going to take care of everything and teams are going to be five people for companies that are worth a trillion dollars. That’s not happening. Today’s thesis, I think a little bit of this doomsday scenario needs to be seen with a more nuanced lens. I think that’s how we’re framing today’s episode, that there’s a bit of a nuance, there are some extremes happening. We’re going to talk about those extremes, but ultimately, it’s not quite as simple as saying that the tech middle class is disappearing in early jobs are going to be a thing of the past.   Bertrand Schmitt At the same time, what you started with is true. I mean, that 50 million ARR company, just five people. At a bigger scale, that’s exactly the matrix for Anthropic. They have reached a stage where they are at a range of 12 million ARR per staff per employee. It’s metrics that are definitely never seen before. I don’t think any company raised to this level. Best in class, best run companies, one, two million per employees. I mean, that was your target if you can make it. We are definitely in a different game. But I think what matters at the end of the day, and that’s what we’re arguing, is that you have to see the big pictures. Yes, some positions might disappear inside some companies, but some other positions will be created in other companies. Usually, what people do is keep talking about the jobs who disappear and not looking at the bigger picture of jobs that are being created as well. What is true, and I think you alluded to that, is that the big tech the past 10, 15 years had some strategy of hoarding talent in a war where having the best talented people will make the difference in numbers, will make the difference between winning or losing. The Google of the world, the Microsoft of the world, the Amazon of the world, they were hoarding talent. They would try to make sure that they might not have such needs in talented number of people. But if they have the talent, it means their competitors didn’t have the talent. It means that the startup trying to reach scale couldn’t pay the giant salaries that the Google of the world were paying. There was definitely some hoarding. But it went so far in the 2020, 2021, that I think since then there has been a coming back to normal. There is also now in 2026, the recognition that it’s not true anymore. Yes, talent can be very valuable, but there is now a bigger and bigger gap between the extremely talented versus the rest that are merely talented because of AI. AI is able to replace at scale your software engineers, your software managers. I would say it’s quite new. I don’t think it was true a year ago. We’re really talking about a recent dramatic change in what can be achieved thanks to AI. We can see most of the big AI companies are moving to coding. It was started by Anthropic as a trend, OpenAI has followed through. Obviously, the Cursor of the world existed before, but they were not as successful. All the Chinese open-source models are moving very fast to coding optimization the past few weeks. It’s quite an incredible change. I think there is that dramatic change, recognition that coding can be done differently. As a result, we are going to see change in the distribution of jobs. I think it will start from the top because we see the news of the big Google, Microsoft, Amazon, and others who used to hold talented software developers to a change in realization that no, we actually need to invest in AI. We need to invest in compute because compute is going to do the job of most of these people. Therefore, we can’t pay for both at the same time, even us with all our money, we cannot. Wall Street is not going to let us do that. They start by removing a lot of position. I think we see that accelerating, quite frankly. We have only seen the beginning, but in the next 2 years, we see a dramatic shift. But I think my position, I guess yours, and you know as well, is that there will be a lot more opportunities created as well, probably by also entities.   Nuno Goncalves Pedro The Great Unbundling Yeah, there will be more opportunities created. The hoarding is just taken also a little bit of a different view. To your point, there’s hoarding of resources, compute, et cetera. But there’s also hoarding of top talent. We are seeing people getting paid, packages all in that could run up to 100 million, in some cases even over 100 million over several years. This is unheard of. I mean, an officer of Meta would make, I don’t know, maybe 20, 25 million a year. It’s like now there are people that are on the top end of AI researchers that are getting paid around that amount just to join some of these companies. There’s a little bit of a different hoarding. It’s very selective hoarding of certain talent. We’ve seen some acqui-hires. We’ve talked about it in previous episodes that are just literally about getting one or two people specifically to come on board. Alexander Wang, again, going to Meta to lead their intelligence labs there. I feel, I don’t know what you feel, but I feel this is a transition moment where there is overpaying for certain talent on the top of the market. At some point, this will stabilize. You can’t keep paying people 100 million over 4 years or something like that across the board. To your point, a lot of this is actually going to scale up quickly also on the AI side. There’s a little bit of a different hoarding happening on the top end, not just the resources, but also of people, which seems to give further this notion of barbell, that there’s two extremes, the haves and have-nots, the super-duper talented people that get paid a ton of money, tens of millions of dollars a year at the very least. Then the emptying of the middle where there’s a ton of tech layoffs going on in some ways, the belly, as they would call it, is being expelled. The middle market, the managers are being fired because there’s nothing to manage. There’s a lot of positions going away. In some cases, you might keep some of the more junior talent, but with a little bit of experience. But even the talent coming out of colleges is not getting hired either. It’s a little bit of a weird thing where there’s hoarding at the top, there’s an emptying of the belly, the middle, and then the early, early, early is also not getting recruited. It’s like what gives? How is this going to look in the future? I agree fully with you, Bertrand, that there’s a migration of this talent, not only to other companies, but also to other jobs. There will be new jobs that will emerge out of this. The DevOps, dev tools market didn’t exist until maybe 20 years ago at scale, and it got created. In some ways, we’re seeing there will be new markets, there will be new roles and new jobs that will be created around engineering teams going forward. We can’t anticipate all of them. But basically, the emptying of the belly is true as it’s happening right now. The low hiring on the early and the top end, getting tons of money. We think this is a transition to something else. There’s the hoarding of engineering in general is coming to an end at momentum. Now it’s time to rightsize teams, to get the right at the table, et cetera, and start figuring out what works and what doesn’t work. We’ve already had some horror stories coming out even from Amazon where they were breaking systems with their use of AI tools, and I’m sure it’s happening across the board. I’m on a board of a company and been tremendously affected by Meta and its algorithms, where basically because of advertising, there have been people served with ads for this specific company where the ad doesn’t match the company, so basic stuff like that. It’s been actually very, very difficult because in some ways, the company goes back to Meta. It’s like, “Hey, dudes, you guys are serving ads that are not even our ads with our copyright and stuff. How does this work?” They’re like, “Oh, it’s AI.” It’s like, “Well, it’s AI but can you give me my money back?” They’re like, “No, we won’t give you money back.” This creates huge issues for companies, for example, that are very dependent on advertising, which obviously there’s a lot of industries that are. They’re actually in production systems at scale. Meta is, I think now, the largest digital advertising in the world. I think they outgrew Google in one of the last quarters. Basically, this has a tremendous effect that systems that are in production at scale are getting inputs and changes driven by AI tooling, and somehow nobody can say what the hell is happening. Again, there will be a reckoning, there will be a redistribution, there will be a rightsizing of teams and an adequacy of teams going forward. I personally think this is a transition period.   Bertrand Schmitt I think we are moving from hoarding or software engineering to hoarding the top of the top scientists in AI and hoarding of GPUs, GPUs/data center. For me, it was quite interesting to see the deal of Cursor with xAI, where basically they couldn’t get access to computing resources to run their model. But xAI had, I forgot the exact numbers, but close to half a million GPUs that no one, I mean, “no one was using” because their services are not so successful yet in terms of AI chatbot and the like. Basically, suddenly they are like, “You know what? We control access to resource.” But the new resource is, again, a mix of extremely talented AI engineering or AI scientists versus GPUs/data center. There is this race of controlling boss and everything else is going to be collateral damage. Some examples, I think, are quite interesting. You talk about some example of Amazon, even some production issues. I remember reading a quick post-mortem of one of the issues, and the conclusion was it was AI, definitely part of the issue. But the other part of the issue was AI used by junior engineers. For me, it’s interesting. It shows that actually junior plus AI is actually a danger zone. That’s why many companies are going to be way more careful. “Why do we need the junior people if they are just playing with fire?” I think we go back to that situation of barbell, as you call it. The top talents are extremely valuable because they know how a production system works. They are here to develop better AI systems. But the junior guys playing with fires, yeah, maybe it’s cute in startups, but in a big time production environment, a different story.   Nuno Goncalves Pedro There will be a barbell with top-end talent super-mega paid and then mid-level talent that is individual contributors still doing a lot of great work, et cetera. Along the way, a lot of emptying of entry, a lot of emptying of the middle. Where does the talent go? The Three (?) Destinations I think we could say there’s three destinations for this talent. Maybe there’s four, maybe there’s more. Three that we can immediately identify. One is the AI native startup piece, where we have smaller teams that potentially get to a lot of revenue or top line over time, and where the Series Seed is the primary round, where we’re seeing Series Seed being raised of tens of millions of dollars, actually even hundreds of millions of dollars in Series Seed. In some ways, the stars there can get incredible compensations in terms of stock. They will stay for private and selling in secondaries later down the road because there’s so much capital at the table. Actually, in some ways, salaries are very high as well in some of these companies. It’s not like you’re trading off anything. You can get paid a lot of money. If your company at Series Seed for 10 or 15 employees has raised 50-$100 million, you can pay great salaries. In some ways, this is the extreme destination. The AI native startups that can make it is the extreme destination. Now, there aren’t a ton of AI native startups that can raise 50-100 million to 400 million in Series Seed, just to be clear. There’s a handful of hot deals in that space, but that’s one clear destination for top-end talent going through that. In that market, I think that’s one of the destinations. The second one is more what we would call the human-verified premium. It’s more of a play of companies that has still the need of human in the loop, either in terms of development, also in terms of activity, either because go-to markets are very intensive, and so therefore you need to have sales forces, partnership teams, et cetera. Or on the engineering side, it needs to have a lot of customization, integration. Companies are not just going to the, “Oh, you can come in and just apply your AI tooling and somehow magically the systems all work.” there needs to be quite a lot of and work and high touch work in getting stuff done. A significant part of that market, I’m not sure, is super VC investible. Maybe it’s a hybrid of private equity in VC, more PE style in many cases. It’s a PE-hold, sell to someone else market. As we’ve discussed in a previous episode on the SaaS-apocalypse, that hasn’t quite worked out for PEs. Question marks on how that human-verified premium market is going to evolve. But obviously, there’s a lot of work still to be done there, even on the engineering and science side. That’s the second potential destination. Then the third more aggressive destination is the reindustrialized middle companies that have a lot of specificity in going after small and medium businesses, local or regional affectations like ERPs or CRMs for specific markets, et cetera. Those are the three natural destinations. I would add the fourth, which is big tech. I mean, big tech doesn’t magically disappear, and I don’t think it fits neatly into any of these three markets. In some ways, big tech is now looking at the extreme for top talent a little bit like the AI native startup because they can pay. They can pay the 100 million every four years, et cetera. I do think it will typify taxonomically into a fourth type emerging, where, as we discussed, you’ll have top-end individual contributor talent. You’ll have the absolute top-end of the market because they can get paid. Then you’ll start having the emergence of earlier talent that is highly capable, et cetera. That will go back to a bit of a normal distribution in terms of talent on big tech. For me, those are the four destinations that I would put at the table.   Bertrand Schmitt For me, big tech moving to big tech, I’m not sure if it’s really a destination. I mean, yes, in some ways it’s a reshuffle between the big tech companies. They are definitely all fighting in some ways for some of the same people. I can see that dramatic shift where big tech has to remove a lot of positions in order to replace by AI. Again, I think at this stage, it’s mostly driven by AI coding. We are still at the beginning because this is brand-new phenomenon that AI coding is so successful at its task. I don’t think it was true even 6 months ago. Some companies, take Anthropic, take OpenAI, are definitely there or close to be there in terms of no more writing of a single line of code by a human, zero. This is, again, 6, 12 months ago. Not true. But now it’s true in a few top companies. Take OpenClaw as well, most successful GitHub project of all time, not a single line written by its author. It would have been impossible. We’re talking about hundreds of thousands of line of code in a few months. It’s impossible to achieve that manually. If you look at the other big tech companies, the Google of the world, the Meta of the world, the Microsoft of the world, they are absolutely not there yet. They are going to be there because they have no choice. It’s you either go fast there or you die. You are not going to be able to survive competitors that are shipping 10, 50, 100 times faster than you are shipping. It’s a life and death situation. All the big tech companies are going to move, and mark my word, in the next 2 years from 10, 20% of AI-written code to 100%. During that transition, the next 2 years max, if you don’t do it in 2 years, you are going to die. Your stock price is going to crash. Then, of course, you will have to make changes. You will have to invest more in GPUs. You will have to invest less in your standard typical software engineer employees. Like you, I’m very optimistic that there are new buckets. AI-native startups definitely will be there. It will be transformational. Human-verified premium, very interesting category. In a way, it will be businesses that are inevitably less scalable through AI, and there is definitely a spot from there. I think the biggest would be the reindustrialized middle SMBs. Most of S&P 500 type of business are going to dramatically offer new software opportunities, new opportunity story to talented software employees because they will need to implement AI in everything they do. They will do it. They will need people who have software engineering knowledge in order to implement these systems. For them, what’s changing dramatically really is that thanks to much cheaper cost as thanks to AI coding, a lot of software projects that they couldn’t afford to do, that they couldn’t imagine doing by themselves, they are able to do it. They will invest in a lot more software capabilities than ever before. That will be a big game changer. And software, very tuned to their business model. There might be less buying of your traditional off-the-shelf SAF software and a lot more investment in a highly custom software by their own team, assisted with AI. I think that would be the part that is most transformed by all of this in a positive way.   Nuno Goncalves Pedro Alternative Cap Tables, Alternative Compensation Models This will lead to a very fundamental shift, right back to the broken contract. What does the new contract look like? It looks like alternative cap tables depending on which bucket are you transitioning into. If you’re going into your AI-native bucket, and you’re a top-end talent, you’re like, “Dude, I’m worth 100 million over 4 years, so just compensate me accordingly with a mix of options in the company plus my salary.” If you’re top 1%, you can probably get away with salaries that you’d get anyway at mid-level from 300K, 400K and above, and you can get actually a lot of options already in the company. A lot of this is happening right now. There’s a premium for AI, we know that. There’s a premium for AI at the top end of AI researching, in particular on companies that are doing hardcore research on staff AI engineers, so companies that require actual AI engineering. There is a premium that is significant. It could be as high as 18% over non-AI peers, and it widens actually with seniority, shockingly enough. This is more of an average than anything else. Now, for me, and it’s for debate, but the perspective is this extreme comp will need to compress at some point. There will still be the haves and have-nots paid much better than the have-nots, so to speak, but there will be a compression. The variance can’t be the variance we’re seeing today for absolute top-end talent. That said, there will be variants. We know that big tech for over a decade, decade and a half, for example, in the Bay Area, has been paying a lot of money for director and above levels that used to be the VPs, so a million, a million and a half a year, all in compensations. It’s not unheard of that this will actually increase after this stage. That said, I do think that the compensation extreme that we’re in will get diluted down the middle. It will actually come down at some point. It’s part of where we are today. As we know, it is still a bubble.   Bertrand Schmitt Yeah, it’s an interesting point. I think it’s possible. At the same time, that compression coming 2, 3, 5 years. At the same time, we have examples where there is no such compression. Take the top sports players in the world, golfing, basketball, NBA players. There has not really been any compression at all. For me, it’s interesting. If you look at the big tech companies, each being one of this top NBA team, why would such compression happen? As long as they are competing against each other and generating plenty of cash, I think there will be some fair question. We will see. I don’t have a strong opinion, but for me, it’s not a total given.   Nuno Goncalves Pedro For me, the shocking thing is the faster AI becomes better, the more that compression will happen, because at some point, it’s like, why do you need the top talent as well? I don’t know. It feels like you’re trying to evolve a system that’s there to replace you. It’s like, “Okay, I’m getting paid 100 million over the next 4 years”, and then you develop something that’s so good that replaces you. Thank you. That’s cool.   Bertrand Schmitt That’s a total possibility, yes, because we are in that very unusual market where the game is to only replace yourself and people like yourself. At some point, it is a possibility, I guess this one. Right now, we’re talking about replacing your “average software talent”. In 2 years, could we absolutely replace the absolute best top experts in the world? Probably. I think it’s just that at some point we’ll be reaching the stage where we strictly have no control anymore on our AI systems because no human is able to challenge and understand what’s produced. It’s not just a question of scale anymore. We’re talking about a gap in IQ, basically.   Nuno Goncalves Pedro Exactly. It will happen at some point in history. We don’t know exactly when. For the second bucket, the human-verified premium bucket, it’s difficult to see how an HVAC company or an HVAC roll-up of scale or a regional health care platform or high touch go-to-market, B2B, SaaS play, et cetera, for a vertical will compete. At the same end, they have to compete and they will compete. There will be more and more jobs, we believe, for engineering talent in these companies. They’ll have to be more and more AI-enabled themselves. The cash salaries will have to be competitive within the local markets, not necessarily with Silicon Valley. There will be potentially profit sharing and revenue sharing and actual dividends played at the table. The model there on the cap table needs to change a little bit, needs to be probably propped up more on salary and on some way of doing profit sharing or actually having dividends paid to employees and figuring out employee to equity in a more aggressive manner. This is the market that probably was already very attacked, so to speak, or let’s say, occupied by private equity firms. There are still obviously part of that model that would work well. There needs to be a fundamental shift, certainly on the quantum of salary compensation, dividend compensation, profit sharing, and all of that. Then last but not the least, obviously, we had the bucket around basically the reindustrialization of the middle, so everything else, which will take most of the belly that we were talking about. This is probably a poor analogy, the belly fat. It’s not belly fat, it’s people that were doing their jobs that now are getting disrupted. In some ways, that bucket will absorb a lot of that belly, will absorb a lot of talent. The small and medium businesses that Bertrand was saying will need to crucially become more AI, software-enabled by themselves, even with some core stuff and underpinnings that actually might not even require AI in terms of infrastructure platforms. There, you need to get properly paid. Again, how many people do you need in your engineering team if you’re a small business? Probably not a lot. It’s maybe you need one or two people and that’s it. They’ll need to be very nicely paid because they’re running the stuff in the rails. This is probably a market that over time, as AI gets more and more competent, will also be disrupted, but let’s not talk about the disruption to the disruption because otherwise, we’ll stay here the whole day, but certainly a market that has a lot of potential to shift and to absorb a lot of the moments that we’re seeing in terms of layoffs happening in the US in particular.   Bertrand Schmitt This category was a category that historically could not compete with Silicon Valley salaries, could not attract the most talented engineers. It’s not a category that didn’t want to bring these people on board. It’s a category that just couldn’t afford to bring this talent on board, typically. I think it would be a dramatic shift for them when suddenly there are opportunities to hire these people. There is an opportunity to hire them at maybe more reasonable prices from this company’s perspective. You talk about small companies, the great thing is that there are millions of small companies at some point. I think things could be truly transformational. Of course, some of these engineers, software engineers, might decide to become entrepreneurs on their own. Solo entrepreneurs, small businesses, build their own, easier to build their own product to market so to serve other companies. I think there will be quite dramatic changes because not all companies will be disrupted by AI as much, but not every company will benefit from improving processes, improving software through AI. At least early on, you will need this human touch to make it work inside a business. Interestingly enough, I was hearing that some companies like IBM were hiring more younger people to do the work of going to the client, understand their needs, propose implementation plans. That forward deployed engineer, those positions, I think there will be more and more available.   Nuno Goncalves Pedro Investor Landscape Fragmentation What happens to investor into the landscape? We already had an episode, the previous one, Episode 76, where we talked quite a lot about the big capital reset on the private equity and private reset, including venture capital. Just maybe to summarize, how does it align with the buckets that we’ve just been discussing? I think the AI-native bucket clearly is going to be the key bucket. There, we’re going to see two movements. One movement, which is the mega funds, as we discussed in the last episode, are no longer just VC funds. They’re really mostly multi-asset private equity funds, maybe even private equity hedge funds in some cases. Those funds will be all over the high-growth AI-native companies and will be pouring money into companies that are scaling really, really quickly. The early stage, so to speak, VCs, the actual VCs that will stay in the market will be the guys probably identifying the next big wave of AI-native companies. We’ve discussed that as well in the last episode, some research that we did at Chamaeleon that I shared in episode 76. We’ll see that as emerging. What happens to the second bucket, the bucket around human premium, human in the loop? Likely we’ll have more and more private equity capital going into it and the large-scale VC guys, the Thrives of the world, they’ve just announced Thrive Holdings, and others going after those markets as well. It’s trying to converge into the private equity market, which aligns with the point we made in the previous episode that the VC mega funds are no longer VC, that they are private equity, multi-asset class. They’re going after a bunch of things. There’s a conversion happening from VC into private equity. It was going to happen anyway because the private equity guys were coming into VC as well and the hedge funds were coming to VC as well. There’s a convergence in the middle of very, very large funds and large assets under management happening to go after some of these opportunities, certainly in Bucket B. Then this Bucket C, so to speak, the bucket of reindustrialization, as Bertrand was saying, very well, likely will be self-funded for a significant period of time. Will self-fund with their own cash flow. Doesn’t need to have a ton of capital intensity. Maybe you need one or two engineers to do stuff, but that’s it. You don’t need tons of capital. You didn’t need in the past, you won’t need it today. Not sure there’s going to be a fundamental shift to that market.   Bertrand Schmitt Yes, I certainly, overall, agree with you. That last pocket, probably little change to the capital and capital structure. Again, I see that as the biggest opportunity for a lot of people who might be less needed by big tech and also top tech companies. What is sure for the first category, the high native startups? I would say more overall in the VC ecosystem, there is no space left for SaaS anymore. I think SaaS, as we used to know it, is dead in some ways in the sense that new pure SaaS software startup are definitely out. Existing ones that are critical to run your infrastructure, the Salesforce of the world, I think they’re in a decent spot. Actually, interestingly, they changed their pricing model to now sell to AI agents, not just per seat. There is a change in pricing there. But this day and age of funding a pure SaaS software startup through VC money, no way. VC money going to AI-native startups, AI-focused startups, to biotech, to deep tech, to defense tech, yes. SaaS as a fundable category early on, I think it’s over.   Nuno Goncalves Pedro I’m a bit more nuanced as we shared in The SaaS Apocalypse episode. We can call it whatever we call. It’s applied AI is the new SaaS thing. Horizontal applied AI is the new horizontal SaaS or vertical applied AI is the new vertical SaaS. I agree in common with your point that very specific point solutions around SaaS will be disrupted by nature with all the easy stuff you can do today with AI. It will take a while. This is not something that’s going to happen this year. It’s going to happen over the next years. Maybe interesting to also talk about the exit markets. I think the IPO market, as we’ve also discussed in the past, there is, in my view, going to be a reopening of the IPO market, I think this year, probably later in the year, third or fourth quarter. The median time to IPO actually is going to be really weird because there’s going to be potentially some companies in the current landscape, bubble or no bubble, that are going to IPO, the OpenAIs of the world, Anthropics of the world, et cetera. There will be more and more aggression, I think, on M&A. Big tech has already shown it, that they want to buy into markets. Large non-tech companies have also started doing acquisitions in space. To prop up their IT teams, their engineering teams with this world that we’ve also discussed in previous episodes that I’m going to own my own engineering stack for now. As we see, that normally doesn’t withstand the test of time. At some point it will get unbundled and served by someone else. Then finally, the secondary market is very hot right now. Obviously, there’s heavy discounting on some areas, high premiums on others. The exit market, strangely enough, is going to be propped up, in my opinion, over the next year to 2 years, dramatically. Then we’ll see if there’s a big reckoning around the bubble that we are clearly in or not, if it’s a soft landing or hard landing. Definitely, there’s going to be a lot of exit paths over the next year to 2 years.   Bertrand Schmitt Concerning the “bubble”, I have two perspectives on this. One is it’s a bubble in the sense that money is going to a lot of players and some players are going to blow it up. There will be a concentration of players at the end, like it usually happens. If you look at, for instance, long time ago, the railway revolution, there was that intense influx of capital. At the end of the day, there was a dramatic change in transportation in the US and a complete railway system put in place. Yes, some investors lost money, some companies went bankrupt, but the transformation was fully real. There were a lot of top leaders at the end of this revolution. The change after that only happened, we guess, post-World War II, with the construction of the highway system and the rise of airlines and plane transportation overall. Here I feel it’s similar in the sense that, yes, there is a lot of money going in. Some players are going to blow it. They will misuse the money in different ways, but that’s part of dynamic allocation of capital. Of course, you make mistakes. That’s what happens. At the same time, I feel it’s a similar level in the sense of this is a dramatic change in the US infrastructure. This buildup of AI data centers filled with GPUs, integrated at scale with some of the best software in the world and running it, supported by a dramatic shift in energy infrastructure. This is for me similar to the Railroad Revolution. Some players might not own the data center they build because they didn’t manage well their debt, they didn’t manage to run proper software. You know what? They will get acquired by somebody else. I think we are at this level of fundamental transformation. The fact that in a matter of maybe 2 years, the move from 0% of code written by AI to 100 % written by AI is an insane dramatic shift. Just to be clear, when you move from manually coded to AI coded, we’re talking about a 100X difference in terms of speed at similar, if not better level of quality. The shift is dramatic, and on top of it, you don’t pay salaries anymore to achieve that. You pay CapEx, and with GPUs and OpEx with electricity. It’s a very big shift, positive shift in business model. New unions, no management over it, AI working 24/7. Personally, I think for me, bubble has a bad connotation in the sense of it was all for a waste. I don’t think it’s all for a waste. I think we are witnessing a dramatic revolution of our lifetimes, quite frankly, bigger than SaaS, bigger than mobile. From my perspective, it’s exciting times.   Nuno Goncalves Pedro Operator Playbook and Predictions Let’s move to if you are this person, what would you do in the future? Let’s start with two extremes and go from there. One is you’re non-tech, so you’re not an engineer, et cetera. You’re trying to figure out, how do I scale my activity? Maybe physical labor is where I want to go. It’s not, “Go west” anymore. Definitely not necessarily go west. You should go to, I guess, the states that have no sales tax with very cheap energy because that’s where the data centers are being built if you want to be in that market. Obviously, there’s a lot of stuff that needs to be done: HVAC, electricity work, et cetera. Don’t go west. Go low sales taxes, low cost of energy. That’s likely where the data centers are being built. You probably can just follow. There’s, I’m sure, some way for you to follow where the data centers are being built, but that’s next, I think on that extreme of the table. The other extreme of the table, let’s say you are super ambitious, maybe you’re no longer an engineer, but you’re a product manager in your prompt engineering. You could do prompt engineering all day long. You’re 28, 29-year-old superstar. What do you go and do? Likely either you start your own thing, start your own company because you’re so good at prompt engineering, you probably can do a lot of the code yourself, particularly if you have an engineering background, or you go and join very early an AI-native startup that you think has the chance of going through the roof, and you take a pretty good salary early on, a ton of upside on the company because guess what? Companies like that need product managers. They need people to figure out UX, UI. It’s not going to be, at least for now, yet AI figuring that out for you. Those are two extremes, just to give two of the extremes, like engineering, product management persona, and physical labor at the other extreme, non-tech, et cetera.   Bertrand Schmitt In some ways, every software engineering job is going to become the equivalent of a software engineering manager or a product manager, because suddenly you don’t have to do the coding anymore. You’re managing AI that is coding for you. Either you start to have some manager hat, but we saw the humans, so it’s a very different type of manager, obviously, or you are going to be really an empowered product manager. You’re skipping the middleman. You’re skipping the traditional engineering organization because your engineering organization is AI running and doing the work for you. I still believe that it requires some serious skills. I don’t believe in the vibe coder type of value proposition. I don’t believe in the prompt engineer becoming suddenly super incredible, able to manage that. I still think it requires some serious chops to do the best from all of this and to do it in a safe and sane way. It’s very easy to have poor taste, make mistakes. I don’t know you, but keep reading these stories on the heads of companies who lost everything because of the AI agents. That deleted stuff in production, and they had no backups or the backups weren’t deleted as well. Crazy situation. You cannot run companies like this if you let your agents running wild. You could argue it’s the early days. I would argue it that that issues would be there for a while. You need to have some engineering discipline at core in the company running the business to make sure things don’t go sideways because it would be easy for things to go sideways.   Nuno Goncalves Pedro I totally agree. If you’re thinking, Oh, should my kid go into science and engineering and computer science, et cetera? Absolutely, still, because of everything that Bertrand just said. You need to understand actually what code does and what technology does and what all of that does. That’s still a skill of the future. It’s not a skill of the past. In some ways, it’s still a skill of the future very much. Maybe let’s try two more extremes. Around the same level, the person that decided to do an AI native company bootstrapped initially, having difficulty raising a mega round, but could probably get away with raising a 2-3 million seed round, et cetera. Is that still viable? The answer is yes. There’s tremendous capital efficiency right now happening in the market still, 10 plus higher than if you were doing a SaaS company, and you were a founder in 2019 or something like that. That capital efficiency is going to reverberate. You can run a tighter team, smaller team. Actually, you don’t need that many salaries. If you’re a decent engineer as a founder or if you understand enough as a product manager to just generate that code, you can do a lot of stuff yourself, can bring in maybe one or two technical elements to the team early on as you would have done if you were bootstrapped anyway. There’s obviously a path for that. The other extreme is you’re in big tech, you’re level five, individual contributor, making a ton of money, or you were a manager, and you’re now out of a job, where do you go? You can go to a big company that is non-tech, S&P 500 company that’s non-tech, something like that. You join the company, you’ll probably get paid pretty well, maybe not as high as you were paid in big tech. There’s some stock at the table, but guess what? You’ll have probably more work-life balance than you ever did. That’s the trade-off. You’ll have a better job. On the upside, you can transform the company. You can help and be part of transforming a company from non-AI to AI-first or AI-enabled in the future, whatever BS that will look like in terms of the argumentation to the board. You can actually create tremendous productivity enhancements in a big non-tech company if you come with that background. Again, you’ll have certainly a better work-life balance, so not a bad deal, to be honest.   Bertrand Schmitt Also, to be clear, I talk a lot about AI coding because it’s truly transformational. You could argue that it’s going to be self-improving. We are in the situation of a self-improving AI that keeps improving itself thanks to automated coding. It’s a dramatic, virtuous loop. Obviously, AI is also going to improve everything else. It’s going to improve your marketing, it’s going to improve your search process, it’s going to improve your DNA. Improvements will be everywhere. It’s just that right now we are at a point in the quote-unquote revolution where there is one clear piece of the puzzle that is moving faster than the rest.   Nuno Goncalves Pedro Bertrand, the senior executives at non-tech don’t know anything about that. It could be just a great prompt engineer. That’s the only job you do. “I’m the chief marketing officer. I have someone below me that’s doing the whole work.” Nobody knows. Nobody’s the wiser, I guess. I’m being facetious, but not fully.   Bertrand Schmitt Yeah. There would be a transition period where what you described happen. I want to say, going back to AI coding, I think that the part of AI that as of today has reached a stage of limited AGI. We have reached, from my perspective, a limited type of AGI for coding. If you take coding as a discipline today, I think we reach AGI. If you go beyond coding, that’s true. If we are talking about coding, leveraging the latest LLMs: OPUS 4.7, ChatGPT 5.5, combined with Claude Code, Codex, and OpenCode for harness, I think we’ve reached AGI in the context of coding. I’m not sure everyone fully realize that and the consequence of that. I think the rest is going to come as well. We are going to see that category by category, usually categories that are more scientific in nature, where you can replicate, where you can test easily, where you can create clear success. Metrics will be the “easiest” to follow in that direction of self-improvement. I just want to highlight that this part is truly transformational, the root cause of everything we’re talking about today. At the same time, it’s coming beyond coding.   Nuno Goncalves Pedro I think it is true. There are a couple of markets where that might not hold true, which is maybe the final path. If you’re thinking of starting your own business in plumbing and in HVAC maintenance and installation, this is a pretty good time for the reasons we already said before. There’s a lot of buildup of data centers and all that stuff, but also for other reasons, because it’s an activity that won’t be disrupted by AI yet. You need them embodied AI. You need physicality to AI to do stuff like actually fixing pipes.   Bertrand Schmitt Until Optimus replace you.   Nuno Goncalves Pedro Yeah, but if we’re 3, 4 years out in terms of a lot of these optimizations that we’re talking about at the software layer, we’re 10 years plus out on embodied AI, right?   Bertrand Schmitt Oh, yeah, it’s 10 years.   Nuno Goncalves Pedro We’ll probably be optimistic as we speak. That’s a nice business. I’m thinking of starting to go into that market. If you guys are interested in listening to this, just reach out to me. What’s the angle? I think there’s a lot of stuff you can do in the buildup of some of these businesses, plumbing, HVAC, all sorts of maintenance. There are markets that are just totally messed up. Handyman market in the US is totally messed up. There’s a bunch of companies out there that try to go after it with marketplaces and stuff. I honestly just start something from scratch, a small business, and go from there.   Bertrand Schmitt Yes. They’re an interesting middle. Think about accounting firms, consulting firms. I think they are not as easy to replace, but at the same time, there is no way on what they do is not going to be dramatically changed with AI. I don’t know if it’s 50, 80, 90% of the job, but this is changing quite dramatically, would be my expectation in the coming few years. Conclusion Thanks for listening episode 77 of Tech Deciphered about that great talent redistribution. As you heard it from us, we believe there is a dramatic change in play, enabled by AI coding, and that ultimately a lot of the big tech companies are changing their employee distribution, way more focused on the top talents and bringing more GPUs. As a result, we will see a change in their staffing. Some of this change will benefit AI-focused startups, but probably more likely will benefit the bigger SMBs, the S&P 500 companies of the world that will finally be able to bring inside and afford some of the talent that were in some ways trapped by the top 5, 10, 20 software companies of the world. Thank you, Nuno.   Nuno Goncalves Pedro Thank you, Bertrand

Episodio 369.El único que compró un huevo grueso fue un tracalero que dijo que el mar está en el sur. Necesito que acepte que se equivocó y que lo admita como si fuera un AI. Espero que se quede haciendo el Excel el solito y que ninguno de sus vecinos decida dispararle. La ignorancia es suya.

In 1999, a teenager's debut book unintentionally caused a royal scandal in Belgium that wouldn't be resolved for more than 20 years.Each evening after he'd finished his homework, Mario Danneels dedicated his spare time writing a biography of Queen Paola. While researching her, he'd discovered that her husband, King Albert II, had fathered a child outside of his marriage.It was just one sentence in his book but once the revelation was published it caused headlines across Europe which, as Mario tells Daniel Rosney, would weigh heavily on him until 2020.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Mario Danneels, 1999. Credit: Renders/Isopress-Senepart via Shutterstock)

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I coach women from their very first digital product all the way up to founders doing over a million a year, and I can tell you the bottleneck is almost always the same thing: the founder is still doing work that has no business being on her plate.In this Fail to Win podcast episode, I walk you through 5 specific ways women I have coached scale their income without scaling their hours. I'm not giving you the generic 'just build a course' advice. I'll give you real examples, including how I went from manually making invoices in Excel to running an AI inbox system that replaced years of PA costs and how I turned my personal training conversations into my first 30-day evergreen course way before that sh*t was easy.Your hours are limited, but your rate absolutely is not so I want to share with you the 3-step path one of my clients took from employed and terrified to running her own business on her terms.If you want to figure out what a digital product could look like for your specific business, even if you have no clue right now, use my free IdeaGPT at fastforwardamy.com/ideagenerator. It takes what is already in your brain and turns it into real digital product ideas with easy-to-sell price points.Follow me on Instagram for more business and mindset tips: instagram.com/fastforwardamyDiscover my free trainings and ebooks: fastforwardamy.com/freeresources

In 1981, Poland's communist regime imposed martial law and the dissident Solidarity movement was suppressed. In response, Helena Luczywo helped set up an underground newspaper called Mazovia Weekly to communicate uncensored information to the population. Despite police raids and arrests, the newspaper played a significant role in the fall of communism in Poland. Helena tells Ben Henderson about the years she edited the newspaper while on the run.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Protest against martial law, 1982. Credit: Bettmann via Getty Images)

In this Retail Technology Spotlight episode, Judah Berger, AI Product Manager at Unframe.ai, joins Omni Talk to explore one of the biggest questions facing retail leaders today: how do you actually implement AI across an organization without creating operational chaos? Judah works directly with enterprises to turn AI from an exciting concept into scalable systems that solve real business problems, helping companies identify inefficiencies, design AI powered workflows, and deploy solutions employees can actually trust and use. As companies rush to adopt tools like ChatGPT and Claude, Judah explains why unrestricted experimentation can unintentionally create an “Excel on steroids” problem, where disconnected prompts and workflows multiply inconsistencies across the business. From AI governance and workflow orchestration to SKU intelligence, predictive inventory management, and a real world footwear retail case study that generated a reported 40x ROI, this episode offers a practical roadmap for retailers looking to operationalize AI responsibly while still encouraging innovation across their teams. Key Topics Covered: • 00:01:56 – The four major approaches retailers can take toward AI implementation • 00:05:21 – Balancing bottom up AI experimentation with enterprise wide governance • 00:17:40 – How organizations should identify, scope, and scale the right AI use cases • 00:21:26 – The technology, auditability, and infrastructure needed for scalable enterprise AI • 00:26:58 – Case study: How a footwear retailer used AI inventory intelligence to achieve a reported 40x ROI See our past 8 years of wonderful Spotlight Series podcast guests, featuring roughly 200 movers and shakers in retail, by clicking here: https://omnitalk.blog/category/spotlight-series-podcast/ #retailtech #AI #retailAI #inventorymanagement #retailoperations #SKUintelligence #supplychain #predictiveanalytics #enterpriseAI #generativeAI #retailinnovation #OmniTalk #retailpodcast #AIstrategy *Sponsored Content*

We catch up on a chaotic launch week, a new company announcement, and the growing noise around AI and tech culture before switching gears into what actually makes a presentation land. We share the practical public speaking and presentation skills we use to keep audiences engaged, stay calm under pressure, and communicate with clarity without sounding rehearsed. • a fast check-in on work chaos, health, and getting back on the mic • Michael's company launch and the promise of agentic AI for reclaiming time • Palantir's manifesto and why AI fear-mongering is spreading • why knowing your audience and goal beats memorizing a script • setting expectations up front so the room does not derail you • breathing, intentional movement, and using energy the right way • storytelling frameworks like the Amazon model, hero's journey, and what so what now what • simple slide design, why never to present from Excel, and how to end strong • Q&A tactics that lead to better questions and better answers If you're interested in supporting the show, you can do so by clicking on the link. It is a link tree now in every place. If you can't do any of those things, the least you can do is share this episode with your friends.Support the showClick/Tap HERE for everything Corporate StrategyElevator Music by Julian Avila Promoted by MrSnoozeDon't forget ⭐⭐⭐⭐⭐ it helps!      

From the archive: This episode was originally recorded and published in 2022. Our interviews on Entrepreneurs On Fire are meant to be evergreen, and we do our best to confirm that all offers and URL's in these archive episodes are still relevant. Brandon Zobel is CEO and Founder of ProsperSpark, using 20 plus years' experience to provide Excel consulting and process automation, serving 200 plus clients and simplifying their workflows. Top 3 Value Bombs 1. When automating, focus on small processes as well as large ones. 2. Automation often frees employees from repetitive tasks so they can focus on high-impact work. 3. Use technology for tasks that don't require a human touch. Get a 10 percent discount up to 1,000 dollars on a ProsperSpark project if you mention the code "FIRE." Book your free call today to get started - ProsperSpark for Fire Nation Sponsors HighLevel - The ultimate all-in-one platform for entrepreneurs, marketers, coaches, and agencies. Learn more at HighLevelFire.com. 50 - Join JLD on his free '50 days to something' video series on YouTube and create something special in 50 days.

In 1980, Norway's entry to the Eurovision Song Contest included a traditional Sami joik song from the country's indigenous community. It was the first time joiking was heard by an international audience. The song was originally created by Mattis Haetta as part of a protest against the building of a dam in Finnmark, in northern Norway – which would have flooded traditional Sami reindeer herding routes and villages. Surya Elango speaks to Inga Haetta, the sister of Mattis.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Mattis Hætta on Eurovision 1980. Credit: Stein Dag Jensen/National Library of Norway)

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Charles Cofield. Thanks! The transcript from this episode of Money Making Conversations Masterclass features an inspiring and high-energy interview with CPA and financial educator Carter Cofield, co-founder of Melanin Money. Here's a breakdown of the key highlights and takeaways:

In 1997, Sweden changed television history. That year saw the launch of Expedition Robinson, widely regarded as the world's first reality-based competitive television programme.The premise was strikingly simple. A group of ordinary people were stranded on a remote island, where they were required to build shelter, compete in challenges and vote one another out — until only one contestant remained.When the final votes were cast, it was Martin Melin who stood alone. In doing so, he became the world's first reality TV winner — years before the genre would grow into a global entertainment force.The programme's path to broadcast was far from smooth. It prompted fierce ethical debate in Sweden and came close to being pulled before transmission. Yet once it aired, it became one of the country's most talked-about and successful television shows.Its format would go on to inspire the international hit Survivor, which marks its 50th US season in 2026.Martin tells Madelaine Savage how it felt to be part of a new cultural phenomenon.A Podlit production.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Martin Melin. Credit: Aftonbladet via Alamy)

In 1996, the bricklayer renovating Merced dos Anjos' home in Rio de Janeiro told her something strange had happened. Bones appeared as he was breaking ground. As she inspected the site, she found they were human. But why so many bones? Was it the work of a serial killer?The answer was more macabre. They had unearthed an ancient cemetery. The discovery shed light on the brutal history of Brazil's slavery past – and Rio's role as the biggest slavery port in the Americas.The neighbouring Valongo Wharf, today a World Heritage Site, received roughly one million African captives by 1831. Many were too weak after the transatlantic crossing and died soon after arriving. They were buried in the so-called New Blacks Cemetery.Merced dos Anjos tells Julia Carneiro how the discovery upended her life and led her to create a research centre to shed light on Rio's painful past.An Overcoat Media production.Eye-witness accounts brought to life by archive. Witness History is for those fascinated by and curious about the past. We take you to the events that have shaped our world through the eyes of the people who were there. For nine minutes every day, we take you back in time and all over the world, to examine wars, coups, scientific discoveries, cultural moments and much more. Recent episodes explore everything from how the Excel spreadsheet was developed, the creation of cartoon rabbit Miffy and how the sound barrier was broken.We look at the lives of some of the most famous leaders, artists, scientists and personalities in history, including: the moment Reagan and Gorbachev met in Geneva, Haitian singer Emerante de Pradines' life and Omar Sharif's legendary movie entrance in Lawrence of Arabia.You can learn all about fascinating and surprising stories, like the invention of a stent which has saved lives around the world; the birth of the G7; and the meeting of Maldives' ministers underwater. We cover everything from World War Two and Cold War stories to Black History Month and our journeys into space.(Photo: Merced Guimarães dos Anjos. Credit: Julia Dias Carneiro)