Épisodes

  • Seagate's 2-Star General Turned CHRO: 7,000 Employees AI-Trained, No AI Agents on Org Charts

    Seagate's 2-Star General Turned CHRO: 7,000 Employees AI-Trained, No AI Agents on Org Charts
    Nov 9 2026
    I sit down with Patricia Frost, EVP and Chief People and Places Officer at Seagate Technology, a two star major general in the US Army with 32 years of service, and now leading people strategy at a 50 year old manufacturing company with 30,000 employees across the globe. I break down why Patricia refuses to call someone managing AI agents a manager because they don't deal with the complexities of leading frontline workers in a manufacturing environment, why Seagate democratized AI tools to every professional employee and focused on redefining roles from the ground up instead of cutting jobs, and why she partnered with a German company called CoBrainer that scrapes the internet to show how much of any job role posted on LinkedIn has already been automated. Finally, we look at why the cybersecurity threat landscape isn't about if but when every company will experience a cyber event, why Patricia believes companies need to decide what they insource versus outsource and work closely with public private partnerships especially if they're a national asset, and how Seagate uses an agent management system with owners and guardrails but will never put agents on the org chart because she won't demean engineers by showing an AI agent as equal importance to a human building hard disk drives. Chapters 00:00:00 From Two-Star General to Chief People Officer: Patricia Frost's Service Journey 00:06:19 The Five Cybersecurity Questions Every Board Should Be Asking 00:10:47 The Six Billion Dollar Binance Lesson: Why Employees Are Always the Weakest Link 00:14:34 Why HR Won't Go Away: The Messy Reality of Managing Humans 00:18:21 Employee Experience Equals Productivity: Why HR Must Lead AI Rollout 00:23:25 The Workflow Workshop: Automating Your Biggest Pain Point in Real Time 00:37:23 Job Architecture as AI Foundation: The Nine-Month Data Cleanup Project 00:43:01 Human Amplification Over AI Transformation: Migrating People, Not Eliminating Them
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    45 min
  • Wall Street Plunges 5.5%, Data Center Bans Risk 5.5M Jobs & Apple Slashes AI Budgets to $25/Day

    Wall Street Plunges 5.5%, Data Center Bans Risk 5.5M Jobs & Apple Slashes AI Budgets to $25/Day
    Nov 6 2026
    November 06, 2026: I unpack Wall Street's worst day since 2025 with the S&P down 4.4%, the NASDAQ crashing 5.5%, and NVIDIA falling 9% as Democratic leaders push for national data center moratoriums, why tech companies are losing the PR battle despite data centers supporting 5.5 million American jobs, and how banning this infrastructure could crater one third of US GDP growth while pushing innovation to Saudi Arabia and the UAE. Then I get into new Economist Enterprise research showing only 4% of midsize companies say AI and workforce transformation are moving forward as integrated efforts while 59% say AI is racing ahead of people and processes, why I think the ROI conversation around AI is flawed because we don't measure ROI on driver's licenses or high speed internet, and how AI is less like a factory machine and more like a capability that makes your world bigger. Finally, I look at Apple cutting employee AI budgets from $300 a day down to $200 and possibly $100 for engineers while some teams may drop to $25 daily caps, why organizations are realizing they don't need frontier models for most work when free or cheap tools deliver great results, and how my video editor who I stopped working with came back and created his job again by showing me what he could do with AI to make my content more dynamic and engaging. Chapters 00:00:00 Wall Street's Worst Day of 2025: The $1 Trillion Tech Wipeout 00:05:46 The Data Center Ban Debate: 5.5 Million Jobs on the Line 00:09:28 The Chain Reaction: What Happens If We Ban Data Centers 00:13:47 Your Retirement Account Is an AI Investment: The 45% Reality 00:17:24 AI Moving Faster Than Organizations Can Adapt: The Economist Survey 00:19:00 The Driver's License Analogy: Rethinking AI ROI Measurement 00:21:45 Building a Website in 24 Hours with Muse: The Real AI Capability Test 00:30:01 The Shadow AI Risk: When Enterprise Limits Drive Personal Tool Adoption
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    32 min
  • North Korean Hackers $6.3B Fake Interview Heist, 1 in 4 Candidates Fake & Loud Working’s 17-Day Cost

    North Korean Hackers $6.3B Fake Interview Heist, 1 in 4 Candidates Fake & Loud Working’s 17-Day Cost
    Nov 4 2026
    November 04, 2026: I unpack the 6.3 billion dollar crypto heist at Binance that started with a fake job offer, why the engineer who downloaded malware disguised as an interview assignment thought he was taking a legitimate career step, and how attackers used social engineering to turn hope into the most effective hacking tool in history. Then I get into a hidden wave of graduates who are skipping years of career progression by managing AI agents instead of learning the trade, why PwC found that entry level roles shaped by AI are seven times more likely to require senior skills like leadership and strategic decision making, and how these roles have grown 35% since 2019 while other entry level jobs shrink by 10%. Chapters 00:00:00 The Dream Job Trap: How a $6.3 Billion Heist Started with a Fake Recruiter 00:03:14 Social Engineering at Scale: When Breaking In Means Getting Invited In 00:10:07 The Grunt Work Paradox: Graduates Managing AI Without Learning the Trade 00:13:22 The $6 Billion Spreadsheet Error: Why Judgment Matters More Than Tools 00:15:47 See One, Do One, Teach One: The Apprenticeship Model AI Can't Replace 00:27:12 Let Your Accomplishments Speak: The Cowbell Test for Leaders and Teams
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    30 min
  • 358-Year-Old Merck's Future Ready Formula: Transform While You Perform & Why Leaders Must Eat Last

    358-Year-Old Merck's Future Ready Formula: Transform While You Perform & Why Leaders Must Eat Last
    Nov 2 2026
    I sit down with Khadija Benhamada, member of the executive board and chief people officer at Merck Group, a 358 year old life science, healthcare, and electronics company with more than 62,000 employees across 66 countries. We unpack why leadership is a daily choice not a title, why Khadija believes you're not born a ready leader but become one through aspiration and practice, and how Merck balances two critical energies that every leader must master: performing today while transforming for tomorrow. I explore why performing means understanding customer expectations, delivering with clarity, and using AI to scale productivity faster and cheaper, while transforming is about asking more questions than having answers, building agility at scale, and creating an organization ready for whatever might come next without trying to predict the future. Khadija breaks down why great leaders eat last and put their teams first, why she doesn't count her work hours because impact matters more than time, and why micromanaging kills both energy and results. We get into the four pillars of transformation including being two steps ahead, visionary thinking, risk taking, and scenario planning, why Khadija tells her teams to hope for the best and prep for the worst, and how working for a company that impacts patients with multiple sclerosis and helps people have children creates a noble pressure to always have a plan B. Chapters 00:00:00 Leadership as a Daily Choice: Walking Before You Run at a 358-Year-Old Company 00:07:41 Clarity Versus Transparency: Managing Noise Without Creating Panic 00:09:59 Leaders Eat Last: Why Caring for Your Team Comes Before Everything Else 00:19:08 The Chess Player Mindset: Scenario Planning and Connecting the Dots 00:33:45 AI Productivity Versus AI Transformation: The Two-Speed Strategy 00:38:11 The Agent Manager Dilemma: When Employees Manage Bots Instead of People 00:50:16 Hope for the Best, Prep for the Worst: Building Possibility Over Risk
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    52 min
  • Tech Stocks Massacred, Engagement Hits 15-Year Low & Can An Employee Opt Out Of AI?

    Tech Stocks Massacred, Engagement Hits 15-Year Low & Can An Employee Opt Out Of AI?
    Oct 30 2026
    October 31, 2026: I get into why tech stocks are getting absolutely massacred with the NASDAQ down more than 3.5%, Intel losing 30% of its market cap, Alphabet down 12.6% in its worst day since going public in 2004, and the NASDAQ 100 on pace to lose more than $1 trillion in market value. I look at Gallup's report showing employee engagement hit a 15 year low at 29%, why I think this headline is more dramatic than the reality since engagement started at 26% in 2000 and is now 29% after a dot com crash, financial crisis, pandemic, remote work, and AI, and why a metric that barely moves through all of that isn't a very sensitive alarm. Finally, I unpack the case of David Derman, a research administrator at the University of Kentucky who became the first known humanist to receive a religious exemption from using AI, why the 2023 Supreme Court case Groff versus DeJoy raised the bar for employers to deny religious accommodations, and why religious discrimination charges jumped from 2,400 in 2021 to nearly 14,000 in 2022 during COVID vaccine mandates. Chapters 00:00:00 Bartleby's Rebellion: When Employees Prefer Not To 00:04:09 Tech Stocks Massacred: The $1 Trillion NASDAQ Wipeout 00:15:42 Inside the CHRO Tech Stack: Why Nobody Loves Their Software 00:25:42 The AI Opt-Out: First Religious Exemption Approved at University of Kentucky 00:33:40 The Organic Fruit Niche: When Human-Made Work Becomes a Selling Point 00:34:04 Leader Action Items: Write the Standards Before Someone Says I Prefer Not To
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    36 min
  • Marissa Mayer Outsourced Daughter to AI, AI Builds Nevada, Kills Vegas Jobs & SAP's €2B AI Savings

    Marissa Mayer Outsourced Daughter to AI, AI Builds Nevada, Kills Vegas Jobs & SAP's €2B AI Savings
    Oct 28 2026
    October 28,2026: I unpack Marissa Mayer's viral moment when she asked her AI assistant Dazzle to tell her what made her 10-year-old daughter special, why the internet erupted over whether parents should outsource that kind of thinking, and the three questions you need to ask before handing anything off to AI. Then I head to Nevada where AI is building jobs in the north and replacing them in the south, why more than 100,000 acres of desert east of Reno are becoming one of the world's largest concentrations of data centers providing work for thousands of electricians and pipe fitters, and why 400 miles away on the Las Vegas Strip companies like Zoox and Waymo are replacing human-driven taxis while MGM's call center cuts hundreds of jobs using AI. Finally, I look at SAP replacing expensive AI models inside its software with cheaper alternatives, why their CFO says the move could save more than 2 billion euros in efficiency gains over the next two years even as overall AI spending rises, and how this works like a flat rate plumber who charges $300 to fix a leak no matter which parts go in. Chapters 00:00:00 The Cake Mix Paradox: Why Effort Matters in the AI Age 00:11:03 The Three Questions: Deciding Which Eggs to Keep Cracking Yourself 00:16:42 The Myth of Permanent Jobs: What Construction Workers Already Know 00:21:42 SAP's $2 Billion AI Efficiency Play: Swapping Models Without Cutting Spending 00:24:15 The AI Model Commodity Shift: What It Means for Workers, Vendors, and Customers 00:26:42 Jevons Paradox Returns: Why Cheaper AI Means More AI, Not Less
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    29 min
  • Anthropic IPO Reveals $46B Run Rate, Microsoft Cuts 27% of Staff & Americans Reject CEO Pay Gaps

    Anthropic IPO Reveals $46B Run Rate, Microsoft Cuts 27% of Staff & Americans Reject CEO Pay Gaps
    Oct 26 2026
    October 27, 2026: I unpack Anthropic's IPO filing showing revenue that jumped from under $1 billion a quarter last year to $11.6 billion this quarter, why Wall Street is valuing the company at up to $2 trillion despite $80 billion in reported losses that are mostly accounting charges tied to how they raised money, and what it means when more than half the Fortune 500 are paying six figures or more but spending less than 0.1% of their operating budgets on AI. Then I get into Microsoft offering voluntary buyouts to 60,000 employees including teams in Xbox, Windows, Copilot, and Finance while excluding data centers and sales, why this is a trade of buildings and chips in and people out as the company spends $175 billion on AI infrastructure this year, and why I think we're about to see a massive influx in hiring for communication, PR, and marketing roles because companies are doing a terrible job explaining what AI means to employee. Finally, I look at a Bentley University and Gallup survey showing 84% of Americans say companies should avoid big pay gaps between CEOs and employees but only 15% think their companies are doing a good job of it, why I don't think you should ever care how much your CEO makes as long as you're being paid what you're worth, and the four situations where pay gaps actually do matter. I break down when the explanation doesn't match the decision, when accountability only runs in one direction, when your pay doesn't match your worth, and when leaders' incentives shape your daily life, and why Elon Musk's pay package tied to goals like hitting $8.5 trillion valuation and delivering 1 million humanoid robots shows what happens when compensation is structured around ridiculous astronomical milestones that actually get achieved. Chapters 00:00:00 Google's IPO Warning and the Privacy-to-Scrutiny Trade: What Anthropic's Public Debut Reveals 00:01:10 Anthropic's IPO Filing: The Numbers Behind Claude and What They Tell Us About AI Adoption 00:12:04 The Bear Case: High Valuation, Fixed Costs, and the Dependency Dilemma 00:15:15 Investment Strategy: Who Should Buy Anthropic and Who Should Stay Away 00:24:10 The Bigger Economic Shift: From Tech Hubs to Trades and the 700 Billion Dollar Infrastructure Wave 00:26:48 CEO Pay Gaps Get Failing Grades: When Fairness Matters and When It Doesn't 00:35:54 The Four Times You Should Actually Pay Attention to Pay Gaps and Executive Compensation
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    47 min
  • Musk Gives SpaceX Shares to 73M Kids, Anthropic $100B Promise & ASML Ties CEO Pay to Employee Morale

    Musk Gives SpaceX Shares to 73M Kids, Anthropic $100B Promise & ASML Ties CEO Pay to Employee Morale
    Oct 23 2026
    October 23, 2026: I unpack two very different approaches to sharing AI wealth after Anthropic pledged 5% of its shares to a public benefit fund it controls while Elon Musk announced he'll give one SpaceX share directly to every kid in America, why one approach hands people ownership and the other hands them a promise, and what history teaches us about foundations that drift away from their founders' vision like the Ford Foundation that eventually told Henry Ford's grandson that hospitals weren't part of the program. I explore why Musk's companies support somewhere between 400,000 and a million jobs worldwide, why more than 4,400 SpaceX employees could become millionaires when the company went public, and why giving 73 million children actual equity respects people enough to let them own something instead of waiting for experts to decide who deserves help. I break down the effective altruism philosophy behind Anthropic's approach, why it feels dystopian when the company building technology that might displace millions of jobs also gets to decide which displaced people receive relief, and why Milton Friedman said nobody spends somebody else's money as carefully as he spends his own. Then I get into why AI is everywhere except in the GDP numbers, why companies spent hundreds of billions on AI in 2025 but 95% of projects produced no measurable profit impact, and why the stock market just had its worst day since June with the NASDAQ dropping 2.6% as investors panic about two opposite things at once. I explore why Meta fell 7% after saying it will spend up to $145 billion on capital projects, why CoreWeave's stock crashed from $163 to $54 as local governments put moratoriums on new data centers, and why the real bottleneck isn't chips but power with the U.S. short about six Californias worth of electricity by 2050. I break down why only 2% of U.S. households pay for AI tools, why the most important jobs in the AI era are linesmen and electricians not prompt engineers, and why leaders need to stop asking how to do the same work cheaper and start asking what they'd build if they could build 10 times as much. Finally, I look at ASML, Europe's most valuable company and the only firm that can build the machines needed to make cutting edge chips, tying executive pay to employee satisfaction by measuring whether people understand their roles, whether teams are organized, and whether managers care about them as people, and why this shifts leadership from lagging indicators like revenue to early warning signs that show up before the numbers drop. Chapters 00:00:00 Ownership Versus Promises: Musk's SpaceX Shares and Anthropic's Public Benefit Fund 00:13:23 The Ford Foundation Warning: When Founders Lose Control of Their Legacy 00:23:16 The Real AI Bottleneck: Power Plants, Not Processors 00:26:54 Beyond Cost Cutting: Moving from Bucket One to Bucket Two AI Strategy 00:33:54 The Efficiency Trap: Why Measuring Everything Turns People Into Line Items
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    38 min