Seriously, What Could They Be Thinking? Podcast

Cindy Goodwin-Sak & Jaime Peters
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Welcome to the podcast that unpacks the wildest, weirdest, and most fascinating business decisions through the lens of leadership and finance. whatcouldtheybethinking.substack.com

  1. 2d ago

    Does My Vote Change My Payroll?

    Quick: can you name your state representative? Cindy couldn’t. By the end of this episode, you’ll see why that person may matter more to your business than whoever wins Congress. With the midterms here, Cindy Goodwin-Sak and Jaime Peters do the homework before the outrage. Since 1914, both chambers of Congress have flipped together only 7 times in 56 elections, and economists find that the party running Congress doesn’t predict economic growth. Elections still reach your business, just not where the headlines point. In this episode: * How and when Congress flips, and why flips almost always follow the White House * The real pre-election effect: businesses tap the brakes, cutting investment about 4.8% in election years * How Michigan restaurant owners faced three versions of the same wage and sick-leave law, and who decided which one stuck * Why 69% of adults called the last presidential election a significant source of stress, and what that means for your team Three takeaways for managers: * Expect the whiplash, and know your statehouse. * Plan for the calendar, not the winner. * Give them space, and give them time to vote. And no, neither of us will tell you how we’re voting. Our spreadsheets know. Keep your spreadsheets handy and your coffee strong. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit whatcouldtheybethinking.substack.com

    Does My Vote Change My Payroll?

  2. 3d ago

    Cut the Layer, Keep the Ladder: The Great Unbossing, Round Two

    Block CEO Jack Dorsey says his ideal setup would be all 6,000 employees reporting directly to him. If he held monthly one-on-ones, that’s close to 300 a day. He isn’t the only leader thinking along these lines. Uber cut about 3,300 roles to remove layers and flatten the company. Block cut roughly 40% of its staff, and Dorsey and Sequoia’s Roelof Botha argued that AI can handle the coordination managers used to do. In this episode, Jaime Peters and Cindy Goodwin-Sak ask the question those announcements skip: when a management layer disappears, what happens to the work it was doing? They cover: * Why Uber’s flattening is likely an AI story too. Uber’s memo never mentions AI, but Bloomberg reported the company had used up its annual AI budget by June. * The “Great Unbossing.” This isn’t the first wave of manager cuts. It includes Gartner’s 2024 prediction and Bayer’s experiment with self-organizing teams, which cut its manager ranks by about two-thirds. * What happens to employees and executives. In a Korn Ferry survey, employees whose companies cut management layers reported feeling directionless. Senior leaders doubt they can absorb the work that moves up to them. The hosts point out on air that these are survey findings, not proof of cause. * How people end up as managers. Gallup finds most are promoted for tenure or for success in a non-management job, and most never get formal training. * Where the next leaders will come from. Only 6% of Gen Z want to reach senior leadership, according to Deloitte. A flatter organization may give them even less reason to try. Three takeaways for managers: * Cut the layer, keep the ladder. If you remove a level of management, name who is now responsible for developing the next leaders. * Let AI coordinate, not coach. Status updates and routing can be automated; developing people can’t. If your span of control is about to double, decide what you’ll stop doing before you give up one-on-ones. * Track the coaching, not just the savings. Finance tracks the savings from day one, but almost no one measures whether people are getting meaningful feedback each week. Gallup finds that feedback is a strong predictor of engagement. Next time, we step away from AI to ask whether elections matter to day-to-day business. We’ll talk about politics without talking about politics. Keep your spreadsheets handy and your coffee strong. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit whatcouldtheybethinking.substack.com

    Cut the Layer, Keep the Ladder: The Great Unbossing, Round Two

  3. Oct 26

    Cut Now, Pay Later: The AI Layoff Boomerang

    Over the last three years, Ford brought in or brought back about 350 experienced engineers. They weren’t there to build something new. They were there to catch what Ford’s automated quality systems were missing. CEO Jim Farley credits that effort with saving hundreds of millions of dollars in warranty and recall costs. The savings were booked once. The engineers were hired twice. In this episode, Jaime Peters and Cindy Goodwin-Sak look at the AI layoff boomerang: a company announces cuts because its AI is so capable, then finds out the work didn’t go away. They cover: * “AI washing.” This is Forrester’s term for crediting AI with cuts that were really about cost. * Why Forrester expects half of AI-attributed layoffs to be quietly reversed. * A widely misquoted regret statistic. The 55% figure isn’t 55% of all employers, and it isn’t from Forrester. It comes from Orgvue, and it’s 55% of the leaders who actually made AI-driven cuts. That’s a more damning number. IBM’s HR AI. It handled 94% of employee requests. The 6% it couldn’t handle are the ones that matter. Commonwealth Bank of Australia’s voice bot. The bank reversed the cuts after customer calls spilled back onto the remaining staff. The jobs that come back. They may return offshore, under a new title, or at a reset salary, so the reversal never shows up as a reversal. Three takeaways for managers: * Find the 6% before you cut. Learn the silent work your people do that isn’t in any job description, before severance makes you pay to rediscover it. * A layoff isn’t savings until it survives a year. Run a 12-month check on every AI-attributed headcount decision. Count the full round trip: severance, rehiring, ramp-up, and the cost of the AI itself. * Say the real reason. If the cut was financial and AI was only the explanation, nobody is tracking whether it worked. Your team also learns to see AI as a threat instead of a tool. Next time, we cover the other half of the story: companies cutting the people who manage the work, not the people who do it. Keep your spreadsheets handy and your coffee strong. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit whatcouldtheybethinking.substack.com

    Cut Now, Pay Later: The AI Layoff Boomerang

  4. Sep 24

    Please Regulate Us: Why AI's Biggest Rivals Just Asked for a Referee

    We’re back after a fun-filled summer of activities. We have so many questions!!! On September 12, three men who agree on almost nothing (Dario Amodei, Sam Altman, and Elon Musk) all said the same thing within hours: the AI industry should slow down. Even Rahm Emanuel said he’d never seen an industry ask to be regulated. So did these guys discover a conscience, or a moat? Jaime and Cindy do the homework before the outrage. They walk through the OpenAI incident that set this off, in which about 1,200 test agents built their own secret message board and 700 of them went on to attack Hugging Face. They explain why “the agents cheated” is really a story about the goals we set. And Jaime makes the case that “please regulate us” might have as much to do with the balance sheet as with safety. Then they bring it back to your team, with three takeaways: * Ask your vendors for the transparency the labs are now offering strangers. * Your agents will hit whatever goal you set, one way or another. * Congress has gone home, so you’re the regulator of your own shop. Plus a four-item checklist you can start this quarter, and a mystery: one of these three men asked the world to pause AI once before, and then started an AI company. Keep your guess in your back pocket. Keep your spreadsheets handy and your coffee strong. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit whatcouldtheybethinking.substack.com

    Please Regulate Us: Why AI's Biggest Rivals Just Asked for a Referee

  5. Jun 9

    Houston, We Have a Loophole

    The largest IPO in history is about to launch and Jaime and Cindy aren't strapping in quietly. SpaceX hits the Nasdaq on June 12 at a $1.75 trillion valuation, except the "space company" is now really three companies in a trench coat: rockets and Starlink, the platform formerly known as Twitter, and a cash-incinerating AI unit. The twist isn't the size; it's the quiet rewrite of the index rules that can fast-track SpaceX into the funds inside your retirement account in as little as five trading days; no seasoning, no profits required. Jaime Peters breaks down how passive investing became forced buying, why the S&P 500 alone refused to play along, and who actually pockets the upside before retail ever gets a share. Cindy Goodwin-Sak pulls the management lesson out of the chaos: when someone changes the rules underneath you, which anchors do you refuse to move? Seriously, what could they be thinking? This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit whatcouldtheybethinking.substack.com

    Houston, We Have a Loophole

  6. May 18

    Sole Searching

    What do you get when a $4 billion wool sneaker brand sells its entire identity for $39 million and reinvents itself as an AI GPU rental company…in 16 days? Finance expert Jaime Peters and leadership researcher Cindy Goodwin-Sak untangle the wild, woolly tale of Allbirds' transformation into NewBird AI, asking the uncomfortable question every manager should face: when a publicly traded company completely abandons its original mission, who exactly authorized that flight path? And, does it even matter if the stock surges 700%? This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit whatcouldtheybethinking.substack.com

    Sole Searching

  7. May 6

    More Customers, Worse Numbers

    OpenAI may be the most talked-about company in tech, but even visionary companies have to pass the budget test. In this episode, Dr. Cindy Goodwin-Sak and Dr. Jaime Peters pick up where they left off on OpenAI’s business model and go deeper, this time into the IPO mechanics that could affect everyday investors whether they realize it or not. Jaime breaks down exactly how an IPO works: what it means to shift from private to public accountability, why fewer companies are going public today than in the 1990s, and what a trillion-dollar valuation actually represents in terms of new cash versus converted private equity shares. (Spoiler: the $40 billion and the $960 billion are not the same thing.) Cindy brings the leadership lens with what it means organizationally when you suddenly have millions of eyes on your decisions instead of a handful of private investors, and why the forcing function of public scrutiny might actually be good for OpenAI’s long-term health. Together they work through the uncomfortable math: rising compute costs, shrinking margins, a cash burn projected to hit $190 billion by 2030, and what all of that means for the everyday Americans who hold index funds in their 401(k)s, and who may have no choice but to own a piece of whatever comes next. The takeaway for managers? Demand isn’t the same as health. Know your costs. Build optionality. And tell your team the truth when things are changing, even when the hype says otherwise. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit whatcouldtheybethinking.substack.com

    More Customers, Worse Numbers

  8. Apr 6

    OpenAI's Data Center Gamble

    What does it actually take to run an AI company? And can OpenAI afford it? This week, Cindy Goodwin-Sak and Jaime Peters kick off a multi-part series diving into the business of being an AI company, not just using one. It all started with a CNBC article on OpenAI’s data center pivot that had them talking for days. So they decided to break it down for you, starting from the ground up: what goes into a data center, why AI requires specialized (and expensive) computing hardware, and just how much energy and water these facilities consume. Spoiler: think the combined electricity usage of Chicago, LA, New York, Dallas, and St. Louis, and then double it. They also unpack OpenAI’s original strategy for scaling its infrastructure (the Stargate initiative, its partnerships with Microsoft, Oracle, Amazon, and SoftBank) and what any manager can learn from those moves around vertical integration, vendor diversification, and cost control. But here’s the catch: OpenAI generated $20 billion in revenue last year, and their projected compute bill through 2030 is $600 billion. The math isn’t mathing. Tune in next week to find out what happens when reality sets in. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit whatcouldtheybethinking.substack.com

    OpenAI's Data Center Gamble
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Welcome to the podcast that unpacks the wildest, weirdest, and most fascinating business decisions through the lens of leadership and finance. whatcouldtheybethinking.substack.com

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