People Managing People

Most leaders are making AI decisions in the dark—restructuring roles, cutting headcount, and chasing use cases without understanding how work actually gets done. Not the org chart version. The real, messy, task-level reality. And that’s a problem, because when you don’t understand what creates value, automation becomes guesswork dressed up as strategy.
Victoria Pelletier joins the show to challenge the prevailing top-down approach. Instead of starting with AI capabilities, she argues for working backwards from business strategy to task-level workflows, skills, and human contribution. The result? A more grounded, more human, and frankly more effective way to redesign work in an AI-driven world.
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Everything is urgent—until it isn’t. When every ticket is a fire, teams don’t move faster; they burn out. In this episode, Barbara Nicholas (CEO at Polly) borrows a lesson from search and rescue: urgency only matters when it actually changes outcomes. Most white-collar work isn’t life or death, but we’ve built cultures that pretend it is—and people are paying for it in cognitive overload and constant distraction.
Barbara walks through how she operationalizes a triage system across her company—embedding shared language into tools like Slack, Notion, and Jira, and empowering teams to challenge urgency instead of blindly accepting it. From AI experimentation to customer demands and internal comms, this is a conversation about cutting through noise, making better calls under pressure, and remembering what actually matters.
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AI in HR is finally moving out of the pitch deck and into the messy reality of day-to-day operations. In this conversation, Tim Fisher sits down with Josh Rod from HiBob to unpack what’s actually changing—and what’s still just noise. The headline? Most organizations aren’t chasing some agentic, fully automated future. They’re trying to make today’s workflows less painful, faster, and marginally more effective.
But underneath that pragmatic adoption sits a deeper shift: the structure of work itself is being quietly rewritten. When every employee becomes a “manager” of AI, the old hierarchies start to wobble. HR isn’t just implementing tools anymore—it’s being asked to design the operating system for how humans and machines collaborate. And that’s where things get interesting.
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You don’t need to be using AI constantly to be hooked on it—you just need to feel relief when you do. That’s the uncomfortable premise at the heart of this conversation with psychologist and conflict expert Dr. David Zierk. AI doesn’t just give you answers; it removes uncertainty. And in doing so, it quietly rewires how you think, learn, and connect.
What starts as convenience can quickly become dependency. Leaders, in particular, are at risk of trading away the friction that produces insight, the curiosity that fuels growth, and the empathy that sustains relationships. The result? Faster answers, thinner thinking, and a growing gap between knowing what to do and actually doing it.
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AI is supposed to free people up for “higher-value work.” Fine. But what, exactly, is that work? In this episode, David Rice talks with cyberpsychology researcher and psychotherapist Dr. Rachel Wood about the part of AI adoption most organizations keep skimming past: the human cost of automating too much, too quickly, without a real philosophy for what should remain deeply, stubbornly human.
Their conversation cuts through the usual AI optimism and gets to the more uncomfortable truth. Some friction should absolutely go away. Nobody needs to spend an hour copying and pasting spreadsheet data. But some friction is the job: disagreement, discernment, hard conversations, learning by getting things wrong, and figuring out who you are when your expertise is suddenly easier to imitate. This episode is really about that distinction, and why leaders need to stop treating AI as a software rollout and start treating it as a human development challenge.
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