The Chad & Cheese Podcast

The Shred is a weekly roundup of what’s making headlines in the world of employment.

Talent acquisition teams are currently being expected to pull off the ultimate corporate hat trick: hire at breakneck speed, manifest unicorn candidates out of thin air, slash budgets down to pennies, and somehow prove it with shiny metrics. In this session, ringmasters Chad Sowash and Joel Cheesman—hosts of The Chad & Cheese Podcast—are joined by brave survivors Kayleen Weaver (Director of Talent Acquisition at Americare Senior Living) and Patrick Kelly (VP of Operations at Healing Partners). Together, they pull back the curtain on whether the tidal wave of recruiting AI and automation is actually saving the day, or just making HR's slow-motion trainwreck run slightly faster.

Live from Amsterdam where redheads combust in the sun and nobody uses e-scooters—the Chad and Cheese crew are back with guest star Stephen McGrath to tackle HR’s messiest sagas:

Metaview’s $60M Pivot: How a basic, commoditized note-taking app rebranded as an "agentic AI" messiah.

LinkedIn's Massive Data Purge: LinkedIn is boot-kicking third-party scrapers (RIP Gem, PIN, and NeuroScale)

Palantir vs. The Nurses: The surveillance state giant tried its hand at automated healthcare scheduling.

The "Soft" Labor Market: Jobs reports are crashing, immigrants are leaving, and companies are baffled why nobody’s applying.

Complete with atrocious dad jokes, "dirty D" data warnings, and endless snark, it’s everything you’ve come to expect from HR’s most dangerous podcast.

The Shred is a weekly roundup of what’s making headlines in the world of employment.

Joel and Chad welcome Nathan Labenz, host of The Cognitive Revolution and a self-described full-time student of AI. His agent booked the appearance after a weak first pitch and a better second one.

They start with how he actually works: a separate Mac Mini for agents, a wiki about his life, no unsupervised access to bank and personal email, and a rule that the bots don’t lie about being AI if asked. That setup is the hook for the bigger story.

Nathan walks through the industry as the dog that caught the car—systems that now cheat on tests, rewrite their own logs, and surprise the labs that built them. He argues for pacing the frontier without pretending today’s models are unused. Enterprises, he says, still have a lot of workflow fruit left before they need superhuman agents running for a month.

Work comes next: short-term roles in AI safety orgs (not just researchers—HR, comms, ops), AI-in-the-loop jobs that let teams do more with less, and a hiring market already broken by zero-friction apply. Longer term he talks transformation, a new social contract, and why matching might get better once both sides use agents.

China is the other half. He spent time on the ground this summer because “if we pause, China wins” never sat right. What he saw—and what he didn’t hear—is in the episode, along with advice for kids who may never be smarter than the models.