Wellable Weekly

Your weekly dose of workplace & HR trends, wellness insights, and practical tips to help your team thrive. For more workplace insights, visit: https://www.wellable.co/

Wellable Weekly is a news podcast hosted by Wellable, with 40 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Wellable hosts Wellable Weekly, a news show with 40 episodes published.

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  Wellable Weekly

  Micro Joys and Marijuana: How Gen Z Is Rewriting the Workday Reset

  Aug 12, 202623 min

  In this week's episode, Nick and Geoff dig into two surveys that together reveal how Gen Z workers are managing their energy, focus, and mental health at work. New data on "micro joys" shows that short, restorative breaks are already happening with or without employer support—and the data makes a compelling case for getting ahead of the trend. Then, a landmark finding that daily marijuana use has surpassed daily alcohol consumption for the first time raises a questions most employers have not answered. Key Takeaways 77% of Gen Z workers are already intentionally building "micro joys" into their workday, and 82% say they have their best ideas away from their desk Breaks are happening with or without employer support, and the case for sanctioning them is both a productivity and a culture argument Gen Z's top workplace perks are healthy snacks and beverages and more time outdoors, both at 43%, far ahead of extra days off at 24%, signaling a generational shift toward making the workday itself more sustainable rather than just maximizing time away from it In a tight labor market, many employees are reluctant to step away without an explicit organizational endorsement, which is why employer-sponsored break tools matter not just for the break itself but for the permission they signal Daily marijuana use in the US has surpassed daily alcohol consumption for the first time, with Gen Z being the only generation where marijuana use now exceeds alcohol use after work 51% of Gen Z workers report using THC during the workday, and 52% of the full workforce across all generations report self-medicating in some form during work hours

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  Wellable Weekly

  Ghost Jobs, Stealth Layoffs, and Lower Pay

  Aug 5, 202619 min

  In this week's episode, Nick and Geoff take a break from AI headlines to dig into three stories that together paint a troubling picture of the current job market. In Texas, LinkedIn is under investigation for ghost job postings. A new survey finds 72% of employees believe return-to-office mandates are stealth layoffs. Lastly, Glassdoor data shows 57% of recently laid-off workers are considering accepting lower pay, with women bearing a disproportionate share of the cuts. Key Takeaways Texas has opened a consumer protection investigation against LinkedIn under the Deceptive Trade Practices Act, alleging between one-fifth and one-third of job postings are ghost jobs; Nick proposes a practical fix: require employers to periodically verify postings are still active, automatically removing any that go unconfirmed LinkedIn's new AI slop flag for content is its clearest acknowledgment that platform trust is eroding, but no equivalent tool exists for job postings that would solve for the trust problem 72% of employees believe return-to-office mandates are being used as stealth layoffs, with an average trust score of just 59 out of 100 for employer RTO motives—meanwhile, 46% of workers admit to coffee badging, coming in just to swipe a badge before leaving Nick draws a clear distinction between employers who always communicated an in-office expectation and those who hired remotely and are now changing the terms (only the latter represents a genuine breach of the employment social contract) 57% of recently laid-off workers are considering accepting lower salaries, and pay cuts are disproportionately affecting women, backtracking after three decades of progress on narrowing the gender pay gap in a relatively short period

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  Wellable Weekly

  AI Lawsuits Capturing HR's Attention

  Jul 29, 202621 min

  In this week's episode, Nick and Geoff dig into two landmark AI employment lawsuits every HR leader should be following, and a new workforce sentiment story. Meta employees are suing over an AI-driven layoff process they claim targeted workers on protected leave. The Workday class action advances on the question of whether AI vendors or their employer clients bear liability for hiring bias. Lastly, a survey shows younger workers increasingly describe their relationship with their employer as a "situationship" with no long-term commitment on either side. Key Takeaways Twenty-six current and former Meta employees allege the company used AI to score, rank, and select employees for termination without neutralizing protected leave as an input Meta's spokesperson categorically denies AI made those decisions, creating a stark factual divide at the center of the case Mobley v. Workday is advancing through the courts on the argument that AI hiring tools that replace functions normally performed by employers carry commensurate liability Workday's defense—that its tools only screen candidates and final decisions rest with employers—may be valid but puts its own customers on notice that they bear the liability for how AI outputs are used HR and IT leaders should be asking vendors directly how their tools handle protected class attributes, what bias testing has been conducted, and where liability sits before using AI in any consequential hiring or termination process 59% of workers report no clear long-term path at their current employer, and the resulting "situationship" is partly a job market story Employees cannot afford to leave but see no investment in their development either, a dynamic compounded by the hollowing out of middle management and the redirection of organizational energy toward AI over people

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  Wellable Weekly

  The AI Token Gold Rush Is Over (At Least For Tesla). Now What?

  Jul 22, 202622 min

  In this week's episode, Nick and Geoff reunite after Nick's summer hiatus to break down three recent headlines. Tesla caps employee AI token spending at $200 a week, a dramatic reversal from the gamified leaderboards of just six months ago. Starbucks bets it can replace $400 million in enterprise software spend by rebuilding tools in-house with AI. Lastly, Gartner projects one in five companies will cut more than half their middle managers by year-end, a structural efficiency trend with consequences that are only starting to show up. Key Takeaways Tesla now requires manager approval for AI token spend above $200 per week , and Uber blew through its entire 2026 token budget by March Caps might be signaling negative ROI, not just cost management, since companies with these resources would keep spending if the returns were there Starbucks is attempting to replace roughly $400 million in annual enterprise software contracts by rebuilding tools in-house with AI and internal engineers If Starbucks succeeds, it could mark a meaningful shift in the build-versus-buy calculus for enterprise software and accelerate the so-called SaaSpocalypse for software vendors Gartner projects one in five companies will eliminate more than half their middle managers by the end of the year, but a cautionary case study shows a VP of engineering with 47 direct reports approving decisions in Slack with no context or coaching until their best engineer quietly quit Only 6% of Gen Z aspires to senior leadership according to Deloitte research, a rational response to watching middle management disappear and remaining managers stretched to unsustainable spans of control

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  Wellable Weekly

  Do's & Don'ts of Modern Hiring with Kat Kibben

  Jul 15, 202627 min

  In this week's episode, Geoff sits down with Kat Kibben , keynote speaker, bestselling author, and one of LinkedIn's top voices on hiring. Drawing on 15 years working across HR technology, employer brand strategy, and recruiting education, Kat shares a no-nonsense playbook for key stages of the hiring funnel, from writing job postings that actually attract the right candidates to using AI screening tools without embedding bias. Key Takeaways The real reason you are getting too many unqualified applicants is almost always the lack of specificity in job posting, not the volume of candidates in the market Candidates should apply if they meet 60% or more of a job posting's requirements, because recruiters rarely expect 100% fit and most postings significantly overstate what is actually needed AI screening tools should be limited to clear yes-or-no questions at the initial stage and used to clarify ambiguous criteria in the maybe pile—machines should gather information, not make hiring decisions When companies use AI or bot-driven screening, candidates often are not told they are talking to a bot and do not know how to adjust, so these interviews reward the most confident performers rather than the best-fit candidates Bank of America's AI upskilling framework centers on one principle—never trust the yes—reflecting a shift from teaching prompt skills to building the human judgment needed to evaluate AI outputs critically

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