Steps to Change: A Learning & Development Podcast

There are a handful of genuinely useful data points - the Goldman longevity extrapolation and the IMF cognitive-age equivalence study stand out - but a significant portion of the episode is generic HR advice, extended promotional content about the host's drama-training company, and platitudes like 'say something rather than be silent.' The ratio of novel claims to filler is low for a 33-minute episode.

“a person in the year 2022 who was 70 years old had uh, the same cognitive ability as a 53 year old in the year 2000”

“in India each generation was defined by almost a five year period because the, the rate of change was so rapid there”

The horoscope analogy for generational research is a genuinely fresh frame, and applying longevity science to the workforce-generation-count problem is an underused angle. However, the bulk of recommendations - reverse mentoring, ERGs, returnship programs, AI bias warnings - are well-circulated HR concepts that add little new thinking.

“a lot of the general generational research. Um, though it's useful, I find it's often like horoscopes in a newspaper”

“soon we're going to actually be having six or maybe seven different generations in the workplace”

Stephen Golden held senior practitioner roles at genuine scale - global head of DEI at YouTube/Google and 20-plus years at Goldman Sachs where he ran specific programs like the Returnship across Asia-Pacific. He is not a career thought-leader; he has operational credibility. The score is tempered because his insights, while grounded in experience, rarely reach the depth his résumé would suggest is possible.

“I'm the former global head of DEI for YouTube, uh, which is a part of Google and Alphabet”

“My teams ran the uh, returnship program in Hong Kong, Singapore and India”

The episode has more concrete evidence than a typical HR podcast - the IMF study with 41 countries, specific age-equivalence figures, the Goldman longevity extrapolation, and the named Greygler ERG are all usable data points. Attribution is sometimes loose ('research that came out this year, 2025') and many supporting claims remain vague, limiting the score.

“Goldman Sachs recently extrapolated the linear age trend that's been underway for the past 150 years, they actually believe the average person born today would live up to 110 years”

“a person who was age 70 in 2022 had the same physical traits and abilities of a 56 year old in 2000”

The host occasionally asks targeted follow-ups - pushing on leadership behaviors that made the Google ERG advice actionable is the strongest example - but too often he uses the conversation as a vehicle to showcase his own company's drama-training methodology, asks open-ended softballs, and never challenges a single claim. There is no productive disagreement or probing of weak assertions.

“what were the behaviors and the mindsets and the leadership skills they were showing that really allowed them to take on the advice from the different generations”

“take us along this journey some more. Stephen, what's the next piece of advice you want to jump into?”