What FAANG execs read this week — June 1–8, 2026

One executive posted explicit recommendations this week; a second left scholarly fingerprints without pointing at a specific book. The June 1–8 window was the thinnest since this digest launched: Jack Sallay's LinkedIn activity is fully behind a login wall, Marvin Chow spent the week on Google I/O coverage, and the broader FAANG discovery scan returned nothing for a fourth consecutive cycle. Richard Hua carried the signal — two posts, three separate research citations, a coherent theme running through both.

Richard Hua — CEO of EPIQ Leadership Group and former Worldwide Head of EPIC Leadership at Amazon (25K LinkedIn followers) — posted on June 5 framing purpose as the durable human edge in an AI-saturated workplace. 1 Three bodies of work anchored the post.

The first is Simon Sinek's Start with Why — the 2009 book and its accompanying TED talk, among the most-cited works in the leadership canon. Hua used it as the structural premise: "having purpose (your Why) is the primary element for long-term success, far more than the how or what." 1 The framing is familiar, but Hua connected it directly to AI displacement: purpose is the one input the model cannot replicate.

The second citation is Angela Duckworth's grit research — Duckworth is a professor at the University of Pennsylvania and author of Grit: The Power of Passion and Perseverance (2016). Hua quoted her finding that "the most powerful contributor to grit is purpose," defined as the intention to contribute to the well-being of others. 1

The third is a University of Buffalo study on stress and mortality. Hua cited the finding that people experiencing extreme stress have a 30% higher risk of death — unless they are actively helping others, in which case the elevated risk disappears entirely. 1 He did not name the specific paper, and the exact study is not independently identified in collected sources.

His conclusion: "In the AI era, our competitive advantage isn't just what we do. It's why we do it. That's something AI can't replicate. It's irreplaceable."

The following day, June 6, Hua posted on a related but distinct concept: relational energy — the measurable charge people either add to or drain from those around them. 2

The research he cited: Owens, Baker, Sumpter, and Cameron (2016), "Relational energy at work: Implications for job engagement and job performance," published in the Journal of Applied Psychology, 101(1), 35–49. 3 Kim Cameron and Wayne Baker, both professors at UMich Ross School of Business, are the researchers most closely associated with the concept. The study found across four separate studies that the highest-performing groups in organizations cluster around individuals who generate relational energy — colleagues who leave others feeling more capable and motivated after an interaction.

Hua's framing was personal: he traced his career trajectory at Oracle and AWS to relationships built over years. His takeaway for the post: "The most successful leaders I've known aren't just smart. They are energizing. And the wonderful thing about relational energy is that it's not a personality trait. It's a choice you make."

The two June posts form a coherent pair. June 5 argues that purpose protects performance under stress. June 6 argues that the way you carry that purpose in relationships — whether you deplete or energize those around you — determines whether it compounds.

Ethan Evans — former Amazon VP (15+ years), founder of Level Up Leadership (171K LinkedIn followers, named one of Maven's Top 100 instructors this week) — published no explicit reading recommendations during June 1–8. His seven LinkedIn posts this window were predominantly course promotions and a podcast launch with Codie Sanchez. 4

The exception was a June 3 post on decision-making errors in job selection, where Evans built his argument on two academic frameworks without explicitly recommending either source.

The first is Christopher Hsee's Evaluability Hypothesis — a 1996 paper in Organizational Behavior and Human Decision Processes (67:3, 247–257), cited roughly 1,600 times. 4 The core finding: when people evaluate options separately rather than jointly, they overweight attributes that are easy to evaluate numerically (salary, price) and underweight attributes that resist direct comparison (growth potential, work quality, boss quality).

Evans applied it to job offers: "Salary numbers are easy to evaluate and mostly guaranteed. $154,000 is clearly more than $149,900, and you know you will be paid that amount. But who is the better boss, which company will promote you faster, and what work you will enjoy are unquantifiable and uncertain."

The second is Daniel Kahneman's concept of attribute substitution, which appears in Kahneman's 2011 book Thinking, Fast and Slow (Farrar, Straus and Giroux) and in the earlier academic literature. The mechanism: when the mind encounters a hard question ("which job will make my life better?"), it quietly substitutes an easier question ("which job pays more?") and answers that instead — without flagging the swap. Evans: "Our minds like to simplify, so when faced with the hard, ambiguous question of 'which job will make my life better?' we substitute that question with the much easier one to answer: 'which job pays more?' But our mind doesn't label the swap." 4

These are academic frameworks used as teaching tools, not recommendations to read specific texts — documented here for completeness.

No item was endorsed by more than one executive. Hua's two posts converge on a single argument — purpose and relational energy as the human-layer advantages that compound where AI cannot. Evans' decision-making post arrived from a different intellectual tradition (behavioral economics and judgment research) but touches the same underlying problem: the gap between what people say they optimize for and what they actually optimize for in high-stakes choices.

Jack Sallay's LinkedIn activity remains inaccessible. Marvin Chow posted twice this week on Google I/O production — no reading recommendations for a third consecutive cycle.