On Culture: Traction in the Trough

Myste Wylde
Jul 31
6 min read

Dear Culturati Insider,

I’d never heard the phrase “trough of disillusionment” until yesterday morning. Mark McClain, CEO & founder of SailPoint Technologies, referred to the Gartner hype cycle during a conversation with Eugene and me about AI, leadership, and the weight of this moment. He named the leader’s role in defining reality (though not distorting it) in our VUCA* world shaped by AI disruption, economic swings, and external noise. He also left us with a nifty analogy of AI posed as a question: "Why do race cars need good brakes?" The answer is so that they can go fast. And we don't trust our brakes on AI yet.

Less than an hour after our call, there it was again: "trough of disillusionment,” buried in step four of a five-step playbook on change resilience. (See the Baader-Meinhof phenomenon.) The “trough” is that stretch of the Gartner hype cycle where the novelty wears off, results stall, and confidence dips. And if you’re leading anything meaningful right now including AI adoption, inclusion efforts, transformation strategy, even your team’s morale, you probably know the feeling. We’ve come off the high. And now we’re here, asking harder questions... What really matters? What's working? What's not? And what do we do next?

Mark didn’t offer easy answers, but he offered something better: a path to clarity. He spoke about courage not as a dramatic act, but as conviction to do the right thing even when it’s not on-trend. And about how, as his company grew, values, not vision, became their real North Star. Knowing who we are and who we want to be is foundational. That's how you achieve clarity and lead through change, especially as organizations scale.

Leadership in the trough can be rough, but values help us hold focus without denying the noise or becoming distracted. Embedding these principles systemically is how organizations can flex without falling apart. Clarity of purpose shouldn't shift with disruption.

These articles reflect further on resiliency. AI strategy, workforce planning, and mid-year resets all point to the same truth: the ability to bounce back (sustainably) isn’t grit, it’s design. Agility comes from structure, not speed. And culture, when built intentionally, becomes the operating system that helps us adapt without losing ourselves. We may be in the trough, but the organizations doing the necessary work now are the ones best positioned to step on the gas later.

For the long run,

Myste Wylde, COO

*VUCA: Volatility, Uncertainty, Complexity, Ambiguity >>> On Culture: Successful Leadership in a VUCA World

A Guide to Building Change Resilience in the Age of AI

Harvard Business Review

By Karim R. Lakhani, Jen Stave, Douglas Ng and Daniel Martines

Summary: Despite widespread AI adoption, only 26% of organizations are realizing tangible value, with those outperforming peers showing 45% cost savings and 60% higher revenue growth, according to a BCG global survey of 1,000 CXOs. The problem isn't tech; it's people and process. 70% of implementation challenges stem from an inability to adapt and scale new ways of working. To thrive, leaders must build change resilience, a repeatable capacity to sense weak signals, rewire talent and tools rapidly, and lock in learnings so the next move starts stronger. Companies like Shopify, DBS, Moderna, and P&G are proving that resilience isn’t a trait, it’s a system built through micro-experiments, cross-functional squads, real-time sentiment data, and upskilling tied directly to business impact.

READ ARTICLE IN FULL

Mid-Year Motivation: How to Realign and Restart

Psychology Today

By Harry Cohen, PhD

Summary: By mid-year, most goals lose momentum not because of failure, but because of distraction, fatigue, or misalignment. The best-performing leaders treat this as a strategic inflection point to reflect, reset, and reengage. Emotional clarity is a leadership skill. Reframing setbacks as data, not defeat, builds resilience. Recognizing small, unseen wins shifts teams from self-criticism to momentum. Micro-goals and habit systems outperform big intentions. A few minutes of reflection or a 5-minute task can reignite action. Leaders can ask: are my goals still connected to purpose? Is my system still serving me? Add structure where motivation lags, and inject joy intentionally. Sustainable performance is more about design than willpower.

READ ARTICLE IN FULL

Three Steps To Empower Organizational Agility

Forbes

By Elaine Pulakos

Summary: Agility is not a byproduct of speed or spontaneity. Agility is built through structure. A global study of 300 companies found that those who embed agility into their systems see 150% higher returns on invested capital and 500% higher return on equity. The key lies in three leadership moves: (1) stabilize first by setting clear priorities and removing barriers, (2) rightsize teamwork by cutting wasteful collaboration and defining when it's actually needed, and (3) empower self-correcting teams that can raise and fix issues without blame. Agility thrives in cultures with psychological safety, efficient workflows, and real-time performance tracking.

READ ARTICLE IN FULL

Annual Workforce Planning Is Broken. Here's the Smarter, Real-Time Alternative

Entrepreneur

By Ryan Wong

Summary: Annual workforce planning is no longer viable in a world where AI, geopolitics, and volatility can reshape labor needs overnight. Companies still clinging to rigid yearly cycles risk falling behind, with poor planning contributing to an estimated $8.5 trillion in unrealized revenue by 2030. The alternative is continuous workforce planning, powered by real-time people data, business metrics, and AI-driven scenario modeling. This approach helps leaders right-size teams, forecast vacancies, and adapt faster to shifting conditions. Firms using this model have saved millions and gained critical agility. The leadership takeaway: stop treating workforce planning as a static budget line. Treat it as a live, strategic function that integrates HR, finance, and operations because speed of insight now defines business performance.

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The Bitter Lesson versus The Garbage Can

One Useful Thing

By Ethan Mollick

Summary: Most organizations are messier than they admit, shaped by ad hoc decisions, undocumented processes, and informal workarounds. Classic research calls this the “Garbage Can” model, and it explains why scaling AI inside companies is so difficult. Traditional AI deployment assumes structure, but the reality is chaos. Meanwhile, the “Bitter Lesson” from AI research shows that handcrafted logic is often outperformed by brute-force, outcome-based learning. Instead of mapping every broken process, forward-thinking leaders are redefining success by outputs and training AI to hit those targets, regardless of how. So instead of chasing perfect process design, define quality, train on results, and let AI navigate the noise. The next competitive edge may not come from understanding your organization better, but from letting AI learn how to outperform it.

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