Built to Hold, Not Hype

Generally speaking, Seattle is where you build the system that can’t fail; SF is where you decide to change the rules. Combine those instincts and you get companies that both ship boldly and stand up to reality.

Seattle’s startup scene is a BigCo-shaped ecosystem. The center of gravity is Amazon/Microsoft/Starbucks training, not YC-style blitzscaling. That produces world-class operators and systems thinkers, but fewer “set the rules, break the market” founders. The “break the market” bit is starting to wear thin with many (but that is another article). Founders and recruiters I know describe SF talent as more default-entrepreneurial; Seattle talent as more “show me how to get started.” Recent founder roundtables echo this: SF tolerates wilder bets and higher risk; Seattle is supportive, “chill,” and a bit less urgent.

Part 5: The Ethical Imperative: Redefining Organizational Culture in the Age of AI

As we conclude our exploration of the evolving data culture in corporate America, we find ourselves at a critical juncture. The pendulum swings we've observed—from the data-driven efficiency focus of the 1990s to the purpose-driven revolution of the 2010s—have set the stage for a new era of complexity. The advent of artificial intelligence (AI) is not just another technological advancement; it represents a fundamental shift in how organizations must approach skill development and organizational design for data, purpose, and ethics.

Part 4: The Trilemma of Modern Business: Navigating Data, Purpose, and Ethics in the AI Era

As we stand at the precipice of a new era in corporate evolution, the landscape before us is far more complex and nuanced than we could have imagined even a decade ago. The simple dichotomies of the past—efficiency versus humanity, data versus intuition—have given way to a trilemma that threatens to reshape the very foundations of organizational structure and leadership. This piece aims to unravel the intricate web of challenges facing modern businesses as they attempt to balance data-driven decision making, purpose-driven cultures, and the looming ethical considerations of the AI age.