Tip
Ami Vora talks about choosing jobs: “I try to work through the spreadsheets and then tear it up. The thing that has determined where I do my best work is a feeling of being at home. When I walk through the doors, do I feel like I’m lucky to be there?”
Turns out career transitions at the executive level work the same way.
You’re evaluating whether to take the Chief AI Officer role at the enterprise company. Better comp, bigger scope, impressive title. Your spreadsheet says yes. But when you imagine walking through those doors Monday morning, something feels off. The leadership team dynamic, the way decisions get made, the culture around taking risks—it doesn’t feel like home.
Younger managers optimize spreadsheets because they haven’t calibrated their intuition yet. They calculate: “If I take this role, here’s where I’ll be in five years.” They don’t trust the feeling because they haven’t learned what “home” feels like at work.
You have. Your intuition is trained on dozens of roles, hundreds of teams, thousands of interactions. You know what environments let you do your best work. You know which leaders have your back. You know the difference between “impressive on paper” and “this is where I’ll thrive.”
That calibration—knowing what “home” feels like professionally—took 25 years to develop. It’s pattern matching on environments, leadership styles, team dynamics, risk tolerance, decision-making culture. The spreadsheet shows the same data to everyone. Your gut knows which variables actually matter for YOUR performance. That’s the advantage.
Context
Ami Vora has held leadership roles at WhatsApp, Facebook, Faire. Her approach—“put on the coat of the job” emotionally before analyzing it logically—requires deep self-knowledge that only comes from experiencing enough roles to know which patterns predict success for you specifically.
For experienced executives evaluating opportunities, this isn’t mystical intuition—it’s decades of calibration on which environments unlock your best work. Younger managers don’t have that training data yet.