How to know what you really want
From career choices to new purchases, use René Girard’s mimetic theory to resist the herd and forge your own path
Here are some of my impressive achievements.
I broke my femur in a football game my freshman year of high school. I didn’t handle it well. My grades tanked, and I was kicked out for fighting. In college, I chased the money. I chose a major that I didn’t like and got a job on Wall Street mostly through hustle. I left it to start a healthy vending machine company out of a spare bedroom in Hollywood at age 23. I co-founded two more companies and had everything I thought I wanted as I was nearing my late twenties. Then I realized I hadn’t “found” anything at all. I was on a Sisyphean journey with no escape.
I spent three years in Italy practicing the art of meriggiando (whiling away the afternoons with long lunches, wine, and conversations with good company) and studying philosophy, theology, and classic literature. I couldn’t continue to start businesses and chase dreams without understanding the truth about the human condition—and myself.
My work revolves around exploring human ecology—how our technology, relationships, politics, economics, education, and other systems affect what we want. In the end, each of us is either helping everyone that we come into contact with to want more, to want less, or to want differently. I believe that the future, like each of our lives, depends on what we learn to want today.
From career choices to new purchases, use René Girard’s mimetic theory to resist the herd and forge your own path
What does Athens have to do with Jerusalem—and what do either have to do with Silicon Valley? NASA can land a
What is Mimetic Desire? Nearly everyone (unconsciously) assumes there’s a straight line between them and the things they want. >>
I reached out to Liana Finck during the early, dark days of the pandemic in April 2020. My fiancé, Claire,
My notes as a creator in an algorithmic world—learning when to ride and when to drive
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My notes as a creator in an algorithmic world—learning when to ride and when to drive.