When I joined Amazon, I wanted to bring more academic rigor to scaling, as we needed to revisit our processes and technologies to handle significant growth.

I eventually moved to California to work at Google, where I was in online sales and operations, while continuing to explore side projects.

After quitting my job at Amazon, I moved to San Francisco where I found a co-founder and began working on various startup ideas without being picky about the market.

I initially pursued a career in tech, working at Amazon and Groupon, but I found that chasing what I thought I knew gave me a sense of competence without purpose, leading me to realize the importance of following my passions.

I dropped out of my PhD program in machine learning to join a startup, which was a high-risk decision that ultimately paid off.

Before my startups, I built technology inside larger companies, including developing asynchronous input/output software that outperformed major database companies.

After graduating, I took a job at a consulting firm in Washington, D.C., while working on small internet projects with friends on the side.

There's a growing trend of scientists moving into startups, as entrepreneurship has become a viable career path, supported by infrastructure like Y Combinator and AWS.

I realized that Amazon is not just a retailer; it's a massive technology operation, operating at a scale I had never seen before.