Dropping Out



For a couple of months, I've been working on a plan. When I first came to Carnegie Mellon, my goal was to study Machine Learning in some capacity. In my second year, I locked in this plan, and registered for the new Statistics and Machine Learning dual-degree. I took as many classes in game theory, programming, and AI as I could, and thought I was on my optimal path.

Almost two years later, I feel like I'm wasting most of my time. I learn things in my classes, but not more efficiently than I could by locking myself in a room with food, water, a bucket, and a book. That's why I decided this spring that I would either a) hack my degree to a state where it's significantly less grunt work, or b) drop out. In mid march, I locked myself in a room and decided I was going to try for option [a] first. I took a day off from work and wrote a 30 page proposal on why I deserved my degree for working on Pairi.

The next morning I emailed the proposal to the dean's office. It was a shot in the dark, but two days later I received an email from the deans office asking me to come in for a meeting. Somehow, the application was compelling enough to convince some people that the plan made sense. They didn't ask for revisions, and as such we immediately began the process of pushing the application through the various levels of approval.

Ultimately, however, I still decided to take a leave from Carnegie Mellon during the Spring 2019 semester. Due to a combination of factors, I am confident that this is the correct path. If Pairi launches this summer and is able to grow at 3%+ per week, we're confident that there won't be a reason for me to return. If we can't achieve this with Pairi, we'll keep pivoting until we find traction. Regardless of what vertical we're in, we're confident that solving problems is better than working at Big Co. So we'll keep doing that.