When choosing a career, we often focus on the outcome. Take being a doctor, for example. The outcome of being a doctor is incredibly rewarding: curing patients and helping others, good income, high social status.

However the process of being a doctor involves years of education and internships, night shifts and hospital environment, and constant exposure to sickness. For many, the process is far from enjoyable, and they end up regretting their decision because they focused solely on the outcome.

I made a similar mistake with machine learning. I studied it in grad school because the applications of this field were impressive: translation, speech recognition, recommender systems, algorithmic trading etc.

I was lured by the outcomes of being a machine learning engineer, but the day-to-day work involved statistics and math, feature engineering and building data pipelines, none of which I enjoyed. I realized I enjoyed building products and writing code, not feeding datasets into algorithms.

Even with hobbies, enjoying the process is essential. I picked up pencil drawing for a year and loved things I created: hand drawn portraits. But I noticed that I enjoyed the outcome more than the process.

I’d do 1:1 drawings, and the finished drawings would motivate me. But the process of creating it was meticulous, splitting the photo into a grid and perfecting each cell. It was not very creative, more mechanical and closer to engineering. Not what I was looking for.

I now make pencil drawings for my friends on special days like birthdays and see it as a tool to foster deeper connections with people I love. If I had enjoyed the process, I would have considered it as a potential occupation.

As the saying goes: focus on the process, not the outcome. Enjoying the process is essential.