I love crossovers that make the world better. Danny Miranda is the most positive podcaster I know. David Perell is the one man who regained my faith in humanity through writing. On Danny's podcast, David was asked to talk more about this idea that knowledge workers should treat themselves as athletes and learn from sports.

How can we get better at learning? Look at the world of sports.

Sports has training, discipline, rituals, coaching, and they actually measure their results. Can you do the same at your job? Can you quantify the work you do and improve upon it? Be more efficient. Save time and optimize results or maximize profits? This level of rigor in regards to progress and development is second nature in sports.

I did not know how to write R code in 2018. But I knew what would work if I applied the same principles I used to transform from a slow shitty sprinter, to a faster shitty sprinter in college. I learned from coaches and athletes that were better than me, I worked on getting 1% better everyday, and I absorbed as much as I could in a short amount of time and applied it immediately.

Track is an individual sport. It's you vs. a stopwatch.

R code works the same way. Every improved efficiency saves hours or days of work and resources. If I want to be a better sprinter, it required an attention to detail and small changes led to getting faster over time. To be a better R programmer, I need to understand what my code was doing, how to make it better, and then make changes without breaking everything.

Apply what you learn right away: tighten the feedback loop.

Getting faster becomes a game of constant test-retest. When I set my blocks up this way, do I get a better push and start? If I use data.table does my code run faster? Both track and code have immediate feedback loops. If it works the clock tells you and you're happy. If it doesn't work, the clock tells you and it hurts. By shrinking the feedback loop as tight as possible, you can test tweaks over and over again for immediate best results.