2019 year in review & looking ahead in 2020

Last year I wrote up a few of my goals for learning, and I wanted to repeat the exercise for this year. Planning for last year, even in rough terms, helped me sketch out a path and think about what I wanted to explore. I ended up writing and publishing 4 articles over the course of the year, much better than 2018. Also, talking about what I wanted to learn led to some encouraging words from friends and mentors, and prompted discussions where I shared what I had been learning with people who were interested.

What went well

I did a few things right when it came to my learning goals in 2019:

  • Morning schedule: I became a morning person after a few weeks of trying to be productive after work wasn’t working out as well as I would have hoped. Before making the change, I would sometimes get home drained of the energy I was expecting to spend learning new things. I eventually settled into waking up early, working out, learning for a few hours, then starting my work day as everyone else was. The new schedule also allowed me to work as late as needed without having to feel stressed about fitting in the time I was yearning for.
  • Following my interests/passions: I really dove into subjects that I found myself excited about, even if they were off the rough path that I was expecting to follow. For example, I didn’t plan on bug bounty hunting at all, even though I spent a much of December doing it.

What could have gone better

  • Sharing with more frequency: I followed my interests in a relatively unstructured way (the proverbial “going down the rabbithole”), but I didn’t write much as I was going along. I think I didn’t end up writing frequently because of two factors: I wasn’t actively thinking about topics to write about, and some of the things I was learning didn’t seem like they would be interesting if shared piecemeal. Actively thinking about writing, as well as keeping the “ship early, ship often” mindset top-of-mind, will not only result in me writing more, but also will help me interest more people in what I’m writing about.
  • More building: I feel that I overweighted absorbing new information over the last year, and underweighted building things with that information. With some of the things that I want to explore this year, I think I’ll have a chance to equalize how I spend my time between building and consuming.
  • Better goal setting: I didn’t write as much as much as I wanted to (although still more than the year before), and I didn’t start a few of the things I wanted to try out (for example, CryptoPals and Microcorruption). Learning new things shouldn’t be a job, but setting better goals would be helpful for prioritizing and focusing my learning.

What I want to learn more about in 2020

  • Machine Learning / Deep Learning: ML is top of mind for me again this year, although I didn’t spend as much time on it in 2019. I’ve decided to explore in a few directions, and I will write more about that soon. I’d also like to compete in at least one machine-learning-centric competion this year. Ideally this would be with dataset I’m excited about, like one from satellites. I’m also excited to read ML research and attempt to write about it, similar to what The Morning Paper does with Distributed Systems research.
  • Math: I’ve been wanting to deepen my math knowledge for a while and have a few ideas about how to do so. I’m motivated to expand my expertise in Math because it seems fun (and useful while I dig into ML). I’d like to flex a few math muscles (calculus, linear algebra, and statistics) I haven’t flexed in a bit, read a Programmer’s Introduction to Math, and try out Computational Linear Algebra. Beyond that, we’ll see where the journey takes me. Thankfully, there are a few good resources from Hacker News and Steve Yegge (ex-Google engineer) on good places to start with respect to self-learning math.
  • Distributed Systems - I’ve been reading The Morning Paper for a while and quite like the format that the author follows for summarizing research. Reading about how large-scale systems are designed is fascinating, and Adrian provided good tips for finding cutting edge research in this field (among others). Reading papers and talking about them would also give me a great opportunity to write.
  • Mandarin: I’ve been learning Mandarin! It’s fun and challenging. I’d like to practice Mandarin 30 minutes every day for the rest of 2020.

The first three areas I’m interested in are hard to set goals for, although with the motivation of shipping early and often, I’d like to write at least one new post a month about whatever topic I’m currently in the weeds with. This goal strikes the right balance between being a forcing function while remaining flexible enough to let me explore whatever rabbithole I’m currently in.

As for learning Mandarin, thankfully the apps I’m using (Duolingo and LingoDeer) track progress fairly well, although depending on how much time I have, I might end up taking an in-person class as well…we’ll see.

Until next time!

Subscribe to my writing on distributed systems, machine learning, and computer security. Published a few times a month.