Things I Think You Should Read and Watch

Tue, 21 Jul 2026 00:00:00 +0000

This is a curated, non-exhaustive list of tech-adjacent content I’ve really enjoyed and shared with friends and colleagues.

Mostly general thoughts on life as a data scientist, learning/teaching programming, technical leadership, career advice, and other tech-adjacent topics, and not specific to R or sports analytics (will probably tackle that another time).

Inspired by Derek Sivers’s book notes and Vicki Boykis’s favourite essays, and organized loosely by topic (click to jump to section):

life as a programmer & data scientist
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Michael Lynch: How to Do Code Reviews Like A Human and part two, blog posts (18 and 15 min reads, respectively)
- Code reviews are daily interactions that shape both the code itself and, maybe even more importantly, the relationships between programmers - these posts really help with how to approach these in a constructive and positive way.
Hank Green: The Secret to My Productivity, YouTube video (4 min)
- Invaluable advice on when to stop working on creative projects: stop working on it when you have reached 80% of “the best you can do”, release it to the world, and then go do your next project. Applies in hobbies and tbh to professional projects as well.
Randy Au: Succeeding as a Data Scientist in Small Companies / Startups, blog post (8 min read)
- How to succeed in a small company where you are the first “data” person there: helping the company succeed TODAY and setting up the company to be data driven TOMORROW. Also has a very nice “hierarchy of needs” graphic that explains what it means to set up a company to be data driven. Immediately relevant for people in small companies and also for understanding the core needs for a data team (and seeing how that scales as you add more people.)
Alberto Savoia: The Way of Testivus, PDF blog post
- Advice on developer and unit testing, packaged up as pseudo-Confucian tenets worth living by.
Dan McKinley: Boring Technology, talk/slides and original blogpost
- Core idea: you get “innovation tokens” to spend as a (developer, team) and you don’t have that many even across a team. In order to keep those innovation tokens spent on the team’s core mission (e.g. solving soccer), you should spend less time innovating on the core technologies (fancy database stuff, programming paradigms etc), because fixing bleeding edge database stuff takes up “innovation tokens” that you want to spend doing other things.
David Robinson: Unreasonable Effectiveness Of Public Work, YouTube talk recording (40 min)
- Anything you put out into the world is going to be far better and far more useful than anything that sits in your drafts folder waiting for some arbitrary threshold of “good” before it gets published. Go out there and do things!

learning and teaching programming
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Greg Wilson: what everyone in tech should know about teaching and learning, YouTube video (41 min)
- Massively useful! Especially the ideas right at the beginning about mental models and the differences between how beginners, competent users, and experts learn. The whole video is incredible, but I recommend at least the first 8:23 to cover these ideas.
Andy Harris: how to begin thinking like a programmer, YouTube video (61 min)
- A riveting talk (given at a Python conference, which should surprise you if you know me). which covers how to think like a programmer. Especially profound: comments are not for explaining code to other programmers - instead, code is there to explain comments to the computer!

technical leadership
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Tanya Reilly: Being Glue, annotated talk slides and YouTube video (28 min)
- A brutally honest talk about the non-promotable “glue” work that programmers can get silently stuck with, and that hurts your technical development and ultimately your career development if you’re not prepared. Can disproportionately affect teams, especially women and/or introverted/non-assertive personalities.
Julia Evans: Help, I Have A Manager!, zine (~$12)
- Having a good relationship with your manager is probably the most important factor in your happiness at work. This zine is full of great advice on how to make that relationship better - how to handle 1:1s, asking for feedback, figuring out what they’re good at, building a support system for areas they aren’t as good, and more.
Vasily Zubarev: How to hire sane engineers 2.0 (~15 min read)
- A pragmatic Russian’s take on hiring engineers in a “sane” and effective way. Would love to implement this one day to help with bypassing some of the technical interview steps that are so common now.

career advice
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Derek Sivers: How To Do What You Love And Make Good Money, blog post with audio recording (4 min read/listen)
- This is the advice I share when folks ask me about getting their dream job and making a career from sports analytics or other hobbies - you don’t need to force sports analytics to be both your livelihood and your art! The dream job that does both may or may not come along, but you can be happy in both career and art without it. Part of a larger book, Hell Yeah or No, which is also very worth reading (~$15).
Austin Kleon: Show Your Work, short book (~$15)
- The book I share when people ask me how to build their public portfolio and personal networks: share something small every day without being human spam, teach what you know, and tell good stories. A lot of insights packed into a small and easy to read format. Also great are the other books in the Steal trilogy, including Steal Like An Artist on how to be creative and Keep Going on how to sustain the creative effort
Jacqueline Nolis & Emily Robinson: Build A Career In Data Science, book (~$24) and podcast series (~20 episodes each about 60min)
- A great resource for finding a job in data science. Really like the definitions of data science as an industry - essentially the intersection of programming, statistics, and domain knowledge. Book was available online for free at one point but now seems to be only paid - very worth it, but listening to each of the podcast episodes is a pretty good equivalent.
Haseeb Qureshi: Rules for Negotiating a Job Offer and part two, blog posts (24 and 34 minute reads)
- More people should negotiate job offers and simply don’t. This is good, not-too-kitschy advice on how to approach negotiating.

specific technologies
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Vasily Zubarev: Machine Learning For Everyone, blog post (~40 min read)
- “Machine Learning is like sex in high school. Everyone is talking about it, a few know what to do, and only your teacher is doing it.” An impressively nontechnical and yet surprisingly comprehensive overview of machine learning that I found useful early on in my data science career as someone with neither a CS nor a stats background.
Julia Evans: Hell Yes CSS, zine (~$12) and comics
- I’ve always found CSS to be incredibly frustrating, but reading this zine was super helpful. Still refer back to the CSS Selectors comic to this day whenever I need to format something.
OhShitGit.com (reference page)
- For the times I manage to fuck up using git, this page consistently saves me every single time.
data.table vs base vs dplyr (reference page)
- An awesome syntax lookup page to go between dplyr, base, and data.table in R - a worthy successor to the original post by atrebas

changelog
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2026-07-21: added data.table vs base vs dplyr reference page
2025-09-04: added ohshitgit.com
2025-03-17: added David Robinson’s Unreasonable Effectiveness Of Public Work talk
2024-11-29: first version

Like-Hearted

Thu, 04 Mar 2021 00:00:00 +0000

I immensely recommend Austin Kleon and the Steal trilogy to everyone, especially those looking to “make it” as a creator, programmer, or data analyst.

TLDR: Curating your feed, finding your friend groups, and getting into online arguments can be good
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Each year, I embark on a journey to re-read Austin Kleon’s Steal trilogy, and each time I read it, something new grabs my attention. I was struck today by this image from a chapter in Keep Going called “Like-Minded vs Like-Hearted”:

Modern day Bart Simpson would totally be punished with this

Like many people, I’m not immune to getting drawn into online arguments - just ask the folks on the Dynasty Movement Discord server about my many different soapboxes - so reading this immediately after having been drawn into a particularly vivid discussion hit a little closer to home.

I’ve heard many a time that you should never get drawn into an argument online: it’s impossible to win, petty trolls cannot be fed, and that it’ll have a negative impact on your work, life, and mental health. It’s easy to point to examples of this - a notable Twitter presence making personal attacks, someone repeatedly moving the goalposts on a debate, or someone standing up for an controversial idea and getting bombarded with bits of conventional wisdom - and think that you’d better served by avoiding confrontations altogether.

And yet,

“To think independently of other human beings is impossible. Thinking is necessarily, thoroughly, and wonderfully social. Everything you think is a response to what someone else has thought and said.” - Alan Jacobs, How To Think (c/o Keep Going)

I’ve spent a large amount of time trying to fill my Twitter feed with thoughts, ideas, and opinions from brilliant and insightful people, on topics that I want to get better at. I want my feed to be intelligent, open, and thought-provoking. I’m not as interested in helping others make it big, amass follower counts, become more influential - heck, I’m not looking to do that myself! My Twitter feed is precious to me, and I’m fastidious about stripping away the content that doesn’t fit those goals, or just plain old doesn’t make me happy.

This is both a blessing and a curse: it’s very easy to fall into a trap where you fill your feed (and friend groups) with like-minded people - the people who like the same programming language you do, the same dynasty fantasy strategies, the same analytical methods. Having too much in common makes it tricky to find your own space and niche within your friend group, and you become deeply set in your ways.

If you really want to explore ideas, you should consider hanging out with people who aren’t so much like-minded as like-hearted - those who are temperamentally disposed to openness and have habits of listening. The ones who think about what you’re saying rather than just reacting.

This is a really valuable idea - and one that I feel like I need to strive for, and keep striving for. I’ve backed into finding like-hearted people in my feed, inadvertently, because I’ve been following more and more open source sports data and R stats community members, and that community is inherent more likely to share, listen, and celebrate each other’s achievements.

I’ve also lucked into a community in the TDM Discord where I feel comfortable making those online arguments and challenging opinions, because so many folks there feel like-hearted to me - they listen, they challenge me to be articulate my opinions, and when we disagree we can still respect each other’s opinions. It’s rare that I feel like I’m left angry or drained after spending time there.

The takeaway from the chapter, for me, is that I should continue to strive to surround myself with like-hearted people - on my Twitter feed, in my Discord/Slack communities, and in real in-person friend groups. I’m lucky to have the communities I’m in, and I’m very glad to be able to get drawn into debates amongst my like-hearted friends.

Reading on TanHo.ca

Things I Think You Should Read and Watch

life as a programmer & data scientist #

learning and teaching programming #

technical leadership #

career advice #

specific technologies #

changelog #