Surprising Additions to My 2024 Reading List
The best insights often come from unexpected places. Like that moment years ago when a colleague mentioned dbt (then still Fishtown Analytics), and I had to quietly Google it. That small moment of "I don't know this" turned into an important lesson: expertise isn't about knowing everything - it's about maintaining the curiosity to keep learning - oh yeah, and it led me to start this newsletter!
Think of it like trading - the most dangerous moment isn't when you're uncertain about a position, it's when you're absolutely sure you're right. That's usually when the market teaches you humility.
This newsletter has always been my way of thinking out loud, documenting discoveries across data, AI, and business decision-making. Not because I have all the answers, but because writing helps me structure my thoughts and hopefully sparks interesting discussions.
While I'll save the full 2024 recap for another edition, today I want to share some unexpected additions to my reading list that challenged my thinking this year. Like a poker player studying game theory to evolve their strategy, these sources pushed me to think differently about familiar problems.
“Only the educated are free.” - Epictus (stolen from the DeepLearning.ai newsletter)
The Unexpected Teachers
Alexandr Wang's Clear-Eyed Analysis Scale AI's founder writes about scaling companies the way a good engineer approaches problems - with clarity, directness, and zero fluff. His piece "How to not suck when you get big" is particularly relevant for anyone building data-heavy products. It's like finding that rare trader who actually shares their real strategy, not just the highlight reel.
Lex Fridman's Deep Dives Sometimes the best insights come from your commute. Following Elon Musk's advice (and my own empirical testing), I've found 2x speed works for understanding, 1.5x for reflection. Key episodes I keep revisiting:
Dario Amodei on AI alignment (what I listen to on my commute)
Marc Andreessen on building
Yuval Harari on human nature. Each one of those is like a masterclass in thinking from first principles.
NfX's Hidden Wisdom Think of NfX as that veteran poker player who never played your specific game but understands the underlying patterns better than anyone. They don't focus on data companies, but their insights about network effects and scaling are pure gold for anyone building data products. Morgan Beller's writing especially cuts through the noise with practical wisdom.
The Mind-Expanders
Chris Dixon's "Read Write Own" - Still criminally underrated
Every.to and oneusefulthing.org - Fresh perspectives on familiar problems
The Missing Pieces
Looking at my own writing in 2024, I notice two areas I've written about extensively but haven't found enough good reading material on:
Making BI Actually Useful
Practical Data Strategy
(And no, I'm not writing that book yet - too busy building cool AI stuff at MAIA!)
Like a good trading strategy, the best reading list combines different perspectives that challenge your assumptions. The key isn't to read everything, but to find those unexpected sources that make you think differently about your field.
What unexpected sources have shaped your thinking this year? I'm always looking for new perspectives to add to the mix.