“Falling Behind” & The Benefits of Slow, Intentional Learning in AI, it’s easy to feel like you’re falling behind with new “discoveries” and content published every day unfortunately I think today this manifests in short-term optimizations or “shallow learning” at the expense of life/learning that compound over time. this includes behaviors like: - skimming every cool article on X without engaging with a subset of topics deeply afterwards - foregoing all vacations with friends/family because you have to always be “locked-in” - giving up reading (or listening) to books (I’m bad with this one, but trying to be better). good books are some of the best intentional and timeless artifacts of knowledge. it’s also more long term and intentional in how we approach information - consuming everything but producing little. it feels good to read and feel like you’re in the know, but true learning and discovery happens when you break things yourself and tinker at the frontier in moderation all this stuff is fine, it’s actually great to obsessively sprint at something for a week or get a launch over the line but effective learning in a rapidly evolving field like ai is a healthy mix of short term optimizations mixed with deep, intentional long-term focus on hard problems that you actually care about my brain at least just needs some time to mull over ideas for a while to really let competing notions play around things like reading, going on walks, playing sports, hanging out with friends, help our minds find connections between concepts we’ve been intentionally engaging with for a while there’s many PhD/research stories breakthroughs coming from walks or sleep. the two sides of this are deeply intentional, prolonged focus on a topic mixed with stepping away from the topic and living life you’re not falling behind if you’re working towards something you care about even if grind culture says you are lock-in for a bit, step away, read a book, chill out, and run it back again. pretty hard to lose if you keep at this