Ask HN: What was your “why didn't I start doing this sooner” moment?

Daily fasting and eating meat, fish and veggies makes my mind much sharper. I can see the 3 day fast improving cognitive performance but I can barely do the 20 hour fast as it is.

reading The Three-Body Problem by Cixin Liu.

The book was published in 2008 and I just finished reading the book a couple of months ago. It was a wild journey into the land of science fiction. Highly recommend if you are a fan of Asimov or Phillip K Dick.

Thinking about hard problems in terms of lambda calculus. I took a day to read about all that stuff and at some point so many things fell into place. I learned CS theory in school, learned ML, but it's not the same as being confronted by a seemingly monstrous software project and then realizing ... omg, everything is relational and I can just write an interpreter. No longer asking "how do I write this in ruby/java/js ..." but how do all of these things relate to each other and if which language would be best for encoding my invariants. All kinds of ML and AI fields go from "data science, math stuff ... disregard" to a fascinating universe of answers to questions that you already have in your head for how to solve your real world software problems. The usefulness of macros became obvious and custom monads are rewarding achievements. Closures, instead of being occasional conveniences, became a swiss army knife for eliminating explicit data structures.

Not for all projects of course, but when building something enterprisey, simulated, or creative where users can model their own domain I believe that at least being familiar with the theory is not optional. I'm also somewhat convinced now that most "10x programmers" are maybe ~2x programmers who have simply encoded their expertise into a private DSL using JetBrains MPS or something. Allowing themselves to spend more time snowballing their skills and knowledgebase, and less time doing repetitive tasks and managing incidental complexity.

Oh also, I started using linear constraint solvers for automatically solving small to medium sized problems. You'll usually see them used for UI layout constraints, but that's just the beginning! For example, say you're building a small scheduling system, or a lightweight recommendation system that lies somewhere in between an if-statement and a full blown classifier, or you're writing some arbitrary last-minute business rule for a client where several things depend on each other with varying levels of weights/importance. If you know some things are linear, and the problem is unlikely outgrow the solver, then save yourself hours or work and just solve it at runtime!

Sure, but my point is that this works beyond the expectations of "common sense".

The XYZ fact may turn out to actually not generalize. With mental phenomena, often how you got somewhere matters more than the thing itself. For a nice negative example, think about taste - many of us have strong repulsion towards some foods caused by random events in the past. Like, for many years parsley made me nauseous, and it started when as a kid I ate a broth and then threw up. It's a common thing that when you're sick your brain can create associations between how you feel and what you smell or eat. So you end up hating some food not because it's objectively bad, not because everyone else hates it too, but because of a random event in your life that happened to get associated with it.

I treat n=1 experiments as a way to probe such random associations. If you find out that something works for you, it doesn't matter that it isn't scientifically proven. It doesn't matter the effect doesn't generalize. It doesn't matter it works only through association and that this association was created due to you doing the experiment. If it works for you, it works for you.

But to be clear - "it works for me" is the only thing you can say in such case. N=1 experiments are ok, but trying to generalize from them isn't. Saying "it must work because it worked for me" based on such experiment is of course quackery.

You should write some blog posts or something about this. As someone just finishing up their undergrad I'd love to hear about these applications and detailed examples.