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5 Aug

Mastery lies in the details.

“The ability to reduce everything to simple fundamental laws does not imply the ability to start from those laws and reconstruct the universe. Just because Y lies below X in the hierarchy does not imply that science X is "just applied Y."

At each stage entirely new laws, concepts, and generalizations are necessary, requiring inspiration and creativity to just as great a degree as in the previous one. Psychology is not applied biology, nor is biology applied chemistry.”

— Phil Anderson

Experts usually tend to amass a huge body of experience in their domain, observing things working (and not working) in a wide variety of real world contexts. That is how, over time, their observations tend to distill themselves into a general set of principles and mental models.

These are hard-earned abstractions that they then sometimes choose to publish in a book, in a text- or video-essay, in a Twitter thread, etc. — the length depending on how much context they feel is needed for the principle to be useful to the reader.

What novice readers then do is take these general principles that often assume the form of single sentences or aphorisms, and try to expand them and apply them in their daily life — without having the necessary detail needed to contextualise the said principle and adjust it to their own context.

The thing that we often don’t really grok is the fundamental complexity that is inherent at every step of observation and abstraction.

It’s easy to see a light bulb and explain its working as, “It’s just electricity flowing through a tungsten filament that resists the flow of current enough for its energy to be dissipated as light and heat.”

However, change the scale of observation you’re questioning at and you’ll realize that understanding the physics behind how a light bulb works is a totally different question than trying to make a real light bulb yourself.

It’s a different pandora’s box you will be opening. You will have to learn a tonne of process knowledge, how glass moulding works, how thick the filament should be, what should its material constitution should be, how do you design the base for the light bulb, how do you seal it with argon gas… there are simply too many details involved when it comes to making a light bulb.

And notice that you aren’t even inventing the light bulb, you’re simply following an existing playbook on how to make one!

Change the scale of questioning even further to “How do I make light bulbs at scale?” and this is a whole another set of details around manufacturing setups, engineering processes and best-practices, packaging, logistics…

Now don’t get me wrong: the point isn’t that abstractions or generalised principles are bad or useless.

Just consider what a smartphone application is. What is an app?

An app is an abstraction that simplifies the underlying working of the code — the ugly guts of the system — behind a simple interface any layperson can understand, navigate, and derive utility from.

Good abstractions can almost feel like magic. But the downside is that they also prevent you from truly understanding what's going on under the hood. Now, in most situations, that understanding isn’t needed and you can carry on without worrying too much about how the thing works. In this way, abstractions are extremely efficient and useful. You don't want to be deriving Pythagoras' theorem from the ground up, every time you use a right-angled triangle in your designs.

The point behind focusing on the details is only relevant when you’re trying to apply the abstraction in your own work. Once you understand the detail behind how the abstraction was derived, the underlying mechanisms, you can come back to the abstraction — but now with the knowledge and clarity of contexts where it applies and contexts where it doesn't apply.

And for this, you need to iterate and experiment.

You don’t understand the system well enough to predict its behaviour, so you try an idea, observe what happens, and keep iterating. Over time, your intuition grows, your internal library of case studies grows.

And to start iterating, you need to be able to move freely — to take a wild guess and go into things with an attitude of “Let’s see what happens if I do this.” Any ideas you start with, at the outset, are mere guesses. But the ideas you get as you observe how the system responds to these initial inputs are now much more likely to be fruitful.

Over time, you develop a sense of what tweaks lead to what changes and you start building a library of mental models to approach different problems within your domain. You get more efficient: you diagnose issues faster, you arrive at clarity around potential solutions and their trade-offs faster. And most importantly, you build a sense of what experiments to run next and identifying what is worth pursuing.

You start clueless — from the bottom rung of the ladder of abstraction — and you climb higher rungs of abstraction over time *while* being fully cognizant of the dirty details involved at every rung.

This is the ladder of mastery. And it doesn’t start with abstractions. It starts with the messy detail involved in execution.

It starts with keen observation, making a wild guess based on whatever existing intuition you have, and then observing what happens.

You distill principles as an outcome of wading through the dirty details, not the other way around. And the abstractions you create as you move up serve the purpose of bringing out high-level patterns. They help you defocus and tune out of the low-level clutter of individual trajectories. This “clutter” may not be important for the level of abstraction you’re thinking it, but understanding it is essential to making anything that works in the real world.

Without the detail, the abstractions and principles are almost meaningless. And the only good way of going about it is getting your hands dirty while studying other masters at work. The knowledge you build this way is your own. And I would say that there is no bigger luxury in the world than owning your knowledge.

I will end this essay with this beautiful quote by Craig Mod that hints at how you move up the ladder of mastery:

“Looking closely is valuable at every scale. From looking closely at a sentence, a photograph, a building, a government. It scales and it cascades — one cognizant detail begets another and then another. Suddenly you’ve traveled very far from that first little: Huh. I’d say that that “huh” is the foundational block of curiosity. To get good at the “huh” is to get good at both paying attention and nurturing compassion; if you don’t notice, you can’t give a shit. But the huh is only half the equation. You gotta go “huh, alright” — the “alright,” the follow-up, the openness to what comes next is where the cascade lives. It’s the sometimes-sardonic, sometimes-optimistic engine driving the next “huh” and so on and so forth.”

Are you looking closely enough?

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