Here’s a practical, engineering-grade set of coding principles that actually keep a codebase healthy over years—not just during the honeymoon phase. Think of this as preventative maintenance, not moral philosophy 🛠️🧠.

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1. Smallness Is a Feature

Large things rot faster.
	•	Small files
	•	Small functions
	•	Small modules
	•	Small responsibilities

If a file feels “important,” it’s probably doing too much. Decomposition beats cleverness every time.

Size is friction. Friction accumulates.

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2. One Reason to Change

This is the only part of SOLID that really matters in practice.
	•	Every file should exist for one reason
	•	If a change request makes you touch unrelated logic, the boundary is wrong

Violations show up as:
	•	“While I’m here…” edits
	•	Fear-driven refactors
	•	Accidental breakage

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3. Make State Explicit (and Rare)

Hidden state is technical debt wearing camouflage.
	•	Prefer pure functions
	•	Push IO to the edges
	•	Name state transitions clearly
	•	Avoid “ambient” globals, singletons, magic context

If you can’t explain when state changes, it will betray you at scale 🧨.

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4. Clarity Beats Brevity

Concise code is nice. Readable code survives.
	•	Prefer obvious over clever
	•	Use boring names that describe intent
	•	Avoid dense expressions that require mental simulation

The best compliment for code:

“I didn’t have to think.”

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5. Structure > Comments

Comments decay. Structure persists.
	•	Encode intent in function names and types
	•	Let data shape explain behavior
	•	Use comments only for why, never what

If you need a paragraph to explain a function, split the function.

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6. Types Are a Design Tool

Even in dynamic languages.
	•	Types clarify contracts
	•	They force edge cases into daylight
	•	They prevent “just trust me” APIs

A good type definition is executable documentation 📐.

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7. Tests Define Reality

Untested code is hypothetical.
	•	Tests lock in behavior
	•	Refactors without tests are rewrites in disguise
	•	Focus on behavior, not implementation

Healthy ratio:
	•	Few unit tests per function
	•	Strong integration tests per feature

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8. Errors Are First-Class

Failure paths deserve the same respect as success paths.
	•	Handle errors explicitly
	•	Avoid silent fallbacks
	•	Fail fast, fail loud, fail usefully

Most production bugs live in “this can’t happen” branches.

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9. Consistency Is More Valuable Than Correctness

A consistent codebase is navigable—even if imperfect.
	•	Same patterns everywhere
	•	Same naming conventions
	•	Same folder logic

Inconsistency multiplies cognitive load faster than any algorithmic inefficiency.

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10. Refactor Continuously, Not Heroically

Big refactors are usually a smell.
	•	Refactor as you touch code
	•	Leave things slightly better than you found them
	•	Don’t let cleanup pile up into fear

Entropy is real. You either fight it daily or lose spectacularly 🌪️.

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11. Design for Deletion

The best code is easy to remove.
	•	Avoid tight coupling
	•	Prefer composition over inheritance
	•	Keep feature boundaries clean

If you can’t delete a feature safely, it owns you—not the other way around.

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12. Tooling Is Part of the Codebase

Linters, formatters, CI, and automation are not optional polish.
	•	Enforce rules mechanically
	•	Remove human judgment where possible
	•	Let tools be the bad cop

Humans are bad at consistency. Machines love it 🤖.

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The Meta-Principle

A good codebase optimizes for future humans, not present cleverness.

Every line you write is a tiny act of communication across time. Write like Future-You is tired, busy, and slightly annoyed—but still clever enough to appreciate clean design.

Entropy never sleeps. Engineers must 😄
