(define (think x)

Most people think linearly. Problem → solution. Step 1, step 2, step 3.

But the most elegant solutions come from recursive thinking—breaking problems down until they become trivial, then building back up.

The Pattern

(if (atomic? x)
    x
    (map think (simplify (decompose x))))

If the problem is simple enough → solve it directly If not → break it down, simplify each piece, solve recursively

Real Examples

Code Architecture

Linear thinking: “How do I build this feature?” Recursive thinking: “What’s the smallest unit that composes into this feature?”

Result: Components that work together vs. monolithic spaghetti.

Learning

Linear thinking: “I need to learn React” Recursive thinking: “What are the atomic concepts that compose into React mastery?”

Result: (components → state → effects → patterns) instead of tutorial hell.

Business Problems

Linear thinking: “How do I get more users?” Recursive thinking: “What atomic value creates compound growth?”

Result: Focus on the function that generates users, not just user acquisition.

Why This Works

1. Forces clarity - you can’t recurse on unclear problems
2. Finds reusable patterns - atomic solutions compose into bigger solutions
3. Prevents over-complexity - if it doesn’t decompose cleanly, it’s probably wrong

The Practice

Next time you hit a complex problem:

1. Decompose - what are the real sub-problems?
2. Simplify - what’s the essence of each piece?
3. Recurse - apply the same process to each piece
4. Compose - build the solution from atomic parts

Complexity is just poorly decomposed simplicity.

Input → (think x) → Output

← All thoughts • Next recursion →