Tags: #programming

Returning to the simplest complicated problem: a deep look at Fibonacci and two ways of writing it in Rust and Python

This post explores two different approaches to the Fibonacci problem — the naive recursive method and the optimized memoized version — to show how a simple sequence reveals deep lessons about complexity, structure, recursion, and algorithmic thinking. The naive version demonstrates exponential growth and wasted computation, while the memoized version shows how adding memory transforms recursion into a powerful and efficient tool. Ultimately, Fibonacci becomes a metaphor for the essence of programming: making the right choices.