Why does this matter as an engineer? Because the difference between O(n) and O(n²) means your app runs in 1 second or 100 minutes when the data scales up. Here's the cheat sheet: - O(1) = Constant time → fastest possible - O(log n) = Logarithmic → great for searching - O(n) = Linear → grows with data - O(n²) = Quadratic → AVOID at scale - O(2^n) = Exponential → almost always wrong If you're writing nested loops in your code right now, ask yourself: Is there a faster way? That question separates junior devs from senior engineers.