Big-O notation
A way of describing how an algorithm scales with input size: O(1), O(n), O(n log n), O(n²).
O(1): constant time (hash lookup). O(n): linear (a loop). O(n²): quadratic (nested loops — start hurting around n=10,000). Classic interview question; important to understand when data grows from 100 to millions.