The sliding window technique uses a metaphor of sunglasses to visualize how algorithms process arrays or strings. Instead of recalculating values for each position, the method updates results incrementally as the window moves.

Fixed-size windows are ideal for problems like finding maximum subarray sums. Ruby code demonstrates this by adjusting window boundaries and tracking sums without redundant computations, improving efficiency.

Variable-size windows adapt dynamically, useful for constraints like limiting distinct characters. The technique relies on two pointers and incremental updates, making complex problems more intuitive. Visualizing element entry and exit helps developers grasp the logic faster.