As software engineers, we use clustering algorithms all the time. Whether it's grouping similar users, categorizing content, or detecting patterns in data, clustering seems deceptively simple: just group similar things together, right? You might have used k-means, DBSCAN, or agglomerative clustering, thinking you just need to pick the right algorithm for your use case.But here's what most tutorials won't tell you: every clustering algorithm you choose is fundamentally flawed. Not because of poor...