The first time I implemented Vamana from the DiskANN paper, my approximate nearest neighbor index was slower than brute force. On tiny test fixtures, brute force took 0.27 ms per query. My Vamana implementation took 22.98 ms. That sounds absurd. ANN exists to skip work. The problem was not the algorithm. It was how I mapped the paper's abstractions to actual data structures. The DiskANN pseudocode
The Problem Most engineers deploy to Kubernetes by clicking buttons in a UI. I built Archnet — a fully automated Internal Developer Platform What is an Internal Developer Platform? An IDP is the infrastructure layer that sits between your code How code gets deployed How secrets are managed How the system monitors itself How failures get detected and fixed Most companies pay Humanitec or Backsta
We had ArgoCD running perfectly. Every deployment was reconciled from Git. Drift detection worked. Rollbacks were one-click. Our GitOps setup was clean. Developers still couldn't provision a staging environment without pinging the platform team. That gap — between "GitOps in place" and "developers can actually self-serve" — is where most platform engineering teams get stuck. GitOps solves a real p