Ayende argues RavenDB optimization beats AI code

The author argues that long-lived software accumulates essential bug fixes, edge-case handlings, and deep optimizations derived from real-world experience that AI-generated code cannot easily replicate. Examining the optimization of RavenDB for I/O-constrained environments after a cold boot, the post highlights how intricate details like disk behavior and prefetching strategies provide enduring value that simple benchmarks or automated generation miss. Open article →