We recently ran our first controlled preliminary benchmark to measure how Devramp improves agent accuracy. Using Claude Code (Sonnet-4) on a 100K-line Go codebase, we tested eight representative pull requests (10–40 files each). For each PR, we generated structured summaries: a 300-word explanation of functional and technical changes (with no file or symbol references), distilled down to a 30-word prompt. With Devramp, the agent's outputs matched human reference diffs far more closely. On average, accuracy improved by 55%, and variability dropped by 18 percentage points — making results both more reliable and more consistent.