I built a context orchestration layer that sits between AI coding agents and codebases — it classifies intent, plans multi-source retrieval, ranks context by five factors including graph centrality and semantic similarity, compresses to token budgets, detects when two agents touch the same file simultaneously, and maintains persistent memory across sessions so your agent remembers what it explored yesterday. 65% token reduction measured, not claimed. Open source. Built solo.