THE WRITABLE RETRIEVAL BASIN: Retrieval Basin Topology, Directional Stability, and Attractor Dynamics in AI-Mediated Knowledge Retrieval (EA-RBT-01 v1.1)

spxi.dev — The Writable Retrieval Basin (EA-RBT-01 v1.1) Search is no longer a passive act of discovery. It is a weak act of inscription inside a writable retrieval basin. The retrieval basin is writable but not obedient. RBT formalizes how AI retrieval systems settle on competing framings and how repeated interaction changes which framing stabilizes. Paired case studies: heteronymic provenance theory (stabilization) vs holographic kernel (destabilization). Introduces operationalized Basin Depth Ratio (BDR), Framing Persistence Index (FPI), Drift Vector (DV), Basin Capture Velocity (BCV). Five-state basin machine. Basin hygiene rules. Platform-specific basin geometries. Central directive: deposit before you query. Integrates external research: SparkToro citation variability, Profound citation drift (59.3% for Google AI Overviews), iPullRank query fan-out, Qdrant relevance feedback, Tekin et al. directional attractors, Tacheny geometric dynamics, Goswami embedding drift. Hex: 06.SEI.RBT.01 · CC BY 4.0