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Maintainer: data will not scale; the decision engine is an AI classifier, not ML, with local memory, DSPy style. In-house on the metered client; retrieval by signal profile re-ranked by code embeddings; compiled (bootstrap few-shot, instruction search) per training fold; retrieval never crosses the evaluation boundary; confidence calibrated on held-out repositories. Design and tasks 6+ to revise. Co-Authored-By: Claude Opus 5.5 <[email protected]> Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo