Self-evolving retrieval lifts benchmark scores 25%

AI agents that adapt their retrieval configurations while running deliver a 25.7% performance lift on established benchmarks, overturning the assumption that retrieval stacks should be frozen. This new paradigm allows an LLM-driven "diagnosis" module to rewrite its search strategy as new queries arrive, treating the entire memory-access pipeline as a mutable policy.