AI RESEARCH
A Case for Agentic Tuning: From Documentation to Action in PostgreSQL
arXiv CS.AI
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ArXi:2605.19988v1 Announce Type: cross Documentation has long guided computer system tuning by distilling expert knowledge into per-parameter recommendations. Yet such guides capture only what experts conclude, discarding how they reason. This fundamental gap manifests in three concrete deficiencies: documentation grows stale as software evolves, fails under heterogeneous workloads, and ignores inter-parameter dependencies. We propose shifting from static documentation to dynamic action for system tuning. We.