Portable-skill agentic RAG case study for customer support (arXiv:2610.14428v1)
A new arXiv paper (arXiv:2610.14428v1) reports a deployment case study where a "portable skill"—a natural-language instruction, lightweight retrieval/formatting tools, and an LLM-generated navigation layer over a curated corpus—was used as an agentic RAG solution for customer-support resolution workflow generation. The authors say the approach is quick to implement (1–2 engineer days), portable across agentic harnesses (e.g., Claude Code), achieved 99.2% procedural equivalence and 83.3% evidence sufficiency versus human-approved ground truth, but is roughly an order of magnitude slower per case (~90 s vs ~8–9 s) and is scoped to latency-tolerant, human-reviewed workflows and well-curated corpora.