Context Engineering for RAG Question Parsing: From a Raw Question to Typed Fields That Steer Retrieval and Generation

Short summary

This article explores context engineering for RAG question parsing, transforming a single messy user query into four typed fields that each guide a different downstream retrieval or generation call. The approach is part of an Enterprise Document Intelligence series focused on improving RAG pipeline accuracy. It targets practitioners building production-grade retrieval-augmented generation systems.

• •Decomposes a raw user question into four typed fields for downstream RAG calls
• •Each typed field steers a distinct retrieval or generation step
• •Part of an Enterprise Document Intelligence series aimed at production RAG systems

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