Make Your AI Agents 10x Smarter with Hybrid Retrieval (n8n)

簡介：

In this deep‑dive, the speaker explains that vector search, while powerful for semantic queries, fails in many production scenarios. He outlines nine categories of questions—simple, conditional, aggregation, global, multi‑hop, multi‑modal, post‑processing, and false‑premise—where vector search breaks down, and demonstrates alternative retrieval strategies such as exact‑match for error codes, structured data for tabular queries, aggregation techniques, GraphRAG for knowledge patterns, multi‑hop reasoning with knowledge graphs, multimodal RAG for image retrieval, and evaluation with DeepEval. The talk also covers how to handle hallucination and false‑premise questions, and provides a roadmap for building robust RAG systems. The presentation is organized around timecodes: 00:00 – The Vector Search Myth; 05:20 – Summary Questions; 12:27 – Simple Questions; 15:25 – Simple Questions with Conditions; 19:55 – Aggregation Questions; 20:41 – Global Questions; 22:21 – Multi‑Hop Questions; 23:59 – Multi‑Modal Questions; 25:12 – Post‑Processing Questions; 26:18 – False Premise Questions.