rag
7 results
Agentic RAG — Moving Beyond Simple Q&A
Simple RAG retrieves once and answers. Agentic RAG lets the model decide what to retrieve, when, and how many times — here's how it works and when to use it.
Build a Customer Support AI Agent That Doesn't Hallucinate
How to architect a grounded AI support agent using RAG, strict system prompt rules, and adversarial testing — so it never makes up answers about your product.
How RAG Works: The Plain-English Guide to Retrieval Augmented Generation
RAG is the most widely used technique in production AI. Here's a clear, jargon-free explanation of how it works, why it matters, and when to use it.
Prompt Compression: How to Reduce Context Size Without Losing Quality
Long contexts cost money and degrade performance. Prompt compression techniques let you fit more relevant content into fewer tokens — here's what works in practice.
Retrieval Augmented Generation (RAG): Ground Your AI in Real Data
RAG connects an LLM to an external knowledge base so it answers from facts rather than memory. Learn how RAG works, when to use it, and how to prompt effectively in RAG systems.