For almost two years now, chatting with my AI assistants has become part of my daily routine. It’s a back-and-forth dance: I ask a question, get an answer, refine, dig deeper, redirect, and repeat. They’re always patient and eager to help. Over time, I’ve come to really enjoy this dynamic. It feels like teamwork. Even though I’m technically talking to language models, there’s a sense of collaboration that makes the process surprisingly engaging.
Retrieval-Augmented Generation (RAG) is quickly becoming the go-to technique for making Large Language Models (LLMs) more reliable and less prone to "hallucinations". By integrating a retrieval component that pulls in specific, trusted data, RAG systems can deliver accurate, source-backed answers for everything from customer support to fraud detection.
You know those website builders made for small business owners? Pick a theme. Drop in blocks. Accordion. Image next to text. Call to action. Maybe a testimonial slider. Everything configurable without touching code. Sounds good in theory.