Vector Search & RAG: The Plain English Guide to Modern AI Search
Why You’re Probably Here You’ve probably heard terms like vector search , dot product, cosine similarity , or RAG floating around in AI conversations. Maybe you've seen them in documentation or presentations and thought, “I kind of get it, but not really.” This short guide is here to help -- using simple, practical explanations with everyday examples. No math degree required. If you’re building with AI, curious about modern search, or just want to finally understand what those terms mean, you’re in the right place. By the end of this doc, you’ll know what vectors are, how we compare them, and how those comparisons help AI give better answers using your own data. What Is a Vector (In Plain English)? A vector is just a list of numbers that represents the meaning of some text -- like a sentence, paragraph, or document. For example: “I love dogs” → [0.3, -0.1, 0.9, ..., 0.8] You don’t need to know what the numbers mean -- just that similar sentences produce similar vectors . So: “I ...