GenAI & LLMs · 1 min read · Updated 2026-10-05
Retrieval-augmented generation (RAG)
How it works
First, your documents are stored in a way that makes them easy to search by meaning. When you ask a question, the system finds the best matching pieces and gives them to the AI along with your question. The AI then answers using them.
Why it helps
The AI can use new or private information it was never trained on, like your company's rules. It makes fewer mistakes, and it can point to where the answer came from.
The catch
If the search brings back the wrong pages, the answer can still be wrong. Good search matters as much as a good AI.
Key takeaways
- Look it up first, then answer.
- Lets AI use fresh or private information.
- Works only as well as the search.
Quick questions
What is an embedding?
A list of numbers that stands for the meaning of some text, so similar meanings end up close together.
RAG or fine-tuning?
Use RAG when facts change. Use fine-tuning to change how the AI behaves.
Does RAG stop mistakes?
It reduces them but does not remove them.