Tutorials · Chapter C (3/4) · ~8 min
Inside RAG — the pipeline
Play → read → next
RAG is a pipeline: embed the question → find chunks → put them in the prompt → generate.
Playground
Inside the RAG pipeline
Step through retrieve → augment → generate. Bad backpack = bad answer.
School rulesPhones stay in bags during class.
Cookie recipeBake cookies at 180°C for 12 minutes.
Store hoursWe open 9am–8pm every day.
Recap
What you just did
You walked the pipeline stages and saw how a broken step poisons the final answer — even if the LLM is strong.
Teach
How it works
A typical path:
- Embed the question
- Search your chunk store for nearest neighbors
- Pack the best chunks into the prompt (watch the suitcase!)
- Generate with instructions like “use only the notes”
Quality levers: better chunking, better search, clearer citations, and refusing to answer when nothing relevant was found.
Use it
When you'd use this
- Debugging “why did the bot invent this?” (check retrieval first)
- Designing a doc bot for a small team
- Choosing what to store vs what to put in the system prompt
Watch out
Watch out
Fancy models won’t save garbage retrieval. Fix the backpack before you blame the writer.
Try next
Try this next
Name the stage you’d inspect first if answers cite the wrong product policy.