---
title: RAG: one question, end to end — AI basics, lesson 7
description: RAG is four steps at question time: embed the question, find the nearest chunks, paste them into the prompt, answer with a citation. The prompt, cost and fixes.
url: https://instibrain.ai/guides/ai-basics/rag-one-question-end-to-end
updated: 2026-11-07
site: https://instibrain.ai/llms.txt
---

lesson 7 of 8 · ai basics

# RAG: one question, end to end.

RAG is four steps at question time: embed the question, find the nearest chunks, paste them into the prompt, let the model answer from them with a citation.

## new words

**Retrieval**
Finding the chunks: lesson 5 against the index of lesson 6.

**Augmented**
The prompt is enlarged with the chunks found.

**Generation**
The chat model writes the answer. It never saw the index, only the pasted chunks.

**Grounding, citation**
The answer points at the chunk it came from, so a reader can check.

**Hybrid search**
The vector score plus a keyword score, added together. It catches codes, names and numbers that vectors blur.

**Reranker**
A second, slower model that reads the question with each of the top 20 to 50 chunks and reorders them. The best 5 go into the prompt.

## the lesson

The prompt that goes to the model, with the chunks first and the question last:

```
System: Answer only from the passages below. Cite the passage number.
If the passages do not answer the question, say so.

[1] contracts/acme-2025.pdf, p. 4
"Either party may terminate this agreement with 60 days' written notice."
[2] contracts/acme-2025.pdf, p. 1
"This agreement runs for 24 months from 1 March 2025."
[3] handbook/suppliers.md
"A supplier bill is settled one month after it arrives."

Question: What notice does the Acme contract require?
```

The answer: "60 days, in writing [1]." The model added nothing; it read. Acme is an example name.

| Per question | Figure |
| Chunks pasted | 5 to 20 |
| Context added, at 500 tokens each | 2,500 to 10,000 tokens |
| Cost of that context on Sonnet 5.5, $2 per million | 0.5 to 2 cents |
| Time to embed, search and rerank, before the model starts | 0.3 to 1.5 s |

Where it fails, and the fix for each:

| Symptom | Cause | Fix |
| Right file, half a fact | Chunks too small, or cut mid-clause | Lesson 6: cut on structure, add overlap |
| A question in other words finds nothing | Keyword search alone | Embeddings, then hybrid search |
| A code or a name is missed | Vectors alone | Hybrid search |
| The right chunk exists, ranked 30th | The embedding is coarse | A reranker over the top 50 |
| The answer is from last year's version | The index was not rebuilt | Reingest on file change, nightly at least |
| The model answers from memory | A weak instruction | "Only from the passages", citations required |

Measure before you tune. Take 20 real questions and mark the chunk that answers each. Recall at 5 is the share of questions whose chunk is in the top 5. Under 80%, fix retrieval; the prompt is not the problem.

Where instibrain sits: a page holds a position your team reviewed, and your AI reads it whole, in its context, before it works. Nothing is cut or ranked. RAG is for the thousands of raw files nobody reviewed one by one.

One question through the four steps. Retrieval finds; the chat model only reads what was found.

## try it

Type a question. The prompt under it is rebuilt from the sentences of lesson 5 that score above zero, the top three at most.

Your question

```
System: Answer only from the passages below. Cite the passage number.
If the passages do not answer the question, say so.

[1] finance/payments.md  (cosine 0.58)
"Invoices are paid within 30 days of the date we receive them."
[2] finance/expenses.md  (cosine 0.29)
"Expense claims need a receipt and are paid with the next salary."

Question: When are invoices paid?
```

## you should see

- The retrieved sentences numbered and placed before your question, each with its source file.
- A question that shares no word with any sentence gets no passage, and the model must say it cannot answer. That is the whole of RAG; everything else tunes the four steps.

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