Moderate RAG Question 203 of 223

What is Retrieval Augmented Generation?

GenAI / LLM · Speak this in 60–90 seconds · Faridabad & Delhi NCR

Text inTokens

TransformerAttention

Text outNext token

RAG searches your documents first, then feeds relevant chunks into the LLM prompt.

LLMs use tokens (not full words) because it helps them:

RAG questions separate people

who only read docs from people who shipped.

Keep it short, concrete,

and tied to GenAI / LLM work.

Stable token IDs

Each piece maps to a number the network can learn.

Fits the model

Fixed pieces are what transformers expect as input.

Before the model can read a sentence, it goes through these steps:

1
RAG searches your documents
first, then feeds relevant chunks into the LLM prompt.
2
Answers stay grounded in
company data and cite sources.
3
It reduces hallucinations for
private knowledge.
4
Context mix
Attention looks at nearby tokens together.
5
Next token
The model scores what should come next.
6
Decode
IDs turn back into readable text.

Here's a short line you can speak, broken into clear beats:

Say this line

“Answers stay grounded in company data and cite sources.”

Break into beats

Answersstaygroundedincompanydata

Speaking order

2987408337471632900

Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.

RAG searches your documents first, then feeds relevant chunks into the LLM prompt. Answers stay grounded in company data and cite sources.