RAG

AI & Programming

Retrieval-Augmented Generation

A pattern that grounds language-model responses in retrieved application data.

What it is

RAG retrieves relevant information before generation so responses can use specific source context.

How I learned it

I learned RAG by building natural-language access to engagement and participation data.

How I use it

I use retrieval to connect user questions with relevant structured or indexed project data.

Concepts I work with

  • Retrieval
  • Chunking
  • Embeddings
  • Grounding

What I learned

Retrieval quality and source structure often matter more than prompt complexity.

Applied experience

Projects using Retrieval-Augmented Generation

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