Decision path
RAG Product Stack
Use this path when you are building a knowledge-heavy AI product and need to decide what to add first.
Step 1
Prompt Engineering
First clarify the task, output contract, and examples.
Step 2RAG
Add retrieval when the model needs private, updated, or source-backed knowledge.
Step 3Chunking
Split source material into pieces that answer real user questions.
Step 4Embedding
Represent chunks so semantic similarity can be searched.
Step 5Vector Database
Store and retrieve embeddings when the corpus grows.
Step 6Reranking
Improve ranking after initial retrieval starts finding useful candidates.
Step 7Evaluation
Measure retrieval quality and answer quality before scaling.