AI engineering
RAG is a data pipeline before it is a prompt
Retrieval quality depends on what gets indexed, how it is chunked, and whether search finds evidence relevant to a question.
Aryan (@istmX)3 min read
Start with a clear boundary
Clean and inspect source documents before tuning prompts. Preserve metadata and source locations so retrieved passages remain traceable.
Handle failure deliberately
Measure whether the right passage appears in the retrieved set separately from whether the model writes a good answer. These are different failure modes.
Make the result understandable
Carry source identifiers into generated answers. A useful retrieval system lets people verify claims and admits when evidence is missing.