Build Your First RAG Project Without the Usual Mistakes

Define one question the system should answer from one controlled document collection. Specify who asks it, what a good answer contains, and what must happen when evidence is missing.

A narrow support-policy assistant is a better first project than a universal company chatbot.

Write 20–40 realistic questions, including ambiguous requests, missing answers, outdated statements, and documents that disagree. Record the expected evidence for each.

Measure retrieval separately from answer quality. Prompt tuning cannot repair evidence that never reaches the model.

Return the document title and precise source location beside each important claim. When evidence is weak, say so plainly.

A useful refusal is better than a confident invention.

Log retrieval results, outputs, latency, and corrections. Review failure clusters weekly and change one layer at a time.

Only add reranking, query rewriting, or agentic search after the baseline shows a specific limitation.