ML_Systems_Sow
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 Posted - November 10 2026 : 03:44:12 AM
<a href="https://ai-development-services.com/">RAG evaluation</a> should separate retrieval failure from generation failure. If the right passage never reaches the model, prompt changes can improve tone without fixing the answer. Start with a small evaluation set that identifies the expected source for each query.
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During testing, record which document chunks were retrieved and whether their metadata matched the intended access rules. A correct answer from an unauthorized document is still a system failure. Tune chunking or ranking only after the failed cases are classified, then evaluate how the model responds when retrieval returns weak or conflicting evidence.AEV High Steer |
Test Retrieval Before Tuning RAG Answers
