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Retrieval quality evaluation

Chunking and freshnessEmbeddings in PostgresVector index tuningChoosing embedding modelsHybrid search and rerankingRetrieval quality
Development

Retrieval quality evaluation

  • A Retrieval Test Set for Embedding Model Swaps
  • Measuring Retrieval Quality: Recall and Precision
  • Writing a Regression Query for Every Retrieval Bug
  • A Query Rewrite Step: When the Model Paraphrases First
  • A Relevance Floor on Context: Setting It from the Judged Set
  • Connecting Retrieval Scores to Support Outcomes
  • Generating Realistic Query Sets for Retrieval Tests
  • Measuring Recall@k and Precision on a Golden Set
  • Putting a Relevance Floor on Retrieved Context
  • Quoting a Retrieved Passage Without Blending It Into the Answer
  • Reading a Retrieval Bug in Traces: Query, Chunks, Scores
  • Retrieval That Returns Zero Chunks: Rules for the Next Turn
  • Sampling Queries to Measure Recall on a Live Index
  • Scheduling a Nightly Recall Check on a Fixed Query Sample
  • Tying Retrieval Scores to User Behavior
  • When a Support Agent Should Quote a Policy vs Summarize It
  • When a Test Set Is Not Enough: Add Production Monitoring
Retrieval and embeddings

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