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Topics/RAG

RAG

Retrieval, vector databases, and practical knowledge grounding.

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This topic is less about “better search” and more about reducing confident wrong answers.
Retrieval quality, privacy/security, freshness, and operating cost are the core levers.

Practical checks

  • Many “model” failures are actually retrieval failures—debug retrieval first.
  • Without clear data access and PII policy, RAG projects often stall in operations.
  • If freshness matters, design re-index cadence and evidence display together.

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