Part 7 — Memory Retrieval Strategies

This section focuses on how agents get memories back into context — proactive vs reactive recall, query-time and tool-based retrieval, ranking, caching, and failure modes.

What you will learn

  • Vector, keyword, hybrid, and fetch-based retrieval patterns
  • When the agent should decide to remember versus when the system retrieves automatically
  • Ranking, thresholds, multi-hop recall, and context-budget trade-offs
  • APIs and tool-call designs for retrieval in agent frameworks

Chapters in this section

There are 18 chapters in this part. Open any chapter to read it on its own, or work through them in order.

  1. 1 Retrieval Types: Vector, Keyword, Hybrid, and Direct Fetch
  2. 2 Proactive Recall vs Reactive Recall
  3. 3 Query-Time Retrieval: Using the Current Message as a Search Query
  4. 4 Tool-Based Retrieval: Letting the Agent Decide When to Remember
  5. 5 Fetch-Based Retrieval: Retrieving Known, Bounded Memories
  6. 6 Multi-Hop Retrieval Across Related Memories
  7. 7 Retrieval for Reasoning Traces vs Retrieval for Final Answers
  8. 8 Similarity Thresholds and Precision Control
  9. 9 Ranking and Scoring Retrieved Memories
  10. 10 Combining Multiple Retrieval Strategies in One Query
  11. 11 Retrieval Latency and Its Effect on Agent Responsiveness
  12. 12 Caching Retrieved Memories
  13. 13 Retrieval for Multi-Agent Coordination
  14. 14 Personalized Retrieval: Scoping Results to the Right User
  15. 15 Retrieval Failure Modes: Over-Retrieval and Under-Retrieval
  16. 16 Designing Retrieval APIs for Agent Frameworks
  17. 17 Retrieval as a First-Class Tool Call
  18. 18 Balancing Retrieval Recall with Context Budget