Part 12 — Multi-Agent and Distributed Memory Systems

This section covers memory when more than one agent is involved — shared state, partitioning, write coordination, consistency, and handoffs across teams of agents.

What you will learn

  • Why multi-agent setups break single-context memory assumptions
  • Shared vs partitioned memory and orchestrator vs sub-agent stores
  • Conflict resolution, race conditions, and consistency models
  • Scaling and synchronizing memory across concurrent agent deployments

Chapters in this section

There are 16 chapters in this part. Open any chapter to read it on its own, or work through them in order.

  1. 1 Why Multi-Agent Systems Break Single-Context Memory Assumptions
  2. 2 Shared Memory Across Agents in a Team
  3. 3 Memory Partitioning by Agent Role
  4. 4 Coordinating Memory Writes from Multiple Agents
  5. 5 Conflict Resolution in Shared Memory
  6. 6 Memory as a Communication Channel Between Agents
  7. 7 Sub-Agent Memory vs Orchestrator Memory
  8. 8 Consistency Models for Distributed Agent Memory
  9. 9 Race Conditions in Concurrent Memory Writes
  10. 10 Designing Memory APIs for Agent Frameworks
  11. 11 Memory Handoff Between Agents in a Pipeline
  12. 12 Global Memory vs Local Memory in Agent Swarms
  13. 13 Memory Synchronization Across Long-Running Agent Sessions
  14. 14 Scaling Memory Systems for Many Concurrent Agents
  15. 15 Memory in Human-in-the-Loop Agent Systems
  16. 16 Federated Memory Across Independent Agent Deployments