Graduate Level: The Multi-Agent Conversation
Manage context across multi-agent systems: sharing info among agents, maintaining conversation state
When you graduate from a single agent to a system of multiple, specialized agents working together, you face a new challenge: how do they communicate? By default, Agent A has no knowledge of Agent B's work. This lesson explores the primary architectural patterns for managing state and sharing context across a multi-agent system.
Related topics
- Optimize attention allocation in long-context agents: ensuring critical information isn't lost in large context windows
- Design agent-based RAG systems: agents that autonomously retrieve, analyze, and synthesize from document collections
- Troubleshoot complex agent failures: diagnosing tool selection errors, reasoning breakdowns, context loss, or safety interventions
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