A deep dive into building reliable multi-agent AI applications using Azure Cosmos DB, demonstrated through a travel assistant app. Covers the multi-agent pattern (orchestrator + specialists) versus single-agent limitations, and introduces the Azure Cosmos DB Agent Memory Toolkit (public preview) which provides four memory types: facts, procedural, episodic, and user summaries. The session explains agentic memory vs. RAG, including threshold-driven extraction, conflict resolution with audit trails, and rolling summarization. Architecture highlights include MCP server decoupling, LangGraph checkpointing for state management, hybrid search with hierarchical partition keys, and new Cosmos DB features: distributed transactions (cross-container atomic operations, public preview), per-partition automatic failover (GA), integrated embeddings via Microsoft Foundry, global secondary indexes (GA) for cross-tenant analytics queries, and the Cosmos DB Agent Kit for best-practice code review in CI/CD pipelines.