AWS Guide: Building Multi-Agent Systems with LangGraph and Strands
AWS ML Blog · rss · 2026-07-29
The AWS Machine Learning Blog published a tutorial demonstrating how to build a production-ready multi-agent system using LangGraph and Strands on Amazon Bedrock AgentCore. Using a financial market surveillance use case, the post showcases agent orchestration and error recovery in complex workflows.
Key architectural highlights:
- Macro-orchestration: LangGraph manages dynamic routing, parallel execution, and state sharing via directed graph state machines. Its persistent checkpoint system enables failure recovery and human-in-the-loop reviews.
- Micro-reasoning: Strands Agent acts as the reasoning engine within nodes, featuring a model-agnostic architecture that supports various LLMs like Claude, alongside robust tool integration.
- Anti-injection design: Data query tools strictly separate discovery from retrieval, using parameterized SQL to reject unknown fields and prevent LLM prompt injection.
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