Build multi-agent teams that remember every customer with Amazon Bedrock AgentCore
Blog post from n8n
An n8n workflow template demonstrates how Amazon Bedrock AgentCore harness can run a customer-support team of triage and specialist agents that share persistent, customer-scoped managed memory without requiring a vector database or separately deployed agents. Incoming questions are assigned a common Actor ID and Session ID, enabling a triage agent, analysis specialist with Code Interpreter, architecture specialist with AWS skills, and general research specialist to access the same conversation history through one reusable harness. The example shows an agent calculating whether API usage exceeds a daily limit, then a different agent recommending an architecture change using those earlier figures without requiring the customer to repeat them. n8n manages triggers, routing, credentials, and responses such as Slack posts, while AgentCore runs agent loops in isolated Firecracker microVMs and provides durable memory. Setup requires the verified AgentCore n8n node, AWS model access, separate IAM caller and execution identities, and optionally Slack credentials; users should account for underlying AgentCore memory and capability charges and delete the shared harness when testing is complete.
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