What changed
AWS has announced the release of the Pluggable Agentic AI Framework, a seven-layer composable reference architecture designed to help organizations transition multi-agent AI applications from prototype to production scale. The framework is built on Amazon Bedrock AgentCore and aims to address the challenges of running AI agents in production environments, including handling concurrent user requests, ensuring reliability, and maintaining security and compliance.
What this means in practice
The framework provides a structured approach to building, securing, and operating agentic AI applications at scale. It is organized into seven distinct layers, each with a specific responsibility and a stable contract. These layers include data and knowledge management, model and inference choices, orchestration, security and guardrails, application interface, and observability.
The data and knowledge layer ensures agents have access to relevant, up-to-date information through a defined protocol. Model and inference choices are decoupled from agent logic, allowing for flexible model switching based on evaluation.
Orchestration involves distributing work efficiently, using single agents for simple tasks and supervisors for complex workflows.
Security and guardrails are integrated from the start, with measures like authentication, access control, and data masking to protect against risks like prompt injection and data poisoning.
Limitations and availability
The framework is designed as a reference architecture and not a mandatory set of choices. Organizations can substitute components based on their existing infrastructure and requirements. The framework is available through Amazon Bedrock AgentCore and integrates with services like Amazon Bedrock Guardrails, Amazon Bedrock AgentCore Identity, and AWS Security and governance controls. The supplied announcement does not specify exact release dates or availability timelines for all components.
