AWS unveils seven-layer pluggable enterprise agent reference architecture on Bedrock AgentCore
AWS ML Blog · rss · 2026-11-10
AWS ML Blog published the "Pluggable Agentic AI Framework," a seven-layer composable reference architecture for taking multi-agent applications from prototype to production. The authors argue most agent initiatives stall not because of the model, but because every team rebuilds the same scaffolding—routing, guardrails, observability—after the fact.
The seven layers:
- Data & Knowledge: retrieval, embeddings, and structured/unstructured access via Bedrock Knowledge Base, OpenSearch Serverless vectors, S3 Vectors.
- Model & Inference: model choice driven by configuration, unified through a proxy like LiteLLM so models can be swapped without rewriting app logic.
- Orchestration: single agent for simple tasks; supervisor delegating scoped specialists via MCP/A2A and a centralized agent registry, with bounded autonomy to avoid tool sprawl and context bloat.
- Security & Guardrails: treat external content as untrusted, authenticate every request, fine-grained tool-call authorization, temporary scoped credentials, PHI/PII masking, tamper-evident audit trails, human approval gates, circuit breakers.
- Application: keep it thin; optionally add a cheap decision-model call to score scope/urgency before running the full agentic loop.
- Observability: end-to-end traces from day one, plus per-request cost/token usage, TTFT, and security signals.
All technology choices are reference implementations and can be substituted.
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