From the source
Amazon's post walks through the architecture and a reference implementation for an enterprise agentic AI platform on Amazon Bedrock and Bedrock AgentCore, aimed at platform teams supporting many agent-building teams.
- It argues the model and tool use are not the blocker; the bottleneck is everything around them, such as which team owns each model and tool and how cost and health stay visible across accounts.
- The design uses four connected planes — developer experience, platform control, Workstream execution, and assurance and operations — and scales by a Workstream cell rather than a manually configured agent or one shared workload account.
- Separate inference and tool gateways govern access: every untrusted inference request passes an approved gateway that applies guardrails, restricts models and Regions, and enforces per-team rate limits, token quotas and budgets.
- The blueprint, built on AgentCore, adds ownership, account boundaries, delivery, observability, cost governance and retirement as deployable infrastructure as code, and the post says readers can deploy a governed Workstream from it.
- The blueprint implements a federated operating model, which the post says is where most enterprises land, with a central platform team providing governed services while domain teams own their agents, tools and data.