Amazon Bedrock AgentCore: 9 Rules for Enterprise AI Agents

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Enterprise AI Agent, 9 Core Rules

  • AWS Releases Amazon Bedrock AgentCore Best Practices
  • Presents Session Isolation microVM, Multi-Agent Collaboration Patterns
  • Distinguishing Agentic vs. Deterministic Code is Key

What Happened?

AWS has released a guide to building enterprise AI agents based on Amazon Bedrock AgentCore.[AWS] AgentCore is a platform for creating, deploying, and managing AI agents at scale.

The 9 rules are key: Narrowing scope, observability, tool definition, automated evaluation, multi-agent, scaling, code separation, testing, and organizational expansion.

Why is it Important?

Frankly, AI agent demos and production are different games. This guide is an attempt to bridge that gap.

The AgentCore Gateway stands out. It centrally manages scattered tools such as MCP servers and Lambda. It finds the right tool with semantic search.

Session isolation is also a feature. Each session runs in a separate microVM, and the VM is terminated when the session ends.

What Will Happen Next?

Personally, the distinction between “agentic vs. deterministic code” is the most practical. Date calculations with code, intent understanding with agents. The team that finds this balance will win.

Frequently Asked Questions (FAQ)

Q: What is the difference between AgentCore and existing Bedrock Agents?

A: Bedrock Agents focuses on building single agents. AgentCore is an enterprise platform that includes large-scale operation of multiple agents, tool integration, and session management.

Q: What about multi-agent collaboration?

A: Supports sequential, hierarchical, and P2P patterns. Shares context with AgentCore Memory and monitors handoffs with OpenTelemetry.

Q: How is security ensured?

A: Identity is responsible for authentication, Policy for authorization, and Gateway for pre-execution validation. Each session runs in an isolated microVM.

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