用 Deep Agents 和 Bedrock AgentCore 构建上下文丰富的研究智能体
Build context-rich research agents with Deep Agents and Bedrock AgentCore
AWS 教你用 Deep Agents 和 Bedrock AgentCore 搭研究智能体，还能用 CLI 部署成托管服务，适合搞多步AI流程的开发者。
本教程介绍如何使用 Deep Agents 和 Bedrock AgentCore 构建竞争研究智能体。你将在多步AI工作流中创建隔离执行环境。
在第二部分，你可以通过 AgentCore CLI 将同一智能体部署到 Bedrock AgentCore Runtime，作为托管、会话隔离的服务运行。
Build context-rich research agents with Deep Agents and Bedrock AgentCore
In this post, you'll build a competitive research agent that demonstrates this pattern end to end. This walkthrough targets developers building multi-step AI workflows who need isolated execution environments for their agents. In Part 2 of the notebook, you can deploy this same agent to Bedrock AgentCore Runtime using the AgentCore CLI, so it runs as a managed, session-isolated service.
This report is categorized under AITOP's "How-to" desk. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include Deep Agents, Bedrock AgentCore, AgentCore CLI, 智能体.
Primary source verification: published directly by AWS Machine Learning Blog with first-party authority.
