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Course Outline

Overview of Managed AI Agents

  • Definition and scope of AgentCore
  • Primary functionalities and service components
  • Application scenarios for public sector and industrial use

Initial Agent Architecture and Design

  • Defining agent roles and operational objectives
  • Setting up managed agent parameters
  • Practical exercise: Developing a foundational agent structure

Enhancing Agent Functionality with Memory and Tools

  • Incorporating persistent storage and contextual data
  • Connecting external tools and application programming interfaces
  • Practical exercise: Expanding agent operational capabilities

Foundations of AgentCore Runtime and Gateway

  • Summary of runtime system architecture
  • Implementing gateway integration for application access
  • Practical exercise: Linking an agent to a client application

Deployment of Managed Agents

  • Available deployment strategies within AgentCore
  • Considerations for scalability and operational continuity
  • Practical exercise: Deploying a fully managed agent instance

Monitoring and Observability Standards

  • Utilizing metrics and dashboards in AgentCore
  • Tracking performance indicators and usage patterns
  • Practical exercise: Establishing a monitoring workflow

Best Practices and Future Developments

  • Governance, compliance, and regulatory adherence
  • Optimizing for system usability and dependability
  • Prospective trends in managed AI agent infrastructure

Conclusions and Subsequent Actions

Requirements

  • Foundational understanding of artificial intelligence and machine learning principles
  • Proficiency with cloud service environments
  • Exposure to application development processes

Target Audience

  • Professionals interested in AI technologies
  • Product management staff
  • Generalist software developers
 14 Hours

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