Building Fully Managed AI Agents with AgentCore: From Concept to Production Training Course

Introduction to Managed AI Agents

• Defining AgentCore
• Core features and available services
• Industry-specific use cases

Architecting Your Initial Agent

• Defining agent roles and objectives
• Setting up managed agent parameters
• Practical lab: Constructing a basic agent

Augmenting Agents with Memory and Tools

• Incorporating persistence and contextual data
• Connecting external tools and APIs
• Practical lab: Expanding agent functionality

AgentCore Runtime and Gateway Fundamentals

• Overview of runtime architecture
• Integrating the gateway for application use
• Practical lab: Linking an agent to an application

Deploying Managed Agents

• Deployment strategies within AgentCore
• Considerations for scaling and operations
• Practical lab: Launching a fully managed agent

Monitoring and Observability

• Utilizing AgentCore metrics and dashboards
• Monitoring performance and usage patterns
• Practical lab: Creating a monitoring workflow

Best Practices and Emerging Trends

• Governance and compliance frameworks
• Enhancing usability and system reliability
• Future directions in managed AI agents

Conclusion and Recommended Next Steps