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Course Outline
Overview of Managed AI Agents
- Defining AgentCore
- Essential features and services
- Cross-industry use cases
Architecting Your Initial Agent
- Defining agent roles and objectives
- Setting up managed agent configurations
- Practical lab: constructing a basic agent
Augmenting Agents with Memory and Tools
- Incorporating persistence and context
- Connecting tools and APIs
- Practical lab: expanding agent capabilities
Foundations of AgentCore Runtime and Gateway
- Overview of runtime architecture
- Integrating the gateway for applications
- Practical lab: linking an agent to an application
Deploying Managed Agents
- Deployment strategies within AgentCore
- Considerations for scaling and operations
- Practical lab: releasing a fully managed agent
Supervision and Observability
- Metrics and dashboards in AgentCore
- Monitoring performance and utilization
- Practical lab: creating a monitoring workflow
Best Practices and Emerging Trends
- Focus on governance and compliance
- Optimizing for usability and reliability
- Future trajectories in managed AI agents
Recap and Subsequent Steps
Requirements
- Foundational knowledge of AI and machine learning principles
- Acquaintance with cloud services
- Experience with application development workflows
Target Audience
- AI enthusiasts
- Product managers
- Generalist developers
14 Hours