Building Agentic AI with Amazon Bedrock AgentCore

In this course, you’ll explore the core principles and strategies for designing Agentic AI systems using AWS services. You’ll learn how Agentic AI differs from traditional conversational systems, and how to use tools like Strands Agents SDK, and Amazon Bedrock AgentCore to build autonomous, goal-driven solutions that solve real-world problems.

Course objectives

This course includes presentations, hands-on lab, and group exercises.
In this course learners will:

  • Define agentic AI characteristics and differentiate them from traditional AI systems.
  • Identify the core agent components and their interactions.
  • Describe how Bedrock AgentCore services support agentic AI.
  • Deploy agents by using supported frameworks with AgentCore Runtime.
  • Describe the core features of AgentCore Runtime.
  • Configure serverless execution with session isolation.
  • Configure AgentCore Identity for enterprise security requirements.
  • Create policies to secure agent tool calls using AgentCore Policy.
  • Implement secure token management and permission delegation.
  • Ensure compliance with data governance and audit requirements.
  • Implement different tool integration patterns, including built-in tools and protocol-based tools.
  • Design and deploy Model Context Protocol (MCP) servers and clients for extensible agent capabilities.
  • Describe common authentication patterns for agent tool use.
  • Configure AgentCore Gateway components for secure and authorized tool access.
  • Implement agentic memory patterns for different use cases.
  • Configure AgentCore Memory operations for context-aware development.
  • Optimize memory performance for production workloads.
  • Configure AgentCore Observability for production monitoring.
  • Implement Amazon CloudWatch integration and specialized tracing.
  • Describe the core features of AgentCore Evaluations.
  • Integrate agentic systems with production APIs and services.
  • Design deployment strategies for production environments.
  • Assess production readiness and establish continuous improvement processes

Target Audience 

  • Level: Intermediate (200)
  • Software developers seeking intermediate knowledge for building advanced agentic AI systems
  • Technical professionals exploring AI capabilities and interested in building advanced agentic AI systems.
  • Development teams building advanced agentic AI solutions.

Prerequisites

We recommend that attendees of this course have:

  • Agentic AI Foundations

Module 1: Foundations of Agentic AI Patterns

  • Agent building blocks
  • Amazon Bedrock AgentCore introduction

Module 2: AgentCore Runtime and Framework Integration

  • Supported frameworks and implementation
  • AgentCore Runtime overview
  • Infrastructure and deployment

Module 3: Security and Identity Management

  • Security and identity management
  • Securing your agents with AgentCore Identity

Module 4: Tool Integration and AgentCore Gateway

  • Amazon Bedrock AgentCore Policy
  • Built-in tools and custom integration
  • Model Context Protocol (MCP)
  • AgentCore Gateway
  • Implementing AgentCore Gateway
  • Amazon Bedrock AgentCore Policy

Module 5: Agentic Memory Implementation

  • Agentic memory core concepts
  • AgentCore Memory
  • Securing AgentCore Memory

Hands-on Lab: Enhance and Scale Agents with Amazon Bedrock AgentCore (demo only available at launch, labs released shortly after)

Module 6: Production Monitoring and Observability 

  • Monitoring agents with AgentCore Observability
  • Verifying agent performance with AgentCore Evaluation

Module 7: Course Wrap-up

  • Next steps and additional resources
  • Course summary

Practical information

Duration: 1 day
Price: 9.900
Language: English, Norwegian
Format: Can be delivered as an open course or as an in-house course

FAQ

Hva betyr “agentic AI”?
Agentic AI er autonom programvare som kan planlegge, utføre og koordinere komplekse oppgaver på egen hånd ved hjelp av målrettet logikk og tilgang til verktøy og data gjennom spesialiserte tjenester som Amazon Bedrock AgentCore.

Hvorfor bruke Amazon Bedrock AgentCore?
AgentCore gir en serverløs, skalerbar og sikker plattform for å bygge, distribuere og drive AI-agenter i produksjon uten å måtte bygge og vedlikeholde infrastruktur selv.

Hvilke rammeverk og modeller kan jeg bruke med AgentCore?
AgentCore støtter åpne rammeverk som LangChain, Strands Agents og CrewAI, og kan brukes sammen med en rekke foundation-modeller som Claude, Gemini, Llama og Nova.

Hva er forskjellen mellom vanlig AI-bruk og agentic AI?
Vanlig AI svarer på enkeltforespørsler, mens agentic AI kan autonomt ta beslutninger, planlegge arbeidsflyter og utføre flere steg for å nå et mål.

Hvordan hjelper kursinnholdet meg med produksjonsetting?
Du lærer å designe, implementere og drifte agentbaserte systemer med fokus på sikkerhet, skalerbarhet og integrasjon i reelle IT-miljøer, inkludert bruk av tjenester som AgentCore Runtime, Memory og Gateway.

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