Building Production-Ready AI Agents with Bedrock AgentCore

Organizations are rapidly moving from simple chatbots to autonomous AI agents that can execute complex workflows. To bridge the gap between a basic proof-of-concept and a reliable production deployment, developers need a robust framework designed for security, scalability, and integration. This text-based course guides you through the foundational concepts and practical architectures of Bedrock AgentCore on AWS. You will gain the skills to build, connect, and monitor production-grade AI agents that securely interact with enterprise APIs, maintain context across sessions, and operate within strict safety guardrails. What you'll learn: - Understand the core architecture of Bedrock AgentCore and how agentic workflows differ from standard LLM prompts - Configure secure integrations using API gateways, credential management, and identity controls - Implement persistent memory structures and context-aware conversation history for multi-turn interactions - Apply fine-grained safety policies and guardrails to ensure agents behave predictably and securely in enterprise environments - Integrate code execution environments and browser tools to allow agents to analyze data and navigate web resources - Monitor agent performance and system health using modern observability frameworks and evaluation metrics The course begins with essential terminology and core agent concepts before progressing to advanced topics like secure tool integration, memory systems, and production observability. You will work through written architectural breakdowns and conceptual exercises designed to reinforce best practices. This course is designed for software developers, cloud engineers, and technology professionals who want to build autonomous AI systems. No prior experience with agentic frameworks is required, though a basic understanding of cloud concepts and Python is helpful. Start reading today to transform your understanding of agentic AI and build systems ready for the real world.