Designing Agentic AI Systems with Bedrock and MCP

AI is evolving from simple chat interfaces to autonomous agents that can plan, use tools, and collaborate to solve complex problems. Understanding how to design these agentic systems is becoming an essential skill for modern developers and system architects. This text-only course guides you through the core architectural patterns of agentic AI. You will learn how to structure single and multi-agent workflows, implement persistent memory, integrate external tools securely, and establish robust safeguards to ensure predictable agent behavior. What you will learn: 1. Understand the core components of agentic AI, including planning, tool use, and execution loops. 2. Configure Bedrock Agents to automate multi-step reasoning and decision-making tasks. 3. Implement the Model Context Protocol (MCP) to seamlessly connect agents with external data sources. 4. Design multi-agent coordination frameworks where specialized agents collaborate to solve complex objectives. 5. Manage agent memory and state using vector databases and persistent storage patterns. 6. Apply security safeguards and guardrails to control agent actions and protect sensitive data. The course begins with foundational concepts of agency and reasoning models before moving into practical architecture patterns. You will read through detailed design scenarios, explore configuration examples for Bedrock and MCP, and analyze structured text-based use cases. This course is designed for software developers, system architects, and tech-savvy beginners who want to understand the next wave of AI integration. No prior experience with agentic frameworks is required. Start reading today to build a strong foundation in the future of autonomous software design.