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Discover how AI agents can transform your daily system administration workflows on IBM i. This session introduces practical approaches to building agents that automate routine tasks, monitor system health, and respond to operational issues—all while leveraging the IBM i MCP server for seamless integration. You'll learn how to create both individual agents for specific tasks and orchestrated teams of agents that collaborate to solve complex administrative challenges. Through real-world examples, we'll demonstrate agents handling everything from performance monitoring and job scheduling to capacity planning and automated troubleshooting. Whether you're analyzing system logs, or optimizing Db2 for i performance, you'll leave with actionable knowledge to implement AI-powered automation in your own environment. This session is designed for system administrators who want to enhance their productivity without becoming AI experts, focusing on practical implementations using open-source tools and the official IBM i MCP server.
Learning Objectives:
Understand the architecture and capabilities of AI agents specifically designed for IBM i system administration, including how agents interact with IBM i APIs, CL commands, and Db2 for i through the MCP server interface. Implement individual AI agents for common administrative tasks such as system monitoring, job queue management, and performance analysis using practical patterns and best practices. Design multi-agent teams that collaborate to handle complex workflows, including how agents communicate, share context, and coordinate actions across different administrative domains. Evaluate appropriate use cases for AI agent automation in your environment, distinguishing between tasks best suited for agent-based solutions versus traditional scripting approaches. Deploy AI agents using the IBM i MCP server framework, including configuration, security considerations, and integration with existing system management tools and processes.
