In today's rapidly evolving AI landscape, understanding how to strategically orchestrate AI agents is crucial for software engineers and machine learning practitioners. Most developers struggle with building efficient, predictable multi-agent systems because they rely on the standard "agent-centric" approach, where agents must constantly decide which tools to use—leading to inefficient workflows. This project offers you a unique opportunity to master a more advanced "task-centric" approach that creates focused, deterministic workflows by assigning specific tools directly to the tasks that need them. By completing this guided project, you'll gain practical experience in building sophisticated AI systems while learning the architectural patterns that separate amateur implementations from professional-grade solutions.

This hands-on project delivers cutting-edge skills in AI agent orchestration that are increasingly demanded in the technology sector. In just 30 minutes, you'll master a sophisticated architectural pattern that most developers never learn—the strategic difference between giving tools to agents versus assigning tools to specific tasks. The course provides clear, practical demonstrations of both approaches, allowing you to understand when and why to use each method. By the end, you'll have both the theoretical understanding and practical implementation skills to build production-grade multi-agent systems that are more efficient, maintainable, and predictable than standard approaches.

Upon completing this 30-minute intermediate-level lab, you will be able to:

Let your learners know what technology and skills they'll need prior to starting this guided project. Remember that the IBM Skills Network Labs environment comes with many things pre-installed (e.g. Docker) to save them the hassle of setting everything up. Also note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.