Haim Michael

Implementing AI Agent Control Logic with Pattern Matching

Agent-based architectures are becoming a common foundation for modern software systems. The key engineering challenge is orchestrating agent interactions while maintaining a reliable, understandable control flow. This session explores how pattern-matching features offer a powerful approach to implementing agent orchestration logic, demonstrating how to model agent outcomes as structured result types and route execution based on them through practical examples.