About this Session
AI agents are moving beyond simple chatbots into complex decision-making systems. But how do you design agents that behave predictably, scale reliably, and actually solve real business problems?
This session explores practical architectural patterns for building production-ready AI agents, drawn from real-world implementation at a global scale. We'll cover:
- Business Workflow Complexity: Create agents that can actually solve really complex problems and maintain context
- Decision Trees vs. Dynamic Reasoning: When to use structured logic vs. letting LLMs decide
- Error Recovery & Graceful Degradation: Agents that fail safely when they don't know something
- Human-in-the-Loop Patterns: Seamless handoffs between AI and human experts
