Winning the AI Agents Edge Race

AI agents are advancing from prototypes to production, yet large organizations often face challenges such as fragmented workflows, noisy context, tool failures, cost constraints, and inadequate evaluation. This talk will address how to bridge the AI agent value gap using context window and token optimization, orchestration, loop engineering, referee-based control layers, and LLMOps. We will link recent findings on stalled AI pilots to practical architectural choices that enhance reliability, observability, governance, and operational value. Attendees will learn to design agentic systems that retrieve relevant context, coordinate tools safely, manage runtime behavior, minimize token waste, and validate outputs before execution. This session will equip technical leaders, CIOs, and AI practitioners to move beyond chatbot pilots and deploy production-ready AI agent systems that operate safely and reliably at enterprise scale.