AI agents are rapidly moving from hype to reality, but building reliable, production-ready Agentic AI systems remains a challenge. These systems can plan tasks, use tools, reflect on outcomes, and even collaborate with other agents—but scaling them introduces complex hurdles.

This session draws from real-world deployments over the past year, offering practical guidance for organizations and teams looking to move beyond experimentation. Attendees will gain insights into three essential pillars:

 

Architecting agent systems for scalability and resilience

 

Optimizing performance through better memory, context handling, and latency reduction

 

Observability techniques to monitor and evaluate agent behavior effectively

 

Packed with field-tested lessons and actionable strategies, this talk equips participants to design and deliver AI agent systems that not only work in theory, but thrive in production environments.

 

Target Audience: AI practitioners, technical leaders, and product teams looking to operationalize agentic AI at scale.