Naresh Dulam

Enterprises are eager to adopt agentic AI but many run into the same challenges: unclear frameworks, messy integrations, misconceptions about system capabilities, and confusion around design choices. This session will share real lessons learned to help you avoid common pitfalls and build agentic systems that actually perform at scale. We’ll break down the essential decisions, single vs. multi-agent design, choosing the right framework, whether to use MCP, and how to integrate agents into existing workflows. You’ll walk away with a clear understanding of the challenges, the tradeoffs, and the practical steps required to build reliable agentic AI in the enterprise.

• The top misconceptions that derail agentic AI projects and how to avoid them
• Guidance on selecting design patterns and frameworks (single agent, multi-agent, MCP, and more)
• How to integrate agents into existing workflows without adding complexity
• Field-tested strategies to overcome data, governance, and operational barrier
• A concise blueprint for building scalable, effective agentic AI systems