Product Management Challenges in Building Agentic AI Applications

Explore the unique challenges product managers face when building autonomous AI systems that can reason, act, and make decisions independently in this comprehensive webinar. Learn how Agentic AI fundamentally differs from traditional AI tools and discover why conventional product management approaches fall short when dealing with intelligent agents. Understand the core components of agentic systems including intent recognition, planning capabilities, memory systems, and feedback loops, while examining the hierarchy of agent capabilities from basic automation to full autonomy. Address critical challenges including system unpredictability, cost management, tool access control, bias mitigation, compliance requirements, and privacy concerns that emerge when AI systems operate with greater independence. Develop frameworks for establishing trust, governance, and ethical compliance in goal-driven AI applications while learning to design defensive user experiences with appropriate guardrails. Master the balance between performance, cost, and correctness in agentic systems, and gain insights into the Model Context Protocol (MCP) for better system integration. Discover why product managers need deep technical fluency to succeed in this space and learn strategies for designing transparent, explainable interfaces that maintain user control and trust. Navigate real-world deployment pitfalls and understand how to scope valuable agentic use cases with proper oversight mechanisms.