Session
Agentic AI Systems Don't Fail at the Model Layer - They Fail in Production
[Disclaimer: The opinions, insights, and perspectives shared in my session and its details are solely my own and do not reflect those of my current / past employers.]
Note (4/29/26):
Awaiting employer approval before sharing the detailed and complete session description to respect guidelines and comply with policies.
Overview:
The most expensive lesson enterprises are learning is this: Agentic AI failures are not model failures - they are system design failures. The model is rarely the problem; the architecture around it is. Gartner predicts over 40% of agentic AI projects will be canceled by 2027 - not because models underperformed, but due to governance gaps, uncontrolled costs, and systems never designed to be reliable.¹
Structure:
Layer 1: Tool Connectivity and the Integration Problem ("MCP & Tool Schema Designs")
Layer 2: Context, Memory, and the Limits of RAG ("RAG vs. Knowledge Graphs")
Layer 3: Multi-Agent Coordination and Failure Isolation ("Orchestration & Agent-Washing")
Citations:
¹ Gartner, June 2025 press release - over 40% of agentic AI projects to be canceled by 2027
Moeez Khan
Software Engineer @ Amazon Web Services • AWS Agentic AI • Enterprise & Mainframe Modernization
Dallas, Texas, United States
Links
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top