Building an AI agent demo is easy. Building one that behaves reliably, maintains context, uses tools correctly, and scales in real-world environments is a completely different challenge.

This session explores the hidden engineering problems behind modern AI agents and how developers can build more reliable agentic systems using Azure AI services and modern software engineering practices.

Topics include:

Why most AI agents fail in production
Prompt engineering vs system engineering
Agent memory and context management
Tool orchestration challenges
Retrieval reliability and hallucination reduction
Observability for AI systems
Cost and latency tradeoffs
Human-in-the-loop workflows
Practical architecture patterns using Azure AI

Attendees will gain practical insights into designing AI systems that move beyond demos into usable engineering solutions.