Abstract
While 2025 was the year of agentic experimentation, 2026 is the year of architectural
reckoning. As organizations move from single-task bots to autonomous multi-agent systems,
traditional infrastructure is buckling under the weight of orchestration complexity,
non-deterministic latency, and spiraling token costs.
In this session, we move past the hype to address the "hard engineering" required to develop
truly scalable AI systems. We will explore how to build a unified AI platform that bridges
multi-cloud environments (GCP, Azure, AWS) while maintaining the rigorous security and
reliability standards required for global enterprise deployment.

Key Takeaways

The Orchestration Layer: How to design a robust backbone for multi-agent systems that
prevents "agentic loops" and cascading failures.
Hybrid-Cloud Scaling: Strategies for distributing inference and data retrieval across
clouds to optimize for latency and compliance.
The Reliability Framework: Moving from "Best Effort" to "Enterprise Grade" by
integrating Zero Trust security principles within agentic workflows