sponsored | Agent Mesh: Build Enterprise Agentic AI at scale by learning from distributed systems

Prompt-based AI started as an interaction model. Agentic AI turns it into a distributed system problem.
While many organizations are experimenting with multi-agent workflows, most implementations still resemble fragile prompt chains stitched together with synchronous calls and centralized orchestration. This approach may work in demos — but it collapses under enterprise requirements such as reliability, scalability, fault isolation, governance and observability.
We have seen this movie before.
A decade ago, microservice architectures suffered from the same tight coupling and coordination failures until event-driven, asynchronous communication became the backbone for resilient distributed systems. Autonomous AI agents exhibit similar behaviour: they plan independently, collaborate dynamically, retry tasks, exchange context and evolve at runtime. Treating them like synchronous services repeats the mistakes we already learned the hard way.
This talk moves beyond prompts and introduces the Agent Mesh — an asynchronous, event-driven communication layer designed to support enterprise-grade agent ecosystems. We’ll explore how proven distributed-system patterns apply to Agentic AI, and how an Agent Mesh enables decoupled collaboration, resilience, governance and scalable coordination across autonomous agents.
Attendees will gain a practical architectural blueprint for transforming experimental agent flows into robust, enterprise-ready AI systems.