.NET AI Community Standup: Why Orleans for AI Agents

Bruno Capuano and Konstantin Semenenko explain why Microsoft Orleans is a strong fit for building AI agents in .NET, focusing on how the virtual actor model helps with stateful, long-running conversations and coordinating distributed workloads reliably at scale.

Overview

This .NET AI Community Standup session covers how Orleans can be used as a production-ready foundation for agent-based AI systems.

Key themes include:

Why Orleans maps well to AI agent systems

• Using the virtual actor model to represent agent-like components that think/act/collaborate.
• Supporting complex, stateful systems as AI apps evolve beyond single prompts.

Building scalable, reliable, stateful agent architectures

• Managing long-running conversations and preserving conversation state.
• Coordinating distributed workloads and orchestrating work across components.
• Simplifying state management for agent-based systems.

Architecture and operational considerations

• Common architectural patterns and design decisions for AI-driven applications.
• Operational considerations for running distributed AI workloads reliably in production.

Links

• https://learn.microsoft.com/en-us/collections/m2dqt7t0xz0yww?source=docs

Featuring

• Bruno Capuano: https://www.linkedin.com/in/elbruno
• Konstantin Semenenko: https://www.linkedin.com/in/ksemenenk0/