Skip to main content
Back to Blog
Dev · 1 min read

Microsoft Agent Framework Hits RC: Multi-Agent Orchestration Goes Production-Ready

Microsoft merges Semantic Kernel stability with AutoGen patterns into an open-source SDK for building production multi-agent systems.

microsoft agent-framework multi-agent semantic-kernel autogen sdk

What Happened

Microsoft released the Release Candidate of its Agent Framework, unifying Semantic Kernel’s enterprise-grade reliability with AutoGen’s multi-agent orchestration patterns into a single open-source SDK. It supports sequential, concurrent, handoff, and group-chat agent composition patterns with built-in streaming. Both .NET and Python are supported, targeting the full spectrum from experimentation to production deployment.

Background

Microsoft has been running two parallel multi-agent projects: Semantic Kernel (enterprise-focused, deeply integrated with Azure) and AutoGen (research-oriented, flexible orchestration). The Agent Framework RC merges the best of both — Semantic Kernel’s production hardening and AutoGen’s compositional patterns.

The four orchestration patterns are significant:

  • Sequential: Agent A → Agent B → Agent C (pipeline processing)
  • Concurrent: Agents A, B, C run simultaneously (parallel analysis)
  • Handoff: Agent A delegates to Agent B based on context (specialization)
  • Group chat: Multiple agents discuss and converge (collaborative reasoning)

These patterns cover the vast majority of real-world multi-agent architectures.

What This Means for Developers

This is likely to become the default SDK for enterprise multi-agent development, similar to how React became the default for web UIs. Key reasons:

  1. Azure integration: Deep ties to Azure AI services give it an enterprise distribution advantage
  2. Dual language support: .NET and Python cover most enterprise stacks
  3. Production-ready: RC status means Microsoft is committing to stability guarantees

If you’re building multi-agent systems, evaluate this framework before rolling your own orchestration layer.

Actionable Insight

Clone the repo and implement the “handoff” pattern with two agents: one that analyzes code quality and hands off to another that writes tests for flagged functions. This exercise teaches the core orchestration concepts while producing a genuinely useful development tool. Start with Python — the examples are more complete.

Comments

Chat