Key takeaways
- AutoGen pioneered multi-agent orchestration patterns now adopted across the industry
- Microsoft is merging AutoGen with Semantic Kernel into unified Microsoft Agent Framework
- 50.4k GitHub stars and 559 contributors make it one of the most popular agent frameworks
FAQ
What is AutoGen?
AutoGen is Microsoft's open-source framework for building multi-agent AI applications that can act autonomously or work alongside humans.
Is AutoGen still being maintained?
Yes, AutoGen receives bug fixes and security patches, but new features are being developed in Microsoft Agent Framework instead.
What is Microsoft Agent Framework?
Microsoft Agent Framework is the successor to AutoGen, combining AutoGen's multi-agent orchestration with Semantic Kernel's enterprise readiness in a unified SDK.
How does AutoGen compare to LangChain?
AutoGen focuses on multi-agent orchestration and conversation patterns, while LangChain provides broader LLM application development tools. AutoGen pioneered patterns like agent debate and group chat.
Can I use AutoGen in production?
Yes, but Microsoft recommends evaluating Microsoft Agent Framework for new projects, as it offers better enterprise features like observability, compliance hooks, and long-running durability.
Executive Summary
AutoGen is Microsoft's open-source framework for building multi-agent AI applications, pioneering conversation-based orchestration patterns that are now widely adopted across the industry. In 2026, Microsoft announced the merger of AutoGen with Semantic Kernel into Microsoft Agent Framework, signaling a strategic shift toward unified enterprise-ready agent development.
| Attribute | Value |
|---|---|
| Company | Microsoft |
| Founded | 2023 |
| Funding | Microsoft-backed |
| Employees | Microsoft Research |
| Headquarters | Redmond, WA |
Product Overview
AutoGen is a framework for creating multi-agent AI applications that can act autonomously or collaborate with humans. It pioneered the multi-agent orchestration paradigm that has since been adopted by many other frameworks in the space.
The framework uses a layered architecture with clear separation of concerns:
Key Capabilities
| Capability | Description |
|---|---|
| AgentChat API | High-level API for conversational multi-agent applications |
| Core API | Event-driven programming for scalable multi-agent systems |
| Extensions | First and third-party components for external services |
| AutoGen Studio | No-code GUI for prototyping multi-agent workflows |
| MCP Support | Model Context Protocol integration for tool discovery |
Product Surfaces / Editions
| Surface | Description | Availability |
|---|---|---|
| autogen-agentchat | Python package for conversational agents | GA |
| autogen-core | Event-driven runtime for distributed agents | GA |
| autogen-ext | Extensions for LLM clients, code executors | GA |
| AutoGen Studio | Web-based no-code interface | GA |
| .NET SDK | Cross-language support via NuGet | GA |
Technical Architecture
AutoGen implements a layered, extensible architecture designed for both experimentation and production use.
Languages: Python 3.10+, .NET
Key Technical Details
| Aspect | Detail |
|---|---|
| Deployment | Self-hosted, containerized, cloud |
| Model(s) | OpenAI, Azure OpenAI, Anthropic, Google, local models |
| Integrations | MCP servers, Docker code execution, gRPC distributed runtime |
| Open Source | Yes (MIT License) |
Orchestration Patterns
AutoGen supports multiple agent orchestration patterns:
- Sequential — Step-by-step task execution
- Concurrent — Parallel agent work
- Group Chat — Collaborative agent brainstorming
- Handoff — Dynamic responsibility transfer
- Magentic — Manager-coordinated task ledger
Transition to Microsoft Agent Framework
Microsoft announced in 2026 that AutoGen and Semantic Kernel are merging into Microsoft Agent Framework. This unified framework combines:
- AutoGen's multi-agent orchestration capabilities
- Semantic Kernel's enterprise-ready connectors and observability
- Support for MCP, A2A (Agent-to-Agent), and OpenAPI standards
- Graph-based workflow orchestration
Impact on Current Users:
- AutoGen will continue receiving bug fixes and security patches
- No significant new features will be added to AutoGen
- Migration guides are available for transitioning to Microsoft Agent Framework
Strengths
- Pioneer in multi-agent orchestration — Introduced patterns like agent debate, group chat, and handoff that are now industry standard
- Microsoft backing — Corporate resources, research depth, and enterprise integration path
- Mature codebase — 50.4k stars, 559 contributors, 98 releases, 3,776 commits
- Cross-language support — Both Python and .NET SDKs with consistent APIs
- No-code option — AutoGen Studio allows prototyping without writing code
- Clear upgrade path — Microsoft Agent Framework provides enterprise-ready migration target
Cautions
- Transition uncertainty — Active development shifting to Microsoft Agent Framework creates adoption hesitation
- Enterprise features limited — Observability, compliance hooks better in successor framework
- Learning curve — Multiple API layers (Core, AgentChat, Extensions) can be confusing
- Long-running durability gaps — Production workloads better served by Microsoft Agent Framework
- Community fragmentation risk — Split attention between AutoGen and Microsoft Agent Framework
Pricing & Licensing
| Tier | Price | Includes |
|---|---|---|
| Open Source | Free | Full framework (MIT License) |
| Azure Integration | Azure costs | Azure OpenAI, AI Foundry hosting |
Licensing model: Open source (MIT) with optional Azure services
Hidden costs: Azure OpenAI API costs, compute for self-hosting, potential migration costs to Microsoft Agent Framework
Competitive Positioning
Direct Competitors
| Competitor | Differentiation |
|---|---|
| LangChain/LangGraph | LangChain focuses on LLM app development; AutoGen specializes in multi-agent conversation |
| CrewAI | CrewAI offers simpler role-based agents; AutoGen provides more orchestration patterns |
| LlamaIndex | LlamaIndex excels at RAG/documents; AutoGen focuses on agent orchestration |
| Mastra | Mastra is TypeScript-native; AutoGen is Python/.NET with Microsoft ecosystem |
When to Choose AutoGen Over Alternatives
- Choose AutoGen when: You need proven multi-agent patterns with Microsoft ecosystem integration
- Choose Microsoft Agent Framework when: Starting new projects requiring enterprise observability and durability
- Choose LangChain when: You need broader LLM development tools and integrations
- Choose CrewAI when: You want simpler role-based agent teams with less complexity
Ideal Customer Profile
Best fit:
- Microsoft-centric enterprises evaluating agent frameworks
- Researchers exploring multi-agent orchestration patterns
- Teams with existing Semantic Kernel or Azure investments
- Developers wanting both Python and .NET support
- Organizations planning to migrate to Microsoft Agent Framework
Poor fit:
- Teams needing production-ready enterprise features today (use Microsoft Agent Framework)
- Organizations avoiding Microsoft ecosystem
- TypeScript-first development teams
- Projects requiring immediate long-running workflow durability
Viability Assessment
| Factor | Assessment |
|---|---|
| Financial Health | Strong — Microsoft-backed |
| Market Position | Transitioning — Moving to Microsoft Agent Framework |
| Innovation Pace | Slowing — New features in successor framework |
| Community/Ecosystem | Large — 50k+ stars, active Discord |
| Long-term Outlook | Evolving — Future is Microsoft Agent Framework |
AutoGen's market position is unique: it pioneered multi-agent orchestration but is now being absorbed into Microsoft Agent Framework. The strategic consolidation with Semantic Kernel signals Microsoft's commitment to a unified agent development story.
Bottom Line
AutoGen is a foundational framework that defined modern multi-agent orchestration patterns. Its merger into Microsoft Agent Framework represents maturation rather than abandonment — the innovations live on in a more enterprise-ready package.
Recommended for: Researchers, existing AutoGen users, and teams evaluating the Microsoft agent ecosystem before committing to Microsoft Agent Framework.
Not recommended for: New production projects requiring enterprise durability, observability, and compliance from day one — those should start with Microsoft Agent Framework.
Outlook: AutoGen's patterns and community will persist through Microsoft Agent Framework. Expect AutoGen maintenance mode while innovation shifts to the unified framework. Watch for enterprise adoption announcements of Microsoft Agent Framework as the true measure of success.
Research by Ry Walker Research • methodology