# AutoGen vs CrewAI

> AutoGen is in maintenance mode, and Microsoft points new users to Microsoft Agent Framework, its successor built by the AutoGen and Semantic Kernel teams. For a new multi-agent project, choose CrewAI if you want an actively developed Python framework with role-based crews and Flows, or Microsoft Agent Framework if you are a .NET or Azure shop. Keep existing AutoGen systems running and plan a migration.

|  | AutoGen | CrewAI |
| --- | --- | --- |
| Project status | Maintenance mode; no new features, community managed, successor is Microsoft Agent Framework | Actively developed with frequent releases |
| Core idea | Agents that converse with each other, such as group chats and two-agent loops | Crews of role-based agents with assigned tasks, orchestrated by Flows |
| Strongest pattern | Open-ended conversational collaboration, debate and code-writing agents | Structured pipelines of specialists, sequential or with a manager agent |
| Languages | Python and .NET | Python |
| Low-code option | AutoGen Studio for prototyping agent teams | Crew Studio inside the CrewAI AMP platform |
| Managed deployment | None; you host it | CrewAI AMP, in the cloud or on-premise |
| Upgrade path | Official migration guide to Microsoft Agent Framework | Stays on CrewAI |
| License | Open source (MIT for code) | Open source (MIT); AMP is a commercial platform |

## Choose AutoGen if

- You already run AutoGen in production and it is stable, so keep it while you plan a migration
- You are researching conversational multi-agent patterns where agents debate or critique each other
- Your team needs .NET, in which case start with Microsoft Agent Framework, AutoGen's successor

## Choose CrewAI if

- You are starting a new multi-agent project in Python
- The work splits cleanly into specialist roles and tasks
- You want an actively maintained framework with a managed deployment option
- You want Flows to keep agent autonomy inside a predictable process

## The short version

This comparison changed in late 2025. Microsoft moved AutoGen into maintenance mode and named Microsoft Agent Framework as its successor. AutoGen still works and its ideas remain useful, but it no longer gets new features.

So the practical question is no longer AutoGen or CrewAI. It is CrewAI or Microsoft Agent Framework for new work, and when to move existing AutoGen systems.

## Where AutoGen still wins

**Conversational multi-agent research.** AutoGen made agent-to-agent conversation easy: group chats, critic and writer pairs, and agents that write and run code together. For exploring how agents can collaborate on open-ended problems, its patterns are clear and well documented.

**.NET support.** AutoGen has Python and .NET packages. CrewAI is Python only. For .NET teams, though, the forward-looking choice is Microsoft Agent Framework, which also supports .NET.

**Existing systems.** If an AutoGen deployment works and is tested, there is no emergency. Keep it running, pin versions, and schedule a migration with the official guide.

**AutoGen Studio.** Its low-code interface is still handy for prototyping agent teams before writing code.

## Where CrewAI wins

**Active development.** CrewAI ships regularly and its documentation, examples and integrations keep pace with new model capabilities. That matters for anything you will run for years.

**A clear mental model.** Agents have a role, goal and backstory. Tasks have owners and expected outputs. Processes run sequentially or under a manager agent. Business stakeholders can read a crew definition and understand it.

**Flows for control.** CrewAI Flows wrap crews in event-driven state, branching and loops. You keep autonomy where it helps and predictability everywhere else.

**Deployment.** CrewAI AMP deploys, monitors and scales crews in the cloud or on-premise, with Crew Studio for no-code building.

## What we recommend

Do not start new production work on AutoGen. For a Python team building role-based agents, use CrewAI. For a team on .NET or deep in Azure and Microsoft Foundry, use Microsoft Agent Framework. If the process needs explicit state and approvals, also consider LangGraph ([CrewAI vs LangGraph](/compare/crewai-vs-langgraph/)).

Many projects need fewer agents than they first assume. A single well-designed agent often beats a crew on cost and reliability. See [the cost of a multi-agent system](/cost/cost-of-multi-agent-system/) for budgets, or [start a conversation](/start/) about migrating an AutoGen system.

## Frequently asked questions

### Is AutoGen deprecated?

AutoGen is in maintenance mode. Its repository states that it will not receive new features or enhancements and is community managed going forward, and it tells new users to start with Microsoft Agent Framework. Existing AutoGen code keeps working, but you should not start new production work on it.

### What is Microsoft Agent Framework?

Microsoft Agent Framework is the direct successor to both AutoGen and Semantic Kernel, built by the same teams. It combines AutoGen's agent abstractions with Semantic Kernel's enterprise features and adds graph-based workflows. It supports .NET and Python, with Go in preview, and works with Microsoft Foundry, Azure OpenAI, OpenAI, Anthropic and other providers.

### What is AG2?

AG2 is a separate, community-driven fork of AutoGen led by some of its original creators. It continues independent development under its own name. It is not the same project as Microsoft's AutoGen or Microsoft Agent Framework, so check which one any tutorial or library is referring to.

### Should I migrate from AutoGen to CrewAI or to Microsoft Agent Framework?

If your stack is Microsoft, .NET or Azure, Microsoft Agent Framework is the shortest path and has an official migration guide. If you are Python-first and your agents map well to roles and tasks, CrewAI is a strong option. Either way, keep the existing system running until the new one passes the same test cases.

### Is CrewAI better than AutoGen?

For new projects today, CrewAI is the safer choice because it is actively developed. AutoGen's conversational design is still a good fit for research and exploratory agent teams, but its maintenance status means fewer fixes and no new capabilities.

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Source: https://www.lumeor.studio/compare/autogen-vs-crewai/
Published by Lumeor Studio, Newtown, PA. hello@lumeor.studio. Get a written scope: https://www.lumeor.studio/start/