agent frameworks
for Python automation teams
CrewAI vs AutoGen: which is better for Python automation teams?
TL;DR for Python automation teams
CrewAI offers a lightweight DSL for orchestrating multi-agent crews, while AutoGen provides a fuller-featured, Microsoft-backed framework for complex agent conversations.
Key Differences
| Feature | CrewAI | AutoGen |
|---|---|---|
| Abstraction level | CrewAI approach | AutoGen approach |
| Learning curve | Steeper, complex | Gentler, accessible |
| Tool and plugin ecosystem | CrewAI approach | AutoGen approach |
| Observability | CrewAI approach | AutoGen approach |
| Hosting options | CrewAI approach | AutoGen approach |
| Community backing | CrewAI approach | AutoGen approach |
Pricing Snapshot
Both open source under permissive licenses; operational cost comes from the LLMs you call (2025-10-13)
Last reviewed: 2025-10-13
CrewAI
Choose CrewAI if:
- You want quick declarative workflows
- You prefer minimal boilerplate
- You like opinionated defaults
Pros
- + Declarative multi-agent workflows
- + Task routing and role assignment
- + Built-in memory and tool integrations
- + Supports OpenAI and OSS models
- + MIT-licensed open source
Cons
- - Python-only today
- - Requires orchestration expertise
- - Limited enterprise SLAs
- - API surface still evolving
AutoGen
Choose AutoGen if:
- You need enterprise integrations
- You want fine-grained control over chats
- You require advanced memory modules
Pros
- + Flexible multi-agent orchestration
- + Rich tool and function calling support
- + Supports human-in-the-loop supervision
- + Works with Azure OpenAI and OSS models
- + Microsoft-backed open source
Cons
- - Configuration complexity
- - Heavy dependency footprint
- - Verbose debugging output
- - Requires Python runtime
Also Consider
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