Скачать или смотреть LangGraph vs AutoGen vs CrewAI (2025) – Which Agent Framework Wins?

LangGraph vs AutoGen vs CrewAI (2025) – Which Agent Framework Wins?

If you're exploring LangGraph, AutoGen, or CrewAI for building multi-agent AI systems in 2025, this video provides an in-depth comparison of their features, performance, and suitability for various use cases. Whether you're a developer, researcher, or enterprise architect, this guide will help you determine which framework best fits your needs.

In this video you will learn:

Overview of LangGraph, AutoGen, and CrewAI

Architectural differences and design philosophies

Developer experience and ease of use

Performance benchmarks and scalability

Memory management and state handling

Tool integration and extensibility

Security and safety features

Community support and documentation

Best use cases for each framework

Final verdict and recommendations

Q: What are the key differences between LangGraph, AutoGen, and CrewAI?

A: LangGraph offers a graph-based approach with modular workflows and fine-grained control, making it suitable for complex, structured tasks. AutoGen focuses on conversational agent architectures, emphasizing natural language interactions and dynamic role-playing, ideal for flexible, conversation-driven workflows. CrewAI adopts a role-based model, emphasizing team-like collaboration among agents, which is effective for hierarchical and sequential task execution.