AutoGen vs LangChain

Choose AutoGen if…

Best for developers building multi-agent systems that need iterative back-and-forth reasoning between agents, and its edge is the human proxy pattern makes it straightforward to build supervised, not fully autonomous, multi-agent workflows. Strong for complex research and coding tasks, now in maintenance mode, check whether the AG2 fork better fits new projects. Lean toward LangChain instead if composable chains, agents, and memory abstractions that cut LLM app code from hundreds of lines to dozens matters more for your use case.

Choose LangChain if…

Best for developers building custom applications on top of large language models, and its edge is composable chains, agents, and memory abstractions that cut LLM app code from hundreds of lines to dozens. The standard starting framework for LLM app development, expect the API to keep shifting under you. Lean toward AutoGen instead if the human proxy pattern makes it straightforward to build supervised, not fully autonomous, multi-agent workflows matters more for your use case.