Definition: Microsoft multi-agent conversation framework where agents interact through messages with human-in-the-loop support.
— Source: NERVICO, Product Development Consultancy
What is AutoGen
AutoGen is a multi-agent framework developed by Microsoft Research that enables creating systems where AI agents interact with each other through structured conversations. Its conversational approach differentiates it from other frameworks: agents communicate by exchanging messages as human team members would. AutoGen supports human-in-the-loop integration, allowing people to intervene at critical points in the conversation between agents.
How It Works
AutoGen defines agents as conversational entities that can send and receive messages. The framework provides several predefined agent types: AssistantAgent (powered by an LLM), UserProxyAgent (which can execute code and represent the human user), and custom agents. Developers configure conversation patterns that determine how agents interact, including one-on-one, group, or chain conversations. Each agent can access tools, execute code in a sandbox, and maintain conversation memory.
Why It Matters
AutoGen’s conversational approach makes debugging and understanding multi-agent systems easier, since every interaction is recorded as a readable message. For teams that need to maintain human control over automated processes, the native human-in-the-loop capability is critical. This is especially relevant in domains like finance, healthcare, or legal, where autonomous decisions require human validation before execution.
Practical Example
An engineering team configures an AutoGen system with three agents to automate technical report creation. A planner agent defines the report structure, a researcher agent collects data from internal APIs, and a writer agent generates the content. When the report covers sensitive topics, the UserProxyAgent requests human approval before publishing, ensuring oversight at critical points in the flow.