Group Chat and Speaker Selection

AutoGen GroupChat and AG2 GroupChat share one conversation across N agents; a selector function (LLM, round-robin, or custom) picks who speaks next. This is the archetype of emergent multi-agent conversation — agents do not know their role in a static graph, they just react to the shared pool. AutoGen v0.2's GroupChat semantics were preserved in the AG2 fork; AutoGen v0.4 rewrote it as an event-driven actor model. Microsoft put AutoGen into maintenance mode in February 2026 and merged it with Semantic Kernel into Microsoft Agent Framework (RC February 2026). The GroupChat primitive survives in both AG2 and Microsoft Agent Framework — learn it once, use it everywhere.

Learn + Build 1 hr Python (stdlib)

Prerequisites: Phase 16 · 04 (Primitive Model)

#Problem

Static graphs (LangGraph) are great when the workflow is known. Real conversations are not static: sometimes the coder asks the reviewer, sometimes the researcher, sometimes the writer. Hardcoding every possible handoff produces an edge explosion. You want agents reacting to a shared pool, with some function deciding who talks next.

That is exactly what AutoGen GroupChat does.

#Problem

Keep going. The rest of this lesson is one step away.