Phase 1: Topologies & Roles · ~60 minutes · Python (stdlib)

Group Chat and Speaker Selection

Shared-conversation orchestration puts N agents in one conversation; a selector function (LLM, round-robin, or custom) picks who speaks next.

Hiring signal: Can operate group chat and speaker selection in production

Introduction

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 GroupChat and AG2 GroupChat are the reference implementations: 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.

Type: Learn + Build Languages: Python (stdlib) Prerequisites: Phase 16 · 04 (Primitive Model) Time: ~60 minutes

Objective

Learning objectives

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Key terms in this lesson

Agent