Conversational Multi-Agent
Two or more agents converse turn by turn, each playing a distinct role, until a completion criterion fires — natural fit for tasks that converge through dialogue.
Intent & Description
🎯 Intent
Have agents converse turn by turn until a completion criterion fires, with agent roles driving the conversation forward.
📋 Context
Some tasks naturally shape like dialogue between two or more specialists: a coder and a reviewer revising a patch, a teacher and a student working through an explanation, a writer and an editor. The work converges through back-and-forth rather than a single agent’s monologue.
💡 Solution
Define agents with system prompts and allowed actions. Implement a conversation manager that selects which agent speaks next (round-robin, condition-based, model-decided). Each agent reads the conversation and emits a turn. Continue until a termination criterion fires (task complete, max turns, explicit handoff to user).
Real-world Use Case
- The task naturally maps to dialogue between roles (e.g. user-proxy and assistant, planner and executor).
- A conversation manager can pick the next speaker by rule, condition, or model decision.
- Termination criteria (task complete, max turns, explicit handoff) are easy to express.
Source
📌 TL;DR
Agents with distinct roles take turns in a shared conversation until a completion criterion fires — the simplest and most natural shape for peer collaboration.
Advantages
- Natural way to model peer collaboration with clear role definition per agent.
- Each agent has a clean, inspectable role that’s easy to reason about in isolation.
Disadvantages
- Conversation drift is real — agents can gradually lose track of the original goal over many turns.
- Hard to formally verify correctness of the multi-agent flow as a whole.