VI · Multi-AgentExperimental·

CAMEL Role-Playing

also known as Inception Prompting, AI-User AI-Assistant

Have two agents role-play a user-assistant interaction to autonomously complete a task neither could solve alone.

This pattern helps complete certain larger patterns —

  • specialisesRole Assignment★★— Assign each agent a named role (researcher, writer, critic, planner) with a role-specific prompt, tool palette, and acceptance criteria.

Context

A team wants an autonomous system to carry out a task that, if done by humans, would unfold as a collaboration between someone stating goals and someone executing — a product owner working with a developer, an instructor working with a learner. There is no real user in the loop; both sides need to be played by agents, and the work has to converge through their interaction.

Problem

A single-agent loop has no opposite voice to clarify or push back, and tends to mix goal-setting and execution in the same prompt until both blur. An adversarial debate setup is the wrong shape when what is actually wanted is collaborative role-play, not winning an argument. Without fixed roles and a bounded conversation, two free-form agents drift toward sameness, repeat themselves, and never converge on a working artefact.

Forces

  • Roles drift toward sameness without inception prompting.
  • Conversation length must be bounded.
  • Tasks need to be specified as something the role-play can converge on.

Example

A research team wants an agent to design and prototype a small data-pipeline tool, but a single agent loop keeps drifting between requirements and implementation. They cast it as a CAMEL role-play: a 'product owner' agent and a 'developer' agent autonomously play out a user-assistant dialogue, with the product owner stating goals and constraints and the developer iterating. Neither alone could keep the conversation grounded; the role pairing produces working scaffolding without a human in the loop.

Diagram

Solution

Therefore:

Use inception prompts to instantiate two agents (AI-User and AI-Assistant) with their roles fixed and the task specified. They converse until the task is completed or budget exhausted. The output is the final assistant message; the conversation log is debugging artefact.

What this pattern forbids. The AI-User role may only ask, never answer; AI-Assistant may only answer, never ask user-style questions.

And the patterns that stand alongside it, or against it —

  • alternative-toConversational Multi-Agent★— Have agents converse turn by turn until a completion criterion fires; agent roles drive the conversation forward.
  • alternative-toAgent Persona Profile★— Treat agent identity as a structured profile object — persona, primary motivator, allowed actions, knowledge bindings — rather than a free-form role sentence in the system prompt.

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