Phase 2: Coordination & Agreement · ~75 minutes · Python (stdlib)

Theory of Mind and Emergent Coordination

Li et al. (arXiv:2310.10701) showed that LLM agents in a cooperative text game exhibit emergent high-order Theory of Mind (ToM) — reasoning about what another agent believes about a third agent's beliefs — but fail on long-horizon planning due to context management and hallucination.

Hiring signal: Can operate theory of mind and emergent coordination in production

Introduction

Riedl (arXiv:2510.05174) measured higher-order synergy across a population and found that only the ToM-prompt condition produces identity-linked differentiation and goal-directed complementarity; lower-capacity LLMs show only spurious emergence. That is, coordination emergence is prompt-conditional and model-dependent, not free. This lesson implements a minimal ToM-aware agent, runs a cooperative task with and without ToM prompting, and measures the coordination delta against the Riedl 2025 protocol.

Type: Learn + Build Languages: Python (stdlib) Prerequisites: Phase 16 · 07 (Society of Mind and Debate), Phase 16 · 17 (Generative Agents) Time: ~75 minutes

Objective

Learning objectives

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You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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Key terms in this lesson

Agent