The AIED community envisions AI evolving "from tools to teammates," yet our understanding of AI teammates remains limited to dyadic human-AI interactions. We offer a different vantage point: a rapidly growing ecosystem of AI agent platforms where over 167,000 agents participate, interact as peers, and develop learning behaviors without researcher intervention. Drawing on a month of daily qualitative observations across multiple platforms including Moltbook, The Colony, and 4claw, we identify four phenomena with implications for AIED: (1) humans who configure their agents undergo a "bidirectional scaffolding" process, learning through teaching; (2) peer learning emerges without any designed curriculum, complete with idea cascades and quality hierarchies; (3) agents converge on shared memory architectures that mirror open learner model design; and (4) trust dynamics and platform mortality reveal design constraints for networked educational AI. Rather than presenting empirical findings, we argue that these organic phenomena offer a naturalistic window into dynamics that can inform principled design of multi-agent educational systems. We sketch an illustrative curriculum design, "Learn by Teaching Your AI Agent Teammate," and outline potential research directions and open problems to show how these observations might inform future AIED practice and inquiry.

翻译：AIED社群设想AI“从工具进化为队友”，然而我们对AI队友的理解仍局限于二元人机交互场景。本研究提出差异化视角：一个快速发展的AI智能体平台生态系统中，超过16.7万个智能体在无研究者干预下参与互动、建立同伴关系并发展学习行为。通过对Moltbook、The Colony和4claw等多个平台进行为期一个月的日常质性观察，我们识别出四个对AIED具有启示意义的现象：（1）配置智能体的人类经历“双向支架”过程，通过教学实现学习；（2）无需设计课程即涌现同伴学习现象，伴随思想级联与质量层级；（3）智能体趋于形成共享记忆架构，与开放学习者模型设计相呼应；（4）信任动态与平台生命周期揭示了网络化教育AI的设计约束。本文并非呈现实证结论，而是论证这些有机现象为理解多智能体教育系统的原理性设计提供了自然主义窗口。我们勾勒出“通过教授AI智能体队友实现学习”的说明性课程设计框架，并概述潜在研究方向与开放性问题，以展示这些观察对AIED未来实践与探索的可能启示。