The ongoing shift of AI models from centralized cloud APIs to local AI agents on edge devices is enabling \textit{Client-Side Autonomous Agents (CSAAs)} -- persistent personal agents that can plan, access local context, and invoke tools on behalf of users. As these agents begin to collaborate by delegating subtasks directly between clients, they naturally form \emph{Agentic Peer-to-Peer (P2P) Networks}. Unlike classic file-sharing overlays where the exchanged object is static, hash-indexed content (e.g., files in BitTorrent), agentic overlays exchange \emph{capabilities and actions} that are heterogeneous, state-dependent, and potentially unsafe if delegated to untrusted peers. This article outlines the networking foundations needed to make such collaboration practical. We propose a plane-based reference architecture that decouples connectivity/identity, semantic discovery, and execution. Besides, we introduce signed, soft-state capability descriptors to support intent- and constraint-aware discovery. To cope with adversarial settings, we further present a \textit{tiered verification} spectrum: Tier~1 relies on reputation signals, Tier~2 applies lightweight canary challenge-response with fallback selection, and Tier~3 requires evidence packages such as signed tool receipts/traces (and, when applicable, attestation). Using a discrete-event simulator that models registry-based discovery, Sybil-style index poisoning, and capability drift, we show that tiered verification substantially improves end-to-end workflow success while keeping discovery latency near-constant and control-plane overhead modest.

翻译：人工智能模型正从集中式云API向边缘设备的本地AI代理转变，这一持续演进催生了**客户端自主代理（CSAAs）**——即能够代表用户进行规划、访问本地上下文并调用工具的持久性个人代理。当这些代理通过客户端间直接委托子任务开始协作时，便自然形成了**智能对等（P2P）网络**。与经典文件共享覆盖网络（其交换对象为静态的、哈希索引的内容，如BitTorrent中的文件）不同，智能覆盖网络交换的是**能力与行动**，这些对象具有异构性、状态依赖性，且若委托给不可信对等节点可能带来安全隐患。本文阐述了实现此类协作所需的网络基础框架。我们提出一种基于平面的参考架构，将连接/身份管理、语义发现与执行机制解耦。此外，我们引入签名的软状态能力描述符，以支持基于意图和约束感知的发现机制。为应对对抗性环境，我们进一步提出**分层验证体系**：第一层依赖信誉信号，第二层采用轻量级金丝雀挑战-响应机制与回退选择策略，第三层则需要包含签名工具收据/执行轨迹（在适用时还需验证报告）的证据包。通过使用离散事件模拟器对基于注册表的发现机制、Sybil式索引污染及能力漂移进行建模，我们证明分层验证能显著提升端到端工作流成功率，同时将发现延迟维持在接近恒定水平，并使控制平面开销保持在适度范围内。