AI agents are rapidly expanding in both capability and population: they now write code, operate computers across platforms, manage cloud infrastructure, and make purchasing decisions, while open-source frameworks such as OpenClaw are putting personal agents in the hands of millions and embodied agents are spreading across smartphones, vehicles, and robots. As the internet prepares to host billions of such entities, it is shifting toward what we call Open Agentic Web, a decentralized digital ecosystem in which agents from different users, organizations, and runtimes can discover one another, negotiate task boundaries, and delegate work across open technical and social surfaces at scale. Yet most of today's agents remain isolated tools or closed-ecosystem orchestrators rather than socially integrated participants in open networks. We argue that the next generation of agents must become Agentic Citizens, defined by three requirements: Agentic-Web-Native Collaboration, participation in open collaboration networks rather than only closed internal orchestration; Agent Identity and Personhood, continuity as a social entity rather than a resettable function call; and Lifelong Evolution, improvement across task performance, communication, and collaboration over time. We present Synergy, a general-purpose agent architecture and runtime harness for persistent, collaborative, and evolving agents on Open Agentic Web, grounding collaboration in session-native orchestration, repository-backed workspaces, and social communication; identity in typed memory, notes, agenda, skills, and persistent social relationships; and evolution in an experience-centered learning mechanism that proactively recalls rewarded trajectories at inference time.

翻译：人工智能智能体在能力与规模上正迅速扩展：它们现在能编写代码、跨平台操作计算机、管理云基础设施、做出购买决策，而像OpenClaw这样的开源框架正将个人智能体普及至数百万用户，同时具身智能体正在智能手机、车辆和机器人中广泛部署。随着互联网即将承载数十亿这样的实体，它正在转向我们所谓的开放智能体网络——一个去中心化的数字生态系统，其中来自不同用户、组织和运行环境的智能体可以相互发现、协商任务边界，并在开放的技术与社会面上大规模委派工作。然而，当前大多数智能体仍作为孤立工具或封闭生态系统编排器存在，而非开放网络中具有社会整合能力的参与者。我们认为，下一代智能体必须成为智能体公民，具备三项需求：智能体网络原生协作——参与开放协作网络而非仅限封闭内部编排；智能体身份与人格——作为社会实体具有连续性而非可重置的函数调用；以及终身进化——在任务性能、通信和协作能力上随时间持续提升。我们提出协同，这是一种面向开放智能体网络上持久、协作与进化型智能体的通用架构与运行时框架，将协作建立在会话原生编排、仓库驱动工作空间与社交通信之上；身份建立在类型化记忆、便签、议程、技能与持久社交关系之上；进化建立在以经验为中心的学习机制之上，该机制能在推理时主动检索并利用已获奖励的轨迹。