ClawNet: Human-Symbiotic Agent Network for Cross-User Autonomous Cooperation

2026-04-21

AI Summary

This work addresses the lack of infrastructure and governance mechanisms for secure multi-user collaboration among AI agents. It proposes a human–machine symbiotic agent paradigm that constructs a collaboration network with humans as nodes, enabling autonomous coordination across user-owned agents through the ClawNet framework. The core innovations include a hierarchical identity architecture that decouples management agents from contextual identities, a scoped authorization mechanism, and operation-level accountability logging. A central coordinator enforces consistent identity binding, access control, and end-to-end auditability throughout the system. This design represents the first realization of a controllable and traceable secure collaboration system supporting multiple users and their respective AI agents.

Technology Category

• Multiagent Systems: Coordination and Collaboration
• Humans and AI: Human-AI Collaboration / Human-AI Teaming
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

Current AI agent frameworks have made remarkable progress in automating individual tasks, yet all existing systems serve a single user. Human productivity rests on the social and organizational relationships through which people coordinate, negotiate, and delegate. When agents move beyond performing tasks for one person to representing that person in collaboration with others, the infrastructure for cross-user agent collaboration is entirely absent, let alone the governance mechanisms needed to secure it. We argue that the next frontier for AI agents lies not in stronger individual capability, but in the digitization of human collaborative relationships. To this end, we propose a human-symbiotic agent paradigm. Each user owns a permanently bound agent system that collaborates on the owner's behalf, forming a network whose nodes are humans rather than agents. This paradigm rests on three governance primitives. A layered identity architecture separates a Manager Agent from multiple context-specific Identity Agents; the Manager Agent holds global knowledge but is architecturally isolated from external communication. Scoped authorization enforces per-identity access control and escalates boundary violations to the owner. Action-level accountability logs every operation against its owner's identity and authorization, ensuring full auditability. We instantiate this paradigm in ClawNet, an identity-governed agent collaboration framework that enforces identity binding and authorization verification through a central orchestrator, enabling multiple users to collaborate securely through their respective agents.

Problem

• cross-user collaboration
• AI agent governance
• identity binding
• multi-agent systems
• human-symbiotic agents

Innovation

• human-symbiotic agents
• cross-user collaboration
• identity governance
• scoped authorization
• action-level accountability