为大模型智能体设计可验证的可信协议，解决高风险领域中的信任问题。
From Cloud-Native to Trust-Native: A Protocol for Verifiable Multi-Agent Systems
- 在智能体底层嵌入身份验证、策略承诺与防篡改日志机制
- 实现跨组织跨司法管辖区的合规自治，避免事后审查
- 适用于医药研发、法律自动化等强监管场景
随着大语言模型驱动的自主智能体在医药、法律等高风险领域广泛应用，挑战已从智能转向可验证性。我们提出 TrustTrack 协议，将可验证身份、策略承诺和抗篡改行为日志直接嵌入智能体基础设施，构建新型系统范式：可信原生自治。通过将合规性作为设计约束而非事后监督，该协议重构了智能体在多组织、多司法管辖区间的运作方式。本文阐述协议设计、系统需求及在医药研发、法律自动化、AI 原生协作等受监管领域的应用案例。我们认为，从云到 AI，再到智能体，最终走向可信的演进路径，是未来自主系统的关键架构层。
原文摘要 · Abstract (English)
As autonomous agents powered by large language models (LLMs) proliferate in high-stakes domains -- from pharmaceuticals to legal workflows -- the challenge is no longer just intelligence, but verifiability. We introduce TrustTrack, a protocol that embeds structural guarantees -- verifiable identity, policy commitments, and tamper-resistant behavioral logs -- directly into agent infrastructure. This enables a new systems paradigm: trust-native autonomy. By treating compliance as a design constraint rather than post-hoc oversight, TrustTrack reframes how intelligent agents operate across organizations and jurisdictions. We present the protocol design, system requirements, and use cases in regulated domains such as pharmaceutical R&D, legal automation, and AI-native collaboration. We argue that the Cloud -> AI -> Agent -> Trust transition represents the next architectural layer for autonomous systems.
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