"Knowledge Protocol Engineering" (KPE), proposed by the team of Zhang Guangwei and Deng Rui from the School of History at Shaanxi Normal University in China, provides a key paradigm breakthrough for AI for Humanities, especially historical research. It moves beyond past approaches of simply "feeding data" to AI (such as RAG—Retrieval-Augmented Generation) or giving it a set of "general tools" (through Agents), toward systematically injecting "research methodology."
This paradigm aims to design historians' tacit workflows (such as the thought processes of authentication, verification, and analysis) and procedural knowledge (such as analytical standards for specific types of documents) into explicit "protocols" that AI can strictly execute. This enables a general large language model to engage in structured, step-by-step logical reasoning under the constraints and guidance of protocols, thereby avoiding the instability and unreliability issues of traditional AI assistants, making behavior transparent and interpretable. The research team recognized from the practical failures of building historical source analysis agents that in professional fields, endowing AI with "discipline" and "method" is more important than merely giving AI "freedom." KPE transforms expert "craft" into reproducible, scalable "procedures." This not only constructs research assistants that truly understand academic standards but also profoundly advances the research process from a "craft" model dependent on individual experience toward a new research science of human-AI collaboration with programmable methods.