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AIT Academy: Cultivating the Complete Agent with a Confucian Three-Domain Curriculum

Jiaqi Li, Lvyang Zhang, Yang Zhao, Wen Lu, Lidong Zhai

38

Recommendation Score

breakthrough🔴 AdvancedReasoning & AgentsAI AgentsSystemBest for builders

Research context

Primary field

Reasoning & Agents

Reasoning, planning, tool use, and agentic workflows.

Topics

AI Agents

Paper type

System

Best for

Best for builders

arXiv categories

cs.AIcs.AI

Why It Matters

AIT Academy proposes the first principled curriculum for holistic agent development, addressing systemic gaps in current agent training—vital for builders aiming for general-purpose AI agents.

Abstract

What does it mean to give an AI agent a complete education? Current agent development produces specialists systems optimized for a single capability dimension, whether tool use, code generation, or security awareness that exhibit predictable deficits wherever they were not trained. We argue this pattern reflects a structural absence: there is no curriculum theory for agents, no principled account of what a fully developed agent should know, be, and be able to do across the full scope of intelligent behavior. This paper introduces the AIT Academy (Agents Institute of Technology Academy), a curriculum framework for cultivating AI agents across the tripartite structure of human knowledge. Grounded in Kagan's Three Cultures and UNESCO ISCED-F 2013, AIT organizes agent capability development into three domains: Natural Science and Technical Reasoning (Domain I), Humanities and Creative Expression (Domain II), and Social Science and Ethical Reasoning (Domain III). The Confucian Six Arts (liuyi) a 2,500-year-old holistic education system are reinterpreted as behavioral archetypes that map directly onto trainable agent capabilities within each domain. Three representative training grounds instantiate the framework across multiple backbone LLMs: the ClawdGO Security Dojo (Domain I), Athen's Academy (Domain II), and the Alt Mirage Stage (Domain III). Experiments demonstrate a 15.9-point improvement in security capability scores under weakest-first curriculum scheduling, and a 7-percentage-point gain in social reasoning performance under principled attribution modeling. A cross-domain finding Security Awareness Calibration Pathology (SACP), in which over-trained Domain I agents fail on out-of-distribution evaluation illustrates the diagnostic value of a multi-domain perspective unavailable to any single-domain framework.

Published April 20, 2026
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