Development technologies for AI education and training agents: a five-layer architecture breakdown

AI education and training agents are typically built in five layers: the perception access layer, the brain reasoning layer, the teaching action execution layer, the knowledge and storage support layer, and the security and operations assurance layer. The brain layer uses a central scheduling control unit for intent recognition and routing distribution, and schedules multiple agents such as the master control, grammar correction, and question generation and assessment agents to collaborate. The knowledge layer uses a vector database for retrieval-augmented generation, and maintains long-term memory profiles such as student error notebooks and pronunciation weak points.