As generative artificial intelligence (AIGC) becomes increasingly integrated into the education sector, Educational stakeholders are seeking more capable and intelligent assistance system. Traditional teaching assistance systems provide relatively limited support for after-class learning and lack systematicity and specificity. The content generated by AI-assisted tools tends to be fragmented, making it difficult to meet students’ needs for personalized learning and continuous improvement. To address these issues, this paper designs and develops an intelligent educational assistance system based on AIGC. The system is centered around an AI Agent architecture, integrating user profile and local knowledge base technology to build a comprehensive system with adaptive learning capabilities and intelligent teaching support functions. The system consists of student, teacher, and management terminals, covering functions such as homework grading, exercise training, intelligent Q&A, and resource sharing. The system aims to improve students’ after-class learning outcomes and provide personalized learning path guidance. At the same time, it helps teachers improve teaching efficiency, reduce repetitive workloads, and promote the intelligent transformation of the teaching process.