<![CDATA[The high administrative burden in developing lesson plans poses a significant challenge to teacher efficiency. Although Generative Artificial Intelligence technology offers potential solutions, its adoption is often hampered by general system outputs that are not structured in accordance with curriculum regulations. This study aims to develop a precise and applicable AI-based learning plan generator using a Design-Based Research approach. The novelty of this study lies in its multimodal development method, which integrates visual-to-code interface conversion, the use of structured data templates, and the injection of a national curriculum knowledge base. The research procedure consists of five phases of the DBR cycle, from problem analysis to design reflection. The results show that the developed system is capable of automatically generating planning documents that include components of identification, learning design, learning experiences, and assessment in accordance with the Ministry of Education and Culture guidelines. The ecological validity of the product was proven through the implementation phase in a real context, where 141 independent access transactions were recorded through the digital distribution platform. The high level of user adoption, including through paid schemes, indicates that this product has high practical value and relevance as a solution for teacher administrative efficiency in the era of digital transformation.]]>
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