Exploring how software development is evolving into knowledge development in practice — where curated knowledge is refined through AI-assisted modeling and documentation, and software emerges as part of that evolving body of knowledge.
The knowledge processing model in SimpleModeling is structured as a transformation pipeline: “meaning → structure → definition → behavior → execution → reality.” Context governs the entire pipeline, and reality emerges through the evaluation of effects.
2026-04-27
1.5hop+ is a knowledge graph exploration approach that constructs concept neighborhoods based on semantic structure rather than fixed traversal distance. By leveraging CML/UML metamodel structures, it provides sufficient semantic context for generative AI, balancing accuracy and efficiency.
2026-03-23
In this article, we reorganize the processes of knowledge activation, assimilation, expression, promotion, and circulation that occur when using generative AI, and clarify how human/organizational knowledge creation connects with AI-based knowledge generation. Our objective is to redraw the knowledge-creation spiral for the AI era, centered on the two-layer structure of AI tacit knowledge and the Body of Knowledge.
2025-11-24