You’ve built a knowledge base. Why does AI still struggle with business problems?
Modeling methodology 01 | Domain × perspective × resolution
Methods & Practice
From understanding the business to making change happen
How to build business domain models, organize knowledge, and collaborate with AI. This section documents concrete methods, why each step is taken, and how to judge when enough has been done.
Business Modeling
How do you set the scope, identify objects, express rules, and decide when the model is sufficient?
From agent authorization to a digital twin of responsibilities
Modeling methodology 02 | Map tools and permissions to responsibilities so agents’ action boundaries can be defined, enforced, and governed.
Grounding Business Abstractions in Reality: Using Real Instances to Test and Refine Models
Modeling methodology 03 | Continually test business abstractions through instance mapping, boundary testing, and checks of terminology consistency across abstraction levels.
Related case studies
Why do people and AI still struggle as more equipment fields are added?Knowledge Organization & Human–AI Collaboration
How can documents and discussions become cognitive assets that can be continually referenced, checked, and reused?
From documents to computable cognitive assets
Organizing knowledge for human–AI collaboration with Cognitive IR.