Automated Semantic Onboarding of Reasoning Objects Across AI Models

This article presents a formal demonstration of Automated Semantic Onboarding, showing how structured reasoning objects can be generated, internalized, and compared across multiple AI models, including Grok Code Fast 1, Chat GPT-5 mini, and Claude Sonnet 3.5. Using a controlled Tic Tac Toe domain, the work illustrates model-agnostic, reproducible, and auditable reasoning, operationalized through a domain-specific language (DSL). Key contributions include cross-model reproducibility, explainable AI by construction, and a framework for universal reasoning substrates. Researchers can reference this work for methods, results, and insights into structured, transferable reasoning workflows across heterogeneous AI systems.