Specification-Driven Intelligence (SDI)

This paper introduces Specification-Driven Intelligence (SDI), a paradigm for working with generative AI systems in which authority, intent, and responsibility reside in a human-authored specification rather than in the AI system itself. SDI reframes generative AI as an interpreter of explicit constraints, not an autonomous author or decision-maker. The specification defines intent, sequencing, epistemic posture, preservation requirements, non-claims, and failure boundaries. AI outputs are valid only insofar as they remain structurally compliant with the declared specification, preserving auditability and accountability. The paper situates SDI as a response to the probabilistic and context-sensitive nature of modern AI systems, where ad hoc prompt engineering lacks reproducibility and clear responsibility boundaries. A concrete example is provided through the Hoffman–Joyce Continuum (HJC), demonstrating how complex natural-language specifications can function as executable constraints without delegating judgment or authorship to the AI. SDI does not claim to solve alignment or eliminate human oversight. It proposes a narrower shift: treating specifications as the primary locus of intelligence and generative AI as an execution environment operating under explicit constraint.