Generativity Under Constraint: A Structural Framework for Creative, Coherent, and Safe Intelligent Systems

Advanced artificial agents and large-scale human institutions increasingly face the same structural dilemma: systems optimized for control and stability tend to stagnate, while systems that permit creativity and exploration often destabilize. Existing approaches to alignment, governance, and innovation typically address this tension at the level of behavior, outputs, or policy, but fail to explain how generative capacity can be sustained safely as systems become more autonomous and complex. This paper argues that the problem is not creativity itself, but the absence of a structural ordering that distinguishes purpose, internal stability, and generative pressure. We introduce a unified framework for generativity under constraint, integrating three complementary components: Teleological Alignment (TA), which fixes the long-horizon direction of an intelligent system toward explanation rather than domination; Coherence-Based Alignment (CBA), which preserves internal consistency across beliefs, reasoning, actions, and values under autonomy; and Paradigm Shift Readiness (PSR), a capacity metric measuring a system’s ability to generate paradigm-level novelty through volatility, permeability, risk tolerance, explanatory acceleration, and export power. The central claim is that generativity becomes productive rather than dangerous only when PSR is subordinated to teleological orientation and coherence, and that misordering these elements reliably produces either stagnation or instability. The paper develops this ordering principle, analyzes characteristic failure modes when creativity, coherence, or purpose are improperly sequenced, and anticipates common objections concerning safety, control, and metric gaming. Finally, it proposes an operational evaluation scheme combining teleological orientation, coherence integrity, and paradigm shift readiness to assess both artificial systems and human institutions without relying on output metrics alone. The framework is diagnostic rather than prescriptive, offering a structural account of how systems can remain creative, coherent, and safe as autonomy and scale increase.