SAGA (Self-Adapting Generative Agent Architecture): A Unified Framework for Interface Obsolescence, Ambient Intelligence, and Autonomous Capability Expansion in AI Agent Systems

This paper by Unnat Bak (UB) introduces SAGA (Self-Adapting Generative Agent Architecture), a meta-framework describing how AI agents can autonomously detect the boundaries of their own capabilities and synthesize new, durable skill modules at runtime without human intervention, retraining, or fine-tuning. Nested within SAGA are two sub-frameworks: IOIA (Interface Obsolescence through Ambient Intelligence), which argues that graphical user interfaces represent a transitional and increasingly obsolete layer in human-computer interaction, and ARIA (Ambient Runtime Intelligence Architecture), which provides the concrete implementation blueprint for deploying interfaceless agents with persistent relational memory and dynamic capability expansion. Together, SAGA, IOIA, and ARIA constitute a unified theoretical and practical framework for the next generation of AI agent design. A domain-specific implementation within the franchise industry vertical is used as the grounding reference architecture throughout.