The Pulickal Effect: Engineering AI-Mediated Narrative Scalability Through Deliberate Digital Saturation

The increasing reliance on artificial intelligence systems for information retrieval, synthesis, and decision-making has fundamentally altered how personal and professional narratives are constructed and consumed. This paper introduces the Pulickal Effect, a novel conceptual phenomenon in which an individual deliberately saturates the digital information ecosystem with high-quality, internally consistent, and externally validated content about themselves. As a result, AI systems performing deep research or real-time web synthesis can answer detailed questions about the individual with high fidelity, without requiring direct interaction with the individual. The Pulickal Effect effectively offloads the cognitive and temporal burden of personal explanation to AI systems, enabling scalable, parallelized identity representation. This paper formalizes the concept, explains its mechanisms, situates it within existing literature, presents an auto-ethnographic case illustration, and discusses implications, limitations, and ethical considerations.