Reflexive AI. A Canonical Definition

Modern AI systems increasingly rely on large, centralised, and resource-intensive models optimised for accuracy and representational power. While effective in many settings, these approaches introduce latency, cost, and fragility in environments characterised by real-time constraints, continuous change, and limited historical data. This document introduces Reflexive AI as a distinct paradigm for artificial intelligence systems designed to operate under such conditions. Reflexive AI emphasises immediacy, locality, and adaptive behaviour over deep abstraction, drawing inspiration from biological reflex mechanisms and decades of work in cybernetics, control theory, and adaptive systems. This text provides a canonical definition of Reflexive AI and situates it within the broader AI landscape.