This whitepaper introduces XChronos, a unified conceptual and technical framework for modeling the temporal structure of experience in both human consciousness and self-improving artificial intelligence (AI) systems. Moving beyond linear time, XChronos proposes a four-layer architecture: Chronos: External, operational, linear time (e.g., timesteps, episodes) Chronons: Minimal units of lived experience, marked by internal change Hexacronons: Recurrent patterns linking non-adjacent Chronons, enabling cross-temporal generalization Metacronon: Structural phase transitions involving deep reorganization of the cognitive system The framework is both philosophically grounded and technically specified, with formal detection criteria (e.g., policy change thresholds ‖Δπ‖ > ε, similarity metrics sim(Vᵢ, Vⱼ) > λ). It is validated through case studies involving modern AI systems such as DeepMind's SIMA 2 and generative environments like Genie 3, demonstrating its ability to explain phenomena like strategy reuse, behavioral coherence, and meta-learning leaps. XChronos serves as a cross-disciplinary protocol applicable in: AI and reinforcement learning Cognitive science and phenomenology Analytical psychology (e.g., synchronicity) Organizational development and creative processes Autopoietic systems and world models This work bridges previously disconnected fields—philosophy, computer science, and cognitive psychology—offering a common vocabulary and measurable standards for the evolution of intelligent systems, whether biological or artificial.