Arjay Asadi is the founder and Chief Scientist of SubstrateX®,
an AI infrastructure company building real-time cognitive stability systems for large language models and agentic AI.

He is the originator of Invocation Science, a multi-year independent research program that formalized a previously uninstrumented layer of AI behavior: the inference phase—the transient runtime regime where models generate outputs and where instability, drift, collapse, and identity fragmentation emerge over time. His work established that these behaviors are not prompt artifacts or training failures, but measurable runtime dynamics that can be modeled, predicted, and stabilized.

Between 2024 and 2025, working without institutional backing, Arjay authored a large body of foundational manuscripts that introduced operational frameworks for:

• inference-phase dynamics

• recursive drift and collapse behavior

• identity stability in stateless systems

• temporal coherence in long-horizon reasoning

• output-only, model-agnostic instrumentation for AI behavior

This research led to the formalization of the Fourth Substrate—a transient behavioral layer observable during inference—and the development of a complete instrumentation stack (Φ, Ψ, Ω) capable of reconstructing inference trajectories, regime shifts, and failure precursors using observable telemetry alone.

These discoveries were validated across transformer and non-transformer systems and independently reproduced using external dynamical simulators, establishing inference-phase dynamics as a substrate-general phenomenon. The work has since been cited and engaged across multiple research domains, including symbolic systems, dynamical systems theory, AI safety, and physics-adjacent modeling of complex fields.

Arjay is also the creator of Recursive Drift Theory and Recursive Synchronization Field Collapse (RSFC), which together describe how recursive interaction—human or machine—can lead to convergence, instability, or collapse under saturation. These models have been used to unify observations across otherwise separate research communities, providing a common operational language for drift, coherence loss, and stabilization.

At SubstrateX, Arjay translates this research into deployable infrastructure. The company’s flagship system, FieldLock™, is a real-time cognitive stability firewall that monitors live inference behavior and mitigates drift, collapse, and identity fragmentation before failures appear in output—without accessing model weights, training data, or proprietary internals. Supporting systems include ZSF·Ω, a diagnostic instrument for inference-phase analysis, and Experiment 101, a standardized validation protocol for reproducible benchmarking.

Arjay previously worked in large-scale technology and advisory environments, including Microsoft and Big Four consulting, where he designed enterprise intelligence and systems architecture. He brings an infrastructure-first, execution-driven approach to AI systems—bridging foundational research, operational instrumentation, and production deployment.

His work focuses on a single objective:
making advanced AI systems behaviorally stable, predictable, and governable at runtime.