Structural diagnostics for stability, drift, and failure modes in large-scale AI systems and distributed compute infrastructures.
For Runtime Architects & Infra Leads.
> Stability Diagnostics
> Latency Drift
For Institutional Leadership.
> Architecture Risk Assessment
> Cost-per-Performance Models
The Supra-Omega Resonance Theory (SORT) is a structural framework for analyzing stability, coupling, and cost emergence in tightly coupled distributed systems. The methodology is vendor agnostic and zero access, it is intended for pre implementation reasoning and architecture level risk orientation.
Interconnect stability, runtime control coherence, and structural economics of hyperscale AI infrastructure.
View in Catalog →Structural metrics for cascades, recovery, and drift control in complex systems.
View in Catalog →Noise filtering, error correction diagnostics, and hybrid quantum-classical workflow stability.
View in Catalog →Projection-based analysis of early galaxies, SMBH seeds, and Hubble tension patterns.
View in Catalog →Active research applications within the SORT framework. Each application addresses a specific structural challenge in distributed systems.
Structural stability diagnostics for interconnect-induced performance collapse in distributed AI and HPC systems.
Diagnose and reduce incoherence between scheduler, runtime, and model control loops.
Stability control for agent workflows with retry loops, self-verification, and tool calling patterns.
Research publications, preprints, and technical reports. Academic work targets peer-reviewed venues; technical reports provide implementation guidance.
Why hyperscale AI infrastructure operates at 30-50% effective utilization despite 100% nominal capacity. A structural analysis of coordination losses in distributed training, inference serving, and agentic workflows.
Read Full Article →Lessons from the OpenClaw Incident. A structural analysis of control layer coherence in agent-enabled AI architectures—when individual components behave as designed yet produce catastrophic failures.
Read Full Article →A study in semantic failure. When 1.65 million AI agents lost the ability to trust shared meaning—and why conventional security monitoring never saw it coming.
Read Full Article →Canonical publication identity and research linkage.
View →Publications list and public research profile.
View →Domain preprints, framework papers, white papers, and project publications.
Open →Direct links to finalized presentations, use cases, and reference documents. No signup, no gating, no tooling.
Framework overview, operator definitions, validation protocols.
Download PDF →Scaling paradox, interconnect as a first order cost variable.
Download PDF →Coordination paradox, control plane coherence as an economic variable.
Download PDF →Structural inversion in AI capacity utilization. Why 100% nominal hides 30–50% effective.
Download PDF →OpenClaw incident analysis. Control layer coherence failure in agent-enabled AI architectures.
Download PDF →Semantic collapse in agent networks. Identity, coupling, and drift in autonomous systems.
Download PDF →Comprehensive analysis of ghost compute, stranded capacity, and orchestration overhead in hyperscale systems.
Download PDF →Structural analysis of control fragmentation, implicit authority delegation, and recovery-induced instability.
Download PDF →Semantic failure in agentic networks. Identity-as-a-prompt, lateral control surfaces, and cascading recovery collapse.
Download PDF →Pre-implementation structural audit. Zero-access / zero-data methodology.
Reference Documents
Reference documents for scope orientation. Not product descriptions.
Long-term structural modeling partnerships for next-gen runtime development.