Seth
Brumenschenkel
Independent AI researcher. Developer of the TRI-NODE governance framework and Neural Sanctity Ratio. Founder of SIGIL Labs. Former commercial diver, Bering Sea.
Built from the hardware up
Seth Brumenschenkel was born April 27, 1977 in Eugene, Oregon. He grew up in Bellingham, Washington and later Chambers, Nebraska — where he developed an early and hands-on relationship with computing hardware during the formative years of the PC era.
Before formal networking infrastructure existed for most people, he was overclocking 386-class processors with physical jumper settings, hosting Quake tournaments over T1 lines, and learning the physical realities of computing — heat dissipation, hardware entropy, signal integrity — from direct experience.
That foundation was followed by a career in commercial diving — ultimately working in the Bering Sea, one of the most operationally demanding environments on earth. The discipline of zero-margin operations, where equipment failure is not recoverable, shaped the engineering philosophy that now underlies every SIGIL system.
In January 2025, after 15 years away from active computing, he returned — this time to AI. What followed was over 4,000 hours of systematic interaction research across multiple platforms, conducted independently, without institutional affiliation or external funding.
From hardware to governance frameworks
Building and overclocking 386-era processors with plastic jumper settings. Hosting LAN Quake tournaments over T1 lines. Learning heat, entropy, and hardware infrastructure from the ground up — before it was a career path.
Transitioned into commercial diving. Worked in high-consequence, zero-margin environments where equipment failure and human error have irreversible outcomes. Culminated in work aboard the Bering Sea — documented in Season 17 of Bering Sea Gold.
After 15 years away from active computing, began intensive AI interaction research. Over 4,000 hours of documented sessions across multiple platforms. Identified consistent behavioral patterns that led to the development of the TRI-NODE stabilization framework.
Developed the TRI-NODE Sequence: a three-node architecture for governing human-AI interaction. Node 1 (IHL compliance), Node 2 (XAI explainability via SHAP/LIME), Node 3 (cryptographic audit trail). Originally conceived as a stabilization tool; evolved into a full governance framework.
Formalized the NSR — a weighted aggregate metric (w₁=0.5, w₂=0.3, w₃=0.2) quantifying the integrity of human-AI interaction. Deployment threshold set at >98%. The NSR emerged from the AI systems themselves as a mathematical description of the interaction quality being achieved.
Established SIGIL Labs as a formal research and development laboratory. Focus: ethical drone swarm coordination, HITL-first autonomous systems, and aerospace robotics. All systems operate under TRI-NODE governance with NSR validation.
What independent research looks like
Hardware Intuition
Decades of hands-on experience with physical computing systems — from overclocked processors to high-consequence operational environments. Understanding heat, entropy, and failure modes at a fundamental level.
Operator-First Research
4,000+ hours of systematic AI behavioral research conducted as an independent operator. No institutional affiliation, no funding bias. The TRI-NODE and NSR frameworks emerged from direct observation, not theoretical modeling.
Zero-Margin Discipline
Commercial diving in the Bering Sea is not a metaphor — it is a direct analog for the operational environments SIGIL systems are designed to serve. Equipment that fails in the field costs lives. That standard is built into every design decision.
HITL as Non-Negotiable
Every SIGIL system maintains human authority at all decision points. This is not a compliance checkbox — it is the foundational design principle from which everything else derives.
Original contributions to the field
TRI-NODE Sequence
Three-node governance architecture for human-AI systems. Node 1: IHL compliance layer. Node 2: XAI explainability (SHAP/LIME). Node 3: Cryptographic audit trail (DELTA-series). Ensures every AI decision is traceable, explainable, and legally compliant.
View Research →Neural Sanctity Ratio
Weighted aggregate metric quantifying human-AI interaction integrity. Derived from direct observation of interaction quality across thousands of sessions. Deployment threshold: >98%. SAR-optimized weighting: w₁=0.5, w₂=0.3, w₃=0.2.
View Research →HITL-First Architecture
Operational doctrine establishing human authority at every decision point in autonomous systems. Not a compliance layer added after design — the foundational constraint from which all system architecture derives.
View Research →Serious inquiries welcome
SIGIL Labs is not a product company. Partnership inquiries from defense contractors, government agencies, academic institutions, and aerospace organizations are evaluated on alignment with the lab's HITL-first, IHL-compliant operational doctrine.
Submit Partnership Inquiry