I build systems, lead sales, and architect intelligence—because real impact requires all three.
Math-first AI systems architect for leaders who need both revenue and rigor.
And I apply these same architectural principles to design and scale high-performance enterprise sales teams.
Work with meAdvisory, architecture, and GTM support for AI systems that must work in production.
I build systems—technical systems, revenue systems, and AI architectures that behave predictably, scale cleanly, and can be explained mathematically.
What I'm Focused On
These aren't academic hobbies—they're the foundations I use to design systems that are fast, explainable, and commercially defensible.
Physics → Computers/AI
Using physics-grade thinking to design AI systems with provable behavior, not vibes-based heuristics.
Polymorphic/Neuromorphic Computing
Building architectures that can change shape with context, so your system adapts to real-world conditions instead of collapsing when the environment shifts.
Field-Based Computation
Designing memory, retrieval, and behavior as a single field-based system, so the AI is mathematically constrained instead of being a best-effort prompt stack.
Latest Thinking
Featured Articles
View All Articles →Agents 3.0: Deep Agents Need Deep Memory
publishedAgents 2.0 fixed coordination. Agents 3.0 fix memory. A field-native architecture where memory is state, the system is the agent, and models operate inside laws—not prompts.
AI Without Memory Is Not Intelligence
publishedWhy 'just add RAG' is not the same as giving a system memory, and what real machine memory would actually require.
The Architecture of Being a Father
publishedHow building resilient systems and raising resilient kids turn out to be the same design problem seen from two angles.
Proof of Work
Professional Proof Points
Credibility built through enterprise results and technical innovation.
Enterprise Operating Track Record
Large, complex environments where revenue, delivery, and long-term programs all had to line up.
AWS
Principal Account Director for MongoDB at AWS, driving hundreds of millions in cloud co-sell revenue, modernization programs, and regulated-industry transformations. Built repeatable enterprise sales motions for complex, regulated customers.
NTT / Dimension Data
Built, ran, and scaled enterprise sales engines delivering $100M+ public sector and Fortune 100 programs over multi-year cycles. Aligned complex delivery, services, and account strategy across teams and regions.
Math-First Systems & IP
Systems and methodologies I’ve designed from first principles to make AI behavior explainable and auditable.
Resonant Field Storage (RFS)
A 4-D field-based memory architecture designed for deterministic recall, energy budgeting, and explainable interference patterns—built as an alternative to traditional vector-only retrieval.
Mathematical Autopsy
A "math before code" methodology that forces invariants, error budgets, and failure modes to be defined and proven before any implementation is allowed to ship.
SmartHaus / AIVA / Execution Fabric
An execution fabric and assistant stack (SmartHaus, AIVA, and related systems) built on top of the same calculus—so every agent, pipeline, and workflow is traceable back to specific math, not just prompts.