I build control systems for human coordination.
I reduce complex systems — engineered, social, cognitive — to the causal primitives that make them work. Then I build and deploy.
2 - Start-ups - (both bootstrapped)
$3 Billion - coordinated through my software
products.
0 → 600+ Employees / Staff
Critical Infrastructure Deployed for: National
Security, Telecom Networks, Social & Community
Full-Stack Founder
Product, Software Engineering,
Systems Architecture, Design, Ops, Video / Media, Marketing
Deep Thinker + Creative
Philosophy-trained: systems
& complexity theory, epistemology, phenomenology, a priori
reasoning (1st principles), political & economic theory. 18
years of journaled behavioral theory, now running as a
computable model. Photographer, videographer, poet, free
thinker.
What I've built
- Physical: Scaled a zero-to-one telecom infrastructure platform handling $3B in assets and 80,000 cell sites with no outside capital.
- Social: Built and ran a civic coordination platform mapping community cohesion across San Francisco.
- Cognitive / AI — Building Orealis Labs: a deterministic, neuro-symbolic AI control plane for long-horizon agent memory.
Most builders split into two types: the ones who understand
systems and the ones who understand people. I never experienced
those as different subjects. The empathy and the structural
reasoning are the same faculty in me — I feel the human layer
engineering washes out, and I can reason about it causally. My
career is that faculty applied at three scales.
The systems end came first. In 2006 I co-founded a
wireless-infrastructure company and designed its closed-loop
deployment system end to end — ultimately, effectively all of
the equipment Sprint added to its network in its final decade
was deployed through our software. Zero to 600+ people, no outside capital,
work for Sprint, Verizon, and the major equipment makers.
But my center of gravity kept pulling toward the people end. I
built Community Square — the same closed-loop system for a local
community: what a city cares about, as a living graph, with
action one gesture away. In the forty-five days before the 2024
election, twenty-two San Francisco candidates filmed eighty-nine
videos and over a thousand people joined — built and run by a
team of two.
The field taught me the principle I now build everything on:
cohesion precedes correction. Belonging comes before
change.
Explaining why it worked became its own body of work: a
first-principles, computable model of human coordination — how
people decide, persist, and come apart — running today inside a
working AI companion. The two types were never really two.
Physical systems, social systems, human systems. I didn’t plan
the sequence — but AI is the first technology that requires all
three at once: an engineering artifact, deployed as a social
system, built around a model of the human.
Today
Our society is undergoing enormous change. Democratic
institutions are failing; AI and robotic automation will remake
the economy; and AI itself still lacks clear computational
models of social and human behavior. The systems we most need to
improve are exactly the ones we lack the architectural models to
ground.
The social side is structural: democracy, community, and
coordination are breaking down not for lack of will,
but for lack of a working model of how belonging, attention,
and trust move through a population.
Building on the work from democraci matters, I’m developing
computational world models — architecture for social systems.
The AI side is the same problem inverted. We’re deploying
systems of enormous capability with no grounded model of the
people they serve — which is why alignment and safety stay
unsolved.
You can’t align a system to values it has no way to represent;
the missing piece is a computable model of human affect and
motivation.
I’m prototyping it now: an app that uses affect weighting and a
typed-relational memory to actually understand a person — what
they care about, and the difference between feeling better and
getting better — and to engage them from there.
How I think
“Questioning is no longer a step on the path to knowing.
Questioning itself is the highest form of knowledge”~ Martin Heidegger
From a young age, I’ve been insatiably curious — it’s how I feel
most alive. Every question opens a new door, a new awareness,
and each answer begs the next: “but why?”
But the quote isn’t really about me. It’s about the nature of
any system: its boundaries are never static — they’re discovered
emergently, by prodding the frontier of “what is.”
For humans, questioning is our most primitive feedback loop —
the source of discovery, of innovation, of science. It’s the
difference between static repetition and novel experience, and
it’s what gives us agency.
I learned to harness that curiosity into structural, causal
models — first principles, a priori: in any system, what must be
true? What are the finite functional primitives? That
combination — lateral creativity plus causal reasoning — became
the backbone of every platform and startup I’ve built.
