About

I work on systems that need to remain credible under pressure.

Background

My background crosses protocol design, infrastructure, real-time machine learning, long-form writing, and formal research. What connects those domains is not résumé variety. It is a recurring problem: how do you preserve signal, coordination, and durable value when the surrounding environment becomes noisy, strategic, or adversarial?

I came into technical work through music. Long before I was thinking about threat models or distributed systems, I was thinking about counterpoint, tension and resolution, invariants, motion, and form. That training never disappeared. It still shapes how I approach engineering, research, and writing.

In practice, that has meant building privacy-preserving and adversarial systems, working on distributed ML and secure infrastructure, shipping latency-sensitive detection systems, and writing about verification collapse, synthetic media, money, sovereignty, and institutional drift. It has also meant originating the public properties, research programs, and knowledge infrastructure described on this site — AfterFiat, Eschatology Report, Capability Commons, GAMUT — each built from scratch rather than inherited or curated.

I am not interested only in software abstractions. I care about the systems households and communities actually depend on: power, water, shelter, repair, tools, local competence, and the transmission of usable knowledge. That concern is not theoretical. It shapes where I live, what I build, and what I teach. It sits directly behind Capability Commons. Public capability is not a side interest. It is part of the same broader architecture.

Background

  1. 2008–2013

    University of North Texas — B.M. Music Performance & Theory

    Bachelor of Music in Music Performance and Music Theory. Training in counterpoint, formal analysis, and composition that still shapes how I approach systems architecture.

  2. 2017–2019

    Rochester Institute of Technology — M.S. Computer Science

    Master's in Computer Science focused on statistical machine learning and functional programming. Published two peer-reviewed papers (ICAI, Bridges) on ML approaches to musical gesture and astrophysical sonification.

  3. 2019–present

    Defense ML & Secure Infrastructure

    Real-time edge inference for Navy sonar systems (<50ms on Jetson). Air-gapped distributed LLM fine-tuning across 128 GPUs.

  4. 2023–2025

    Protocol & Decentralized Infrastructure

    Blockchain storage protocols, mechanism design, incentive architecture. Contributed to systems generating ~$60M in protocol revenue.

  5. 2025–present

    Independent Research & Public Writing

    AfterFiat thesis on next-generation stores of value. Eschatology Report on AI, culture, and institutional drift. Agent systems, retrieval infrastructure, and knowledge architecture.

Published Research

  • Machine Learning Approaches for Musical Gesture Analysis and Composition

    International Conference on Artificial Intelligence (ICAI), 2019

  • Sonification of Black Holes: Mapping Astrophysical Data to Musical Structure

    Bridges: Mathematics, Music, Art, Architecture, Education, Culture, 2019

What I Work On

The visible work spans several domains, but they all feed the same deeper concern.

Protocols, Proofs & Incentives

Verification, mechanism design, privacy-preserving systems, and structures that remain legible under strategic behavior.

ML Infrastructure & Operational Systems

Distributed training, secure deployment, real-time inference, edge systems, and production workflows built for reality rather than theater.

Writing on Money, AI & Civilizational Systems

Long-form work on verification, synthetic media, coordination, repression, sovereignty, and durable value.

Knowledge Architecture & Public Capability

Platforms, schemas, retrieval systems, and teach-forward structures that help people move from information to action.

Music, Geometry & Formal Research

Research into sound, symmetry, lawful form, and the deeper structures that continue to shape how I think.

Principles

A few principles show up often enough that they function as a working philosophy.

Verification over posture

I trust proofs, receipts, clear mechanisms, and measurable behavior more than slogans, vibes, or borrowed prestige.

Operations over theater

I care about what survives contact with latency, logistics, budgets, adversaries, partial observability, and actual conditions of use.

Structure across domains

Engineering, writing, music, and research all become clearer when treated as problems of form: relation, motion, tension, invariants, and composition.

Public legibility matters

Serious work should survive scrutiny without becoming unreadable. Depth and clarity are not enemies.

Digital systems meet physical reality

Software eventually lands in bodies, homes, households, tools, grids, and institutions. I care about that full stack.

Current Focus

Right now the work is concentrated on three things: the AfterFiat thesis (a falsifiable test of when privacy, proofs, and compute may support monetary premium), Kardashev Labs — the research lab building open-source value-capture telemetry, bypass detection, and verification tooling that makes the thesis falsifiable — and selective architecture engagements where the problem is real and the wrong abstractions are expensive.

The thesis names what needs to be true. The lab builds the instruments that tell you whether it is holding.

Where to start

If you want shipped systems, start with Work. If you want the larger map, go to Projects & Labs. If you want to talk, reach out.

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