Systems engineer. Sr. Technical Business Development Leader, Supply Chain at Amazon Robotics.
I'm a systems engineer with 15 years across aerospace, defense, and robotics — GE Aerospace, MORSE Corp, and Amazon. My work has spanned gas turbine development, safety-critical systems for the US Army, and scaling hardware products for warehouse robotics.
In March of 2026 I moved fully to an AI-native daily workflow. I enjoy exploring and collaborating on new AI applications to improve business processes and outcomes, challenging where bottlenecks have changed and opportunities exist.
My current focus is on making agent output measurably useful: data provenance, context curation, trust boundaries, and the evaluation and feedback loops needed to know whether a workflow is actually better than what it replaced.
Spec-first multi-agent development methodology. Three-layer context system, four agent personas, destructive-critique gate before any code is written.
Methodology · summer 2025
Monte Carlo engine that turns season-total fantasy projections into game-level distributions for custom-scoring auction drafts.
Python · ~10k LOC · summer 2025
Fantasy football auction draft helper. Won two leagues in 2025 by someone who watched two football games. Pure-core/impure-adapter architecture, paranoid draft-day persistence.
React · TypeScript · ~31k LOC · summer 2025
Data provenance, trust decay, context curation, and notes from applying GenAI to traditional engineering work.
Commentary on AI workflows, context engineering, and building with agents.