I build and own production software end to end, from the data model to the interface, in education and health — domains where being wrong is expensive.
I work spec-first: define what correct means, then build the automated verification that lets AI coding agents move fast without lowering the bar.
Build member-facing features across web and mobile for a health and longevity platform: lab results, personalized protocols, prescriptions, and care-team coordination.
Work with member health data and prescription workflows, where correctness and auditability matter more than raw speed.
Turn lab results into metrics members can track and act on over time.
Technical lead on Triangulator, an enterprise platform that automates how universities evaluate transfer credit, replacing manual review with ranked suggestions that staff approve, adjust, or reject with a reason.
Designed and built the learning-management-system integration for Orchard, ASU's customizable-assignment platform: single sign-on and automatic grade sync, including the failure paths for when a grade does not post.
Reworked the backend of ASU Earned Admissions, where learners earn credit toward admission to ASU degree programs, and built its enrollment data sync and a new program opt-in flow.
Rebuilt payment processing for Study Hall, the learning platform ASU runs with the Study Hall YouTube channel, cutting failed payments and making the flow safe to change. Also built interactive features for Sun Devils, ASU's athletics site.
Quarterly recognition award — 2024 Q1, 2024 Q2, 2024 Q3–Q4, and 2025 Q1
Freelancing
2020–2022
Software Engineer
Delivered custom websites and web applications for small businesses, from scoping through launch and handoff.
Owned the client relationship alongside the code: requirements, timelines, and post-launch support.
Start from the spec. Before anything is built I pin down what the change must do and how we will know it works. A clear spec is what makes work safe to delegate, to a teammate or to an AI agent.
Make verification automatic. Every requirement that matters becomes a check a machine runs on every change, so correctness never depends on someone remembering to look.
Let the pipeline decide. Nothing ships without passing continuous integration, no matter who or what wrote it. Agents draft; the pipeline is the gate.
Own the outcome. Agents take on the repeatable work. The judgment and the accountability stay with me: if something wrong ships, it is mine.
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Proof, not promises
These figures come from GitHub, not from me. Read them as throughput rather than heroics: much of this work is done with AI coding agents, so the graph reflects the method as much as the hours. The method is the part worth judging.
Contribution period
18,681contributions2025-10-12 → 2026-10-12
Last 12 months: 18,681 contributions across 349 active days.
349 active days · longest streak 76 days · busiest day 686
17,318contributions2026-01-01 → 2026-10-12
2026: 17,318 contributions across 278 active days.
278 active days · longest streak 76 days · busiest day 686
5,823contributions2025-01-01 → 2025-12-31
2025: 5,823 contributions across 316 active days.
316 active days · longest streak 50 days · busiest day 85
3,677contributions2024-01-01 → 2024-12-31
2024: 3,677 contributions across 301 active days.
301 active days · longest streak 30 days · busiest day 88
2,962contributions2023-01-01 → 2023-12-31
2023: 2,962 contributions across 265 active days.
265 active days · longest streak 27 days · busiest day 54
LessMore
GitHub contribution heatmap. Each square is a day; darker is more. 18,681 contributions in the last 12 months.
18,681Contributions (12mo)
76Longest streak (days)
84Public repos
Live data from the GitHub API at build time · 2026-10-12 · verify on GitHub
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About
I'm a full-stack software engineer based in Phoenix, AZ. I take features from idea to production and stay responsible for them once they are live.
My work has been in education technology and health software: university platforms for transfer credit, admissions, and coursework, and tools that help people act on their health data. Both are domains where being wrong is expensive and quiet, which shapes how I build.
I work spec-first. Before anything is built I write down what correct looks like, then turn it into automated checks that run on every change. That is what lets me hand real work to AI coding agents and still vouch for the result.
A background in mathematics and statistics keeps me honest on the data-heavy parts.
TypeScript
React
Postgres
Tailwind
WebSockets
Bun+1
Node.js
SQLite