Case studies
Six of the 15+ projects I’ve shipped, newest first.
Problem
Guests who’d never held a club needed real, spoken coaching seconds after a swing, live at a launch event.
What I owned
The UI, the guest workflow, the coaching and the tests. Made sure it all worked together, on site through event night.
Result
191 guests coached across two bays in one night, each leaving with a personal recap video.
- Screenshot
- Classify
- Extract
- Verify
- Human review
- Production CRM
Problem
Casting submissions arrived as screenshots that had to be re-keyed into the client’s CRM.
What I owned
Everything: vision-LLM pipeline, review interface, multi-model evaluation, and a Chrome extension for full-page capture.
Result
Structured records
published to production after a person approves each one. Nothing is written unsupervised.
Problem
If proving falls behind, a rollup’s state can’t advance and blocks can’t finalize.
What I owned
Proof orchestration (NATS, Go, Rust prover), prover upgrades and rollouts, and the public release pipeline.
Result
Inception to
public mainnet as one of the first four engineers. Open-source publishing ~2.5× faster.
Problem
A four-person team had to get from an idea to a launched product, quickly.
What I owned
The product backend, plus a Node and TypeScript service template the team reused.
Result
#1 Product of the Day on Product Hunt, under a year from start. The template carried three more prototypes.
Problem
Merchants wanted their customer-visit insights and campaigns on their phones.
What I owned
Led the React Native app, its CI/CD and over-the-air updates. Built Go and Kafka services for WiFi presence data.
Result
Shipped to the
App Store and Google Play, on a pipeline serving 20,000 merchant locations.
Problem
Everyday productivity apps on a new mobile platform had to feel instant on 2013 hardware.
What I owned
Release-defining features in the Notes and Tasks apps, in C++ and Qt on BlackBerry 10, then on Android.
Result
List scrolling held at
~60 fps, earning a Performance Champion award. Both apps now have
1M+ downloads each on Google Play.
How I work
Decisions in writing
Specs, decision logs and API docs your team can review, and keep after I leave.
Measure, then change
Eval harnesses and tuning runs before a prompt, model or threshold changes.
Safe to ship
Human review before production writes. Staged rollouts with a rollback ready.
Remote, AI-assisted
Remote since 2019. Coding agents for speed; people make the calls and review what ships.
Also: Mattermost’s Incident Response plugin, now Playbooks. I wrote its REST API spec and bootstrapped the Go plugin API.
Open source: xerrors-ts, and Next.js, Flask and Rails SDKs for an API-monitoring product.
Gemini Golf Coach
Screenshot-to-CRM pipeline
Zircuit
Macro
Zenreach (now Adentro)
BlackBerry