I'm a front-end engineer based in Seattle with over a decade of experience building high-scale web applications. My background spans UI systems, application architecture, and developer tooling.
Over the past six years at Amazon, I've contributed to products operating at significant scale, where performance, stability, and maintainability are fundamental constraints. My work has supported large-scale advertiser and customer experiences.
Alongside my work at Amazon, I design and develop independent AI-centric products and frameworks. These projects explore AI-native systems, human-in-the-loop workflows, agent architectures, and productivity tooling.
An AI-powered object generation service that treats LLM output as proposals requiring human approval before reaching your database. Users describe what they need in natural language, review the structured result, and approve, edit, or reject with feedback — closing the gap between LLM capability and production data quality.
A lightweight, modular AI agent framework designed for local LLMs. Supports hot-reloadable tools, providers, and config — the agent can update its own capabilities without restarting. Runs as an interactive CLI, Discord bot, or HTTP service with a React web UI, and supports sub-agent delegation, cron scheduling, and a built-in knowledge base.
A multi-platform AI-powered productivity app that turns goals into actionable schedules. Describe your goals in plain English and the AI generates tasks, proposes smart schedules, and tracks your progress with streaks and achievements — available on web, iOS, and desktop.