Project access points: case studies, systems, and AI-native builds
PixelCollab is a realtime collaborative whiteboard where users can create a room, share a link, and draw together instantly
Full-stack realtime product engineer: UI/UX, collaborative canvas, WebSocket transport, CRDT sync, presence, and interaction polish / live
A project concept for turning feature requests into structured execution plans: task decomposition, AI-agent routing, implementation prompts, test suggestions, and delivery checkpoints.
AI Engineer, system designer, orchestration workflow architect / case study
A production-minded personal portfolio built to present work with stronger technical context: Astro SSR, structured content, metadata strategy, and a GitHub-backed CMS workflow.
Product design, frontend architecture, content modeling, and deployment setup / live
A side project that turns free-game discovery into an automated notification pipeline: scheduled GitHub Actions, SMTP delivery, GitHub Pages registration, repository_dispatch, and PR-based subscriber updates.
Node.js automation engineer, GitHub Actions workflow designer, CI/CD and registration-flow architect / live
Instead of hiding unfinished work, I keep the next AI-native systems visible. These are the builds I want to turn into deeper case studies around AI-assisted delivery and engineering leverage.
QUEUE-001
A PR analysis workflow that summarizes change risk, highlights refactor opportunities, and generates structured review output before human approval.
PR analysis, risk detection, refactor guidance, review automation
QUEUE-002
A system for tracking agent-assisted feature delivery, code review status, testing progress, and deployment readiness across one delivery pipeline.
AI orchestration, delivery visibility, CI gating, execution control
QUEUE-003
A case study around tracing prompt flows, task execution, and review checkpoints inside an AI-assisted engineering stack.
Prompt tracing, logs, QA checkpoints, workflow reliability