ABOUT · POSITIONING

Boyan Chuang — AI applications, product engineering and system integration

Boyan Chuang (莊柏彥, GitHub boyam01) is an AI Application & Product Engineer based in Taiwan. Current focus: AI Application, Product Engineering and System Integration. I break vague requirements into verifiable flows, then build them out through API, data, permissions, deployment and real operations. Six production operations systems delivered during an internship, plus a merged open-source upstream contribution.

EXPERIENCE
6 production operations systems · open-source upstream contribution
FOCUS
AI Application · System Integration · Product Engineering
EDUCATION
2026 · BBA Information Management, Tamkang University

Works · Method

Work and how I work

Six production operations systems (internship)

All six systems are live: tutoring courses, summer registration, an enterprise operations dashboard, a LINE assistant, cross-venue workforce scheduling and five-pool schedule integration. The work spanned requirement planning, feature development, mobile UI, permissions and security, performance, data recovery and day-to-day operations.

See the six systems and my scope →

WorldMonitor open-source contribution

PR #6937 merged upstream: aligned the self-hosted Redis proxy with the commands the news digest actually issues, and added a command-parity regression test. The record shows reading an existing architecture, locating the gap and landing the fix upstream — it is not a claim of ownership over the project.

See WorldMonitor PR #6937 ↗

University capstone project

What The 髮 was a four-person capstone. I covered backend features, GitHub collaboration and technology selection, and worked on the mobile information hierarchy and layout. The team's project was exhibited and received an Honorable Mention in the Information Application category.

See the capstone and my role →

Focus · Next

Current focus and next steps

Current focus: AI Application, Product Engineering and System Integration — especially turning a vague requirement into a verifiable flow, then building it out through API, data, permissions, deployment and real operations.

Next: push delivery toward stable, documented, verifiable work that someone else can pick up — and move AI from assisted development into production applications, with public engineering evidence for agents, tool calling, RAG, permissions and human approval, evaluation, tracing and failure handling. Not just having used them.

The WorldMonitor contribution is one concrete rep of that: read the existing data flow and command design, reproduce the gap in a self-hosted setup, then protect the fix with a regression test. I will keep comparing the constraints and maintenance cost of different open-source architectures so technology choices come with reasons.


Skills · Tools

Technologies and tools I have used

Compiled from real projects, prototypes and dev environments. Familiarity varies — used is not the same as mastered.

Frontend & interaction
  • Astro
  • React 19
  • React Native
  • Expo
  • TypeScript
  • JavaScript
  • HTML
  • CSS
  • Vite
  • Wouter (routing)
  • TanStack Query
  • Tailwind CSS
  • shadcn/ui + Radix UI
  • React Hook Form + Zod
  • Framer Motion
  • Recharts
Backend & API
  • Node.js
  • Express
  • Python
  • REST API
  • WebSocket (ws)
  • Passport (local)
  • express-session + connect-pg-simple
  • Helmet + express-rate-limit
  • LINE Bot / LIFF
Data & integration
  • Drizzle ORM
  • PostgreSQL (Neon serverless / pg)
  • MongoDB + Mongoose
  • MySQL
  • Redis
  • Ragic
Build, test & tools
  • esbuild
  • tsx
  • Vitest
  • Drizzle Kit
  • Docker Desktop
  • Git
  • GitHub / GitHub Desktop
  • Postman
  • MongoDB Compass
  • Anaconda
  • Cloudflare Workers
Delivery quality & operations
  • Responsive layout
  • Git / GitHub
  • Automated testing
  • Permission & data-flow audits
  • Performance diagnosis
  • Backup & recovery
  • Queues & monitoring

How This Site Works

How this site works

This site is a static build: once the GitHub main branch passes the build and link checks, Cloudflare Workers Static Assets serves dist/. No server-side rendering, no database, and deliberately no client-side router — so the public CV does not depend on a machine at home staying online.

Project pages are content-driven. Adding a project means adding one content file; the layout code does not change, and status, stack and licence all live in that same file instead of being scattered around.

The rules that keep it maintainable are not a verbal agreement — they are files versioned alongside the code:

AGENTS.md
Change rules: what may be touched, what needs approval first, what counts as done.
ARCHITECTURE.md
Architectural decisions and their reasons, including the deliberate non-goals.
DESIGN_SYSTEM.md
Design tokens, layout rhythm and prohibitions.
DEPLOYMENT.md
Deployment steps, post-deploy verification and rollback procedure.

Contact

Contact

Email works for collaboration or questions; code, issues and version history live on GitHub. Either channel reaches me directly.