Technical Depth

Skills organized by delivery responsibility.

I present my skills by the parts of a system I can own: backend services, frontend UI, mobile clients, AI/data prototypes, deployment, and workflow automation.

01 / Stack Matrix

Engineering stack

Backend

Spring Boot, Flask, FastAPI, Node.js, REST APIs, role-based flows, business workflow modeling.

JavaSpring BootPythonFastAPIFlaskNode.js

Frontend

Business UIs, admin panels, dashboards, React/Vite interfaces, Vue 3 apps, and data-heavy workflows.

ReactVue 3TypeScriptViteElement Plus

Mobile and Mini Programs

WeChat Mini Program flows, HarmonyOS ArkUI apps, role-specific mobile interactions, and lightweight service apps.

WeChat Mini ProgramHarmonyOSArkUIArkTS

Data and AI Prototypes

Python data collection, speech-learning prototypes, model-service interfaces, edge-AI experiments, and graph-ready architecture.

PythonWeb CrawlerWhisper-readyNeo4j-readyEdge AI

Database and Permissions

MySQL, SQLite, Redis, SQL initialization scripts, data-scope isolation, multi-role access, and finance/order data flows.

MySQLSQLiteRedisSQL ScriptsRBAC

Delivery and Automation

Deployment notes, smoke checks, manual QA records, handoff docs, Cloudflare Pages deployment, and Word/Visio automation.

Cloudflare PagesQA DocsPowerShellWord COMVisio OLE
02 / AI Coding Workflow

How AI fits into my engineering process

1

Requirement decomposition

I use AI to accelerate requirement sorting, but I still define roles, entities, states, and acceptance criteria manually.

2

Implementation and debugging

I use AI coding tools for scaffolding, iteration, refactoring, and bug investigation while keeping architecture decisions explicit.

3

Verification and delivery

I care about smoke checks, manual QA notes, deployment guides, and handoff materials so the project is usable after coding ends.