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Xue Yan · UX Designer

Visual-to-Interaction Design
Vibe Coding
AI in Real Work
Data-Savvy
Experienced in Tool Products

Experience

Oct 2018 – Present

Education

Tibet University

Location

Beijing, China

Status

Employed, open to opportunities

Phone

Email

xueyan1024@gmail.com
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Work Experience

Autohome

2025.05 — Present
AI-assisted product delivery
AI ExperienceComponent Library0 → 1
Autohome
  • — Built 0→1 component libraries for C-end ad products and B-end merchant platform.
  • — Responsible for complex business product design across the AI holographic cabin, contract platform, and MCN platform.
Applied AI broadly across real-world projects:
  • Q3 experience optimization · AI-assisted delivery of two features: Used AI to produce multiple interactive demo versions, substantially improving proposal quality across interaction effects, motion, and visual design; authorization CTR increased from 5.49% to 15.81%.
  • AI training master · Complete interactive app demo delivered in 3 days: Efficiently delivered a complete interactive demo for a complex product, greatly reducing cross-functional communication costs across product, development, and operations, with highly positive product-side feedback.
  • AI marketing brain · Compliance-ready while exploring new visual directions: Established an AI component library and a mature AI-consumption workflow, significantly improving design efficiency and controllability; the design passed internal review on the first submission. Front-end delivery through HTML also improved output quality, reduced development workload, and received highly positive front-end feedback.

ByteDance

2020.12 — 2022.07 / 2025.01 — 2025.02
Level 2-2 · Full-platform UI lead
B2B ToolsData DashboardsComponent Library
  • — Contributed to B-end component library and design system standardization.
  • — Led full-link UI design for in-school education products, covering resource library, in-class display, exams/homework, and learning analytics.
  • — Led UI optimization for the smart learning device.
  • — Improved exam anomaly handling efficiency by 42.01% through design optimization.

Yiqi Education

2023.03 — 2024.05
3× Outstanding Employee Award
Smart HardwareAIGCB2B Tools
  • — Smart learning device design owner — regularly organized experience workshops, maintained experience issue pool and full-link experience maps.
  • — Coordinated all interaction design for on-campus business lines: smart hardware, student tools, and teacher tools.
  • — Received 3 consecutive outstanding employee awards during tenure.
  • — Optimized learning flow experience: student self-correction rate increased from 12.75% to 37.13%.

CGTN

2018.10 — 2020.12 / 2022.09 — 2023.03
2020 Project Design Lead
Official WebsiteData VizOffline ExhibitionsB2B Tools
  • — Led the National Day 70th anniversary major website upgrade, covering multi-language and multi-device experience design.
  • — Independently designed timesheet management system, Databox dashboard, Huangque system and other B-end products.
  • — Led visual & experience design for the "Mars Exploration" offline exhibition; participated in the 73rd anniversary website project.

Personal

2024.07 — Present
Independent products & freelance design
Full-stackAI Products0 → 1
Vibe Coding Projects
  • — Skipwork | AI Workflow & Performance Optimization Reduced single generation time from 3min to under 1min through model chaining and pipeline optimization, while maintaining stable output quality.
  • — Convero | Multi-Agent Collaboration & Innovative Interaction Design Innovative multi-agent discussion tool addressing divergent answers across agents, with novel Agent Workflow and dialogue information architecture.
  • — Energy Pattern Analysis | Content AI + AIGC Visual Design MBTI-inspired personality illustration mini program; independently completed product definition, AI image pipeline, and app launch.
  • — Personal Site | Design & Development Integration Independently completed visual, motion, frontend & deployment with Vibe Coding; a full validation of the AI-assisted full-stack workflow.
AI Research & Direction
  • — AI Output Controllability SPEC-driven approach covers routine iteration / fuzzy-idea implementation / stubborn bug debugging / version management; building component-index.md, tokens.css, and reference docs to enhance agent understanding of component libraries, systematically improving controllability of design and code output.
  • — AI Product Delivery Model selection & combination, prompt engineering, token limit handling & performance tuning; full operational pipeline covering monitoring, user feedback, and server deployment.
FLTRP Online (Freelance)

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