AI-Powered No-Code UI Builder

Goal

Build a highly usable visual no-code UI builder platform that allows both technical and non-technical users to craft and deploy UI applications via visual flows, while ensuring high performance, scale, and maintainable code; also mentor team members and embed strong engineering practices.

Solutions

Platform & SDK Development

• Developed a modular, component-based front end using TypeScript & Next.js, enabling responsive design previews, drag-and-drop composition, and real-time visual feedback.
• Built backend services in Golang focusing on API performance, concurrency handling, and efficient data models to support large UI projects.
• Designed and delivered SDKs for Web and Flutter so that components and layouts could be reused across platforms, speeding up mobile/web product expansion.

AI & Automation Features

• Co-designed and implemented an image-to-UI conversion flow powered by GPT Vision + screenshot-to-DOM techniques: parsing layout structure, recognizing UI elements, and generating front-end code stubs.
• Added a conversational UI adjustment feature (via GPT-3.5) allowing users to do things like “make this section full width” or “align this text to center” through natural language, reducing manual tweaks.
• Iteratively refined prompt engineering, heuristics, and post-processing to improve accuracy; reduced manual corrections by ~30% (internal metric).

Engineering Excellence & Team Leadership

• Established and enforced coding standards, style guides, and linting rules to improve code consistency and readability.
• Set up CI/CD pipelines, test automation (unit & integration), and monitoring/logging (e.g. via Sentry) for early detection of regressions or performance issues.
• Mentored junior engineers: conducted code reviews, paired programming, and training workshops; guided junior devs to take ownership of small services/components.
• Led architectural discussions about component reuse, API design, infrastructure for scaling, and trade-offs between performance, development speed & maintainability.

Impact & Outcomes

• User-Facing Outcomes: Enabled non-technical users to build and deploy functional UI applications without writing boilerplate front-end/back-end code. Reduced time-to-prototype by ~60%.
• Scalability & Performance: Backend API latency dropped by ~40% through performance tuning, caching and optimized data access. Front-end and SDKs supported multiple screen sizes and platforms with low overhead.
• Quality & Reliability: Introduction of CI/CD, automated tests, and monitoring reduced bugs in shipping features by ~25% and increased deployment confidence.
• Team Growth & Efficiency: Standardized workflows and mentorship improved onboarding speed for new developers; junior devs progressed faster, taking on more complex tasks.
• Innovation Delivered: Launched novel AI-powered features (image-to-UI, conversational UI tweaks) that differentiated the platform; contributed unique IP and technical learnings in this space.