Flows+

Service
UX Design, AI-assisted creativity
Project Scope
Invention Design II
Year
2021
Further Information
Project Documentation
Flows+: Designing with AI, not against it
Overview

Flows+ is an innovative design tool concept that reimagines how UX/UI designers create and iterate on interface designs. It combines a structured design system foundation with intelligent, computer-assisted creativity to streamline the workflow. The vision for Flows+ is to let designers focus on user-centered creative decisions while the system handles repetitive tasks like generating style variations. By bridging the gap between design and development with a class-based style approach, Flows+ aims to let designers focus on high-level creative decisions while the system handled the routine grunt work of iteration.

Facts
  • Project Duration: 4 months
  • Team: Felix Reißner, Lucas Franz
  • Tools Used: Figma, Miro, Adobe Illustrator
  • Inspirations: Modern UI design tools and AI features, CSS Logic
My Impact
  • Research
  • Ideation
  • Design
  • Prototyping
Outcome

Flows+ is a concept for a next-gen UI design tool that combines creative freedom with systemized structure. Its class-and-container logic mirrors the clarity of CSS, enabling global design control and scalable consistency. The interface includes a live canvas, a modular component library, and a dynamic properties panel. Designers can switch effortlessly between manual adjustments and AI-assisted suggestions. Whether refining spacing or testing color palettes, Flows+ keeps creativity fluid. The tool empowers designers to stay in the zone—fine-tuning details or exploring new ideas—without needing to break focus for repetitive design tasks.

Research Focus

To reimagine interface design, the team dissected workflows from wireframe to high-fidelity UI. Through rapid sprints, interviews, and hands-on experiments, key friction points emerged—especially around creating consistent variations. Inspired by CSS logic, we explored class-based design models to bring order and flexibility together. In parallel, we studied AI-driven design aids, examining how generative algorithms could support—not override—human creativity. Our findings pointed to a hybrid approach: a system that learns from designers, suggests when asked, and integrates naturally into the creative flow instead of interrupting it.

Key Learnings

Designers need tools that support, not automate, their intuition. Our research showed that variation generation works best when seamlessly integrated—not separated—from core workflows. Class-based logic offers a powerful bridge between visual design and development structure. Most of all, we learned that intelligent systems must listen as much as they suggest: when designers guide the process, AI becomes a partner—not a distraction.

System
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