How To Organize 1250+ Design Screens in Figma (+ File examples) (https://lnkd.in/e7X4fKcj), a practical case study of how to organize design screens in user flows — to reduce repetitive work and still cover all user journeys. Via Lorenzo Palacios Venin.
✅ Divide the product into files based on navigation.
✅ Each navigation section will get its own Figma file.
✅ … Read the rest
Month: February 2024
Accessibility Research
How to build and run accessibility research, across various dimensions — from permanent and temporary to situational and travel, across touch, seeing, hearing, speaking and thinking.
How We’ve Built Accessibility Research at Booking.com” (https://lnkd.in/eq_3zSPJ), a fantastic case study on how to build accessibility practices and inclusive design into UX research from scratch. Kindly put together by Maya Alvarado.
🚫 Don’t … Read the rest
Service Blueprint Design
A service blueprint is a diagram that visualizes the relationships between different service components (people, props, and processes) that are directly tied to touchpoints in a specific user journey. Service blueprints are part two of user journey mapping; they help businesses discover weaknesses and identify opportunities for optimization.
1️⃣ Define the scope and objectives
✔ Identify the service. Clearly define … Read the rest
AI-Powered Figma Plugins
Top 22 AI-Powered Figma Plugins 👇
A transformative toolkit designed to amplify the capabilities of designers. This curated collection of plugins leverages artificial intelligence to redefine the creative process, enabling designers to work smarter and more intuitively. Dive into a world where automation meets innovation, streamlining tasks and unlocking unprecedented efficiencies.
All these plugins have free plans and you can … Read the rest
Generative AI: Facts VS Creativity
This nugget from our Gen AI research study shows why it’s essential for
@Google to get search/Bard right. Using as more capable search/knowledge base is the singe most common use case of Gen AI today.
People’s primary expectations of Large Language Models: looking up facts. VS what LLMs are innately good at: creativity.
The brain is a prediction machine. We … Read the rest