This article explores UX lessons learned from AI food logging, emphasizing that the best input method (photo, barcode, text) varies depending on the user's situation. The mistake is treating a single input mode as the entire product.
Designing effective conversational interfaces demands a deep understanding of design principles and user behavior, emphasizing a user-centric approach and appropriate tone. Many designers face challenges due to a lack of resources and common mistakes, but guides like "50 ChatGPT Prompts for Freelance Designers" offer valuable assistance.
This article provides a practical guide for developers on deploying voice AI solutions for construction jobsite estimating. It details technical and UX lessons learned from over 50 real jobsites, highlighting how voice AI addresses the unique challenges of field workers compared to traditional SaaS.
The content details the creation of a frontend aimed at making AI decisions understandable, incorporating features like reasoning tracking and comparison dashboards. It covers design principles, technical challenges, and the tech stack utilized, including Next.js and FastAPI.
This article introduces VertaaUX, a tool designed for deep UX and accessibility auditing on URLs, addressing the gap left by AI agents that generate user interfaces without considering usability. It demonstrates the tool's use via CLI and MCP server for integration with AI agents like Claude, Cursor, and Copilot.
O autor compartilha lições aprendidas ao desenvolver o 2ndOpinion, uma ferramenta de revisão de código por IA, através de dez versões de sua CLI. A principal descoberta foi a importância de simplificar a experiência do desenvolvedor, removendo decisões complexas e focando na usabilidade intuitiva.
Privacy-led UX is a design philosophy that prioritizes transparency in data collection and usage to build trust in customer relationships. It treats user consent as an ongoing interaction, rather than a mere compliance checkbox, which is crucial for the AI era.
Products often fail because they are designed around a company's internal logic, not the user's mental model, leading to user frustration. Interfaces mirroring internal structures, terminology, and workflows create friction, causing users to leave when they feel forced to "figure things out".