#UX design

#UX design

The reason is a lack of user research to understand how people think and act when shopping, and how they navigate their way through the experience to get it done. It's the user experience concept of a mental model, if you want to get fancy, or the application of a system matching the real-world heuristic they teach you about in college.

When we think about people who are deaf, we often assume stereotypes, such as "disabled" older adults with hearing aids. However, this perception is far from the truth and often leads to poor decisions and broken products. Let's look at when and how deafness emerges, and how to design better experiences for people with hearing loss. Deafness Is A Spectrum Deafness spans a broad continuum, from minor to profound hearing loss.

The rise of GenAI tools has introduced a new paradigm for design work - rather than crafting interfaces by directly manipulating elements in design tools, designers can prompt AI-prototyping tools to generate designs. When you're working with AI, the output quality will be largely dependent on the specificity of the prompt. This article discusses common issues with vague text prompts and offers recommendations on how to achieve better results from AI-prototyping tools without undertaking the bulk of the design work yourself.

Ask any instructor what helps students learn, and it's unlikely any of them will answer "a really big wall of text". It's incredible to me, as both a university instructor and a UX designer, that the army of people working at OpenAI are not imagining better tools for our students. I want to walk you through a design pattern in ChatGPT that, despite its good intentions, might be creating unintended hurdles for students.

Choosing a learning path in tech can feel overwhelming when you're just starting out. With so many options, from design to coding to data, it's normal to feel unsure about where to begin. The good news is that you do not need prior experience to explore these fields. With curiosity and a willingness to experiment, you can find a path that fits your goals and interests.

When my order arrived, I kept wondering how I could've missed something so obvious. The answer? Selective attention - our brain's way of focusing on what seems most important in the moment, while filtering out the rest. Cognitive principles like selective attention shape every user interaction - what people notice, remember, learn, and even the mistakes they make. Apply them thoughtfully, and you can reduce mental effort, guide users' attention, ease recall and retention, and even motivate users.

Over the past few months, the UX design field has been flooded with AI-powered prototyping tools that generate interfaces instantly from natural-language prompts. Despite the massive marketing hype, our evaluation with real design scenarios revealed that these tools can follow instructions to achieve a general goal, but they lack the sophistication to weigh design tradeoffs and produce thoughtful, high-quality designs without extensive guidance from humans.

Businesses replacing human support agents with chatbots isn't new. Even before the AI chatbots of today, which are extremely common now, companies were using heavily engineered chatbots that could understand only certain keywords and respond with specific answers. They were terrible, but the one remarkable thing about them is that they showed us what different demographics really expect from customer support and set the standard for how AI-first helpdesks should work - not only in terms of support agents but support overall, including documentation.

VeJa is a company that creates guitar plugins simulating amplifiers for music production. They were selling exclusively on the MOD Devices platform but wanted to expand their reach with their own online store. The challenge? They had great products, a loyal niche following, but no website. Just a logo. And us. The brief was simple: Our bootcamp team of three had just 8 days to prototype a e-commerce platform that would help VeJa compete

Using the internet with the help of an AI is a real thing-and it became even more real Tuesday when OpenAI, the generative AI industry's de facto avatar, announced the release of its new ChatGPT Atlas browser. A new race has begun to reinvent the Chrome-style browser experience we've used for so long: The race to reinvent the browser around natural language AI.

A product team once spent weeks debating why their new signup process wasn't working. The forms looked simple, the copy was clear, and the buttons were exactly where they thought users wanted them. But when they mapped out the steps a customer actually took, they saw the problem: users were bouncing midway because the journey was cluttered with extra clicks. 🫤

A lot has been written about filters in the context of the user's journey, complex enterprise software, UI patterns, and UX patterns.

The future of the human experience with digital products necessarily depends on the relationship we will have with information - whether predicted or post-dicted. The use of Artificial Intelligence (AI) and, soon, quantum computing, will dictate the evolution of the digital environment we live in and, consequently, the evolution of human beings themselves over the coming decades - or perhaps the next century.

Seeing your life as a Hero's Journey can make you happier, more resilient, and more fulfilled. But these same principles can also transform your digital products, helping you create more motivating and meaningful user experiences. In this article, I'll share insights from a recent paper on the psychology of the Hero's Journey. I'll explain what it is, guide you through a simple exercise to help you experience its psychological effects, and explore how you might heroify your own digital products.

Real-time dashboards are decision assistants, not passive displays. In environments like fleet management, healthcare, and operations, the cost of a delay or misstep is high. Karan Rawal explores strategic UX patterns that shorten time-to-decision, reduce cognitive overload, and make live systems trustworthy. I once worked with a fleet operations team that monitored dozens of vehicles in multiple cities. Their dashboard showed fuel consumption, live GPS locations, and real-time driver updates.

UX designers frequently work in ambiguous spaces, most notably the discovery phase. We collaborate closely with product managers to identify new problems, understand users' goals and frustrations, and strategically develop solutions to address their needs. However, the best solutions aren't always straightforward, and with AI being embedded in every new product and feature, it makes things a bit more challenging. Just as we get comfortable using AI, something changes or evolves. This makes AI features unpredictable and difficult to document requirements for.

When I first came to the US a decade ago, I wasn't sure how I'd fit into the job market. I wasn't from here and didn't know the playbook. Through trial and error, I eventually found myself in the then-booming role of UX designer - a job that felt relatable, in demand, and easy to explain to others at the time. Like many in the field, I leaned heavily into the mantra of "data-driven" design. Every choice had to be backed by numbers, validated by user tests, or confirmed by analytics. Every choice had to be backed by numbers, validated by user tests.