The boundaries between art, design, and technology are becoming increasingly blurred. This case study delves into the creation of The Skull Crusher website — an experimental extended reality (XR) project that uses hand-tracking technology to immerse users in a digital art experience. Through this, we’ll explore the process of merging creativity with technology and provide actionable insights for designers and developers in the art and design industry.
The Concept: Blurring Lines Between Art and Interaction
The Skull Crusher website wasn’t just a project — it was a vision to merge art with cutting-edge technology. By combining hand-tracking mechanics with a story-driven environment, the goal was to create an engaging and artistic digital product. The key takeaway? Digital products in the art and design industry must evoke an emotional connection while maintaining functionality.
Actionable Insight: Always start with a compelling narrative or artistic vision. This becomes the foundation for both the design and technical approach.
Challenges: Turning Vision Into Reality
Achieving Seamless Hand Tracking: Designing intuitive hand controls in a browser-based XR environment required technical precision.
Creating a Cohesive Experience: Integrating storytelling, sound, and interaction into a single, seamless experience demanded a holistic approach.
Actionable Insight: When tackling technical challenges, prioritize the user experience above all. Technology is a means to an end, not the end itself.
The Process: Designing for Immersion
Ideation and Storyboarding
The project started with brainstorming sessions to conceptualize the storyline and interactions. A simple narrative — a battle against a dark magician — formed the core.
2. Building With Three.js
The 3D environment was created using Three.js, allowing for realistic lighting and interactive objects.
Hand-tracking mechanics were developed using Google Mediapipe to recognize gestures like aiming, shooting, and stopping.
3. Iterative Testing
User feedback was crucial to refining the controls and ensuring they felt natural.
Multiple rounds of testing helped optimize performance without compromising visual quality.
Actionable Insight: Iteration is your best friend. Build, test, refine — and repeat until you strike the right balance.
Results: Impact Beyond the Screen
The Skull Crusher website demonstrated how art and technology could merge to deliver:
Emotional Engagement: Users felt a deep connection to the story and interactions.
Technical Innovation: A seamless hand-tracking interface showcased the potential of XR on the web.
Creative Inspiration: The project has inspired other designers and developers to explore similar intersections of art and technology.
Actionable Insight: Measure success not just by metrics but by the emotional and creative impact your product leaves on users.
Takeaways for Designers and Developers
Embrace Emerging Technologies: Stay curious and experiment with tools like hand tracking and XR to push boundaries.
Collaborate Across Disciplines: Work closely with storytellers, sound designers, and developers to create holistic experiences.
Focus on User-Centric Design: Always prioritize the end-user’s experience, ensuring technology serves a purpose.
Conclusion
Designing and building digital products in the art and design industry is about more than aesthetics — it’s about crafting experiences that resonate. The Skull Crusher project showcases how creativity and technology can converge to create something truly immersive. By focusing on storytelling, iterative design, and user-centric innovation, we can continue to push the boundaries of what digital products can achieve.
What’s Next? If you’re inspired by this case study, consider how you can integrate emerging technologies into your projects. Start with a bold idea and let creativity and technology guide you to something extraordinary.
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Canvs Editorial Meaningful stories and insightful analyses on design
Did you know that over 1 billion people worldwide live with some form of disability? Yet, accessibility often gets overlooked in design.
That’s starting to change. The core of this understanding is that addressing the “lowest” common denominator by virtue addresses the total pool.
Thanks to AI, we’re moving from just meeting basic accessibility standards to actually creating better, more inclusive experiences.
With tools like voice assistants and real-time captions, AI is helping people interact with the world in ways that feel more natural and intuitive.
Let’s take a closer look at some products that are leading the way.
1. Voice interaction: From convenience to necessity
Voice assistants like Alexa, Google Assistant, and Siri have shifted from being just convenient tools to essential ones, especially for people with physical disabilities. They offer a way to interact with devices without the need for touchscreens or keyboards, which can be limiting.
For instance, someone with limited mobility, with voice commands, can control their environment — adjust the thermostat, turn off lights, or set reminders — without needing to move.
It isn’t just convenience, it’s independence.
For designers, this shift means rethinking navigation. Interfaces built around voice interaction need to be simple and intuitive, without relying on visual or tactile elements. Traditional buttons and menus become secondary as spoken commands take the lead.
Voice-first interaction demands an experience where users can access information or complete tasks without ever needing to look at or touch a screen.
In this context, design becomes about listening rather than seeing.
Voice-controlled apps are making a real impact in areas where traditional tech falls short.
For example, in healthcare, voice-activated medical devices allow patients with limited mobility to interact with their environment. It can be be either to adjust their hospital bed or calling for help — useful for those who can’t use their hands.
In education, voice technology gives children with physical disabilities a hands-free way to engage with lessons, leveling the playing field.
Another good example of such product is Voiceitt. This **app is designed for people with speech impairments, using AI to recognize and adapt to non-standard speech patterns.
It helps users who may struggle with mainstream voice assistants, communicate better.
Real-time captioning has become an essential tool for people with hearing impairments.
AI-driven tools like Google Live Transcribe now transcribe conversations, meetings, and even background sounds instantly, in real-time. This opens up access to everyday interactions that were once difficult or impossible for those with hearing loss.
Picture someone attending a business meeting or participating in a social gathering. Real-time captioning enables them to follow conversations, no matter the noise level or complexity of the discussion.
It’s especially useful in environments like classrooms or live conferences, where important information is conveyed verbally and needs to be understood on the spot.
AI is making real-time captioning more practical by adding multi-language support, so people in international events or workplaces can follow along, no matter the language.
Tools like Google Translate or Microsoft Translator can instantly convert speech into captions in different languages.
For example, at a conference, captions can be translated live, allowing non-native speakers to fully participate.
Some tools also go a step further, picking up on tone and emotion, so captions aren’t just about words — they give a fuller picture of what’s being said.
3. Object and scene recognition: More than just descriptions
AI tools like Seeing AI and Google Lookout are giving people with visual impairments a better sense of their surroundings, not just by identifying objects but by helping them understand entire scenes.
Someone using Seeing AI to walk down a busy street gets more than just a list of objects. The app might describe people nearby, alert them to cars at a crosswalk, or even note store signs along the way.
In a store, Google Lookout can read product labels aloud, helping users find what they need without asking for help. It’s about more than identifying things; it’s about helping people make sense of the world around them.
Be My Eyes, originally, connected visually impaired users with sighted volunteers to help with tasks.
Now, with AI stepping in, it’s doing more than just identifying objects. It’s helping narrate experiences in ways that add meaning.
For instance, it can describe not only what’s in front of a person but also capture subtler details — like recognizing someone’s facial expression or sensing the mood in a room.
Imagine someone using an AI tool that detects that the person in front of them is smiling, or that the room feels warm and inviting based on the lighting and sounds.
Samsung’s Good Vibes app, is designed for deaf-blind users to communicate through vibrations, offering a lifeline where traditional communication falls short.
The app uses Morse code — simple taps and vibrations — to send and receive messages.
A sighted person types a message that gets translated into vibrations, and the deaf-blind user responds using touch patterns.
More accessibility, one interaction at a time
From voice control to real-time captions and everything in between, these tools are helping people interact with their surroundings in ways that feel more natural.
For designers, it’s a chance to rethink how we build, not just for screens, but for real-world spaces. The goal is simple: create environments that adapt to everyone, not just a few.
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Canvs Editorial Meaningful stories and insightful analyses on design
In design, AI has shifted from being a buzzword to an essential tool in daily workflows. Agentic AI, a newer development, goes beyond simple automation. It’s a system that works independently, handling tasks that designers once had to oversee themselves. This is especially useful during early-stage product testing, where catching issues early can save a lot of time and effort down the line.
When applied to design, agentic AI can review prototypes, identify potential problems in a flow, or flag areas where the user experience might break.
It acts as an extra layer of validation before human testers even get involved.
The practical shift from human-driven to AI-assisted testing
In the past, product testing meant relying on human testers. It was a necessary but slow and expensive process that often stretched out product timelines. Designers would build, wait for feedback, and then go back to tweaking and reworking the designs, creating delays.
With agentic AI, this cycle looks different.
Instead of waiting for human input at every stage, AI tools built into design platforms can step in early. They catch things like layout misalignments, buttons that don’t work, or accessibility issues, acting as a first line of defense.
They can now spot inconsistencies in design systems or check if a design sticks to brand guidelines without anyone having to manually go over it.
How agentic AI handles objective validation
Let’s look at how it works in real-world tools.
Take Maze, for example. It allows designers to simulate user journeys and spot friction points before human testers are involved.
Designers can run tests on their prototypes and get immediate feedback on potential issues. The tool can flag usability problems, such as unclear navigation or broken interactions, making it easier to refine the user flow early on.
This means that before any human testing happens, designers already have a clear picture of how well their product holds up.
It’s like having an automated second set of eyes.
How agentic AI handles subjective validation & current limitations
AI excels at objective validation but still has limitations with subjective elements like visual aesthetics and user experience.
AI tools can suggest functional improvements, like recommending alternative button placements for better usability or adjusting the layout for smoother navigation. But these suggestions are based on algorithms and patterns, not on the nuanced design choices a human designer makes.
For example, AI might recommend shifting the positioning of a call-to-action button for better flow, but the final decision on its placement — whether it feels intuitive, balanced, or aligned with the brand’s identity — still lies with the designer.
While AI handles technical aspects, the emotional and visual nuances of design still require a designer’s creative touch. Right now, AI and human designers complement each other — AI ensures functionality, while designers bring the human insight needed for impact and aesthetics.
How agentic AI is benefitting design teams
1. Faster feedback, less waiting
Agentic AI helps catch basic issues early on, so teams can resolve problems before they get bigger. This keeps the feedback process moving faster and designs on track.
2. Cutting costs in the early stages
With AI handling initial checks, there’s less need for human testers at the start. This helps cut down on early testing costs, freeing up resources for later stages.
3. Smoother testing as you go
Catching structural problems earlier means fewer revisions in later testing. This smooths out the process and helps avoid delays when you’re closer to launch.
4. More space for creative thinking
Automating the routine tasks — like checking alignment or links — gives designers more mental bandwidth for strategic, creative decisions, letting them focus on what really matters.
Agentic AI, the first line of defense
As AI tools continue to improve, there’s real potential for them to handle more subjective testing — like evaluating overall user experience or aesthetics. This will give designers even more space to focus on high-level decisions, while AI tackles the more time-consuming tasks.
Design teams should start integrating these tools into their workflows now. The sooner they do, the quicker they can take advantage of more efficient testing and validation before products hit the market.
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While still keeping product usability at a high standard
Canvs Editorial Meaningful stories and insightful analyses on design
User scenarios are a key part of UX design, helping you map out how users interact with your product and guiding decisions to improve usability.
But constantly creating new scenarios from scratch can slow you down, especially when you’re working on similar features or products. Instead of reinventing the wheel each time, creating a reusable scenario template can save you time and keep your designs consistent.
In this post, we’ll show you how to reuse scenarios in UX design to save time and resources — building better user experiences.
1. Use a scenario template
A scenario template is a simple, practical tool that saves time and keeps things consistent. It gives you a clear structure for your user scenarios, covering the basics like who the user is, what they’re trying to do, the steps they take, and the outcome. This way, you’ll not waste time figuring out how to organise these details every time you create a new scenario.
The key benefit? You don’t miss any important detail in it.
a. Create or find a template
You can make your own template, or use one that’s already out there, like the ones from the Interaction Design Foundation. The goal is to have a structure that works for you and your team, covering the essentials like user, context, goals, actions, and outcomes.
b. Add a checklist
A simple checklist in the template will make sure you don’t overlook key details. Think of it as a quick way to confirm that your scenarios cover everything from user goals to possible challenges they might face.
c. Tweak it for different projects
The upside of a template is that it’s adaptable. Whether you’re working on a new feature or updating an old one, you can modify the template to fit the situation. The flexibility will save you time.
2. Create a scenario library
A scenario library is a straightforward way to keep all your user scenarios in one place, making them easy to find and reuse. Instead of starting from scratch for every new feature or project, you can pull from a well-organized collection of scenarios that are already in place.
a. Implement categorisation
Make it easy to find what you need by organising scenarios using tags or categories. You can categorise them by user personas, tasks, or specific scenarios. This way, when you’re working on a particular part of a product or targeting a specific user group, you can quickly find relevant scenarios.
For example, if you’re designing for a banking app, you could tag scenarios by user types like “new user” or “experienced user,” or by tasks like “making a transfer” or “checking account balance.”
b. Encourage collaboration
Share the scenario library with your team and relevant stakeholders so everyone can contribute and provide feedback. When team members are involved, they can improve or add to existing scenarios based on their own experience, which will make the library well-rounded.
3. Update and refine your scenarios
User scenarios aren’t static — they need to evolve as your users, product, and market change. What worked a year ago may no longer be relevant, so update your scenarios regularly so that they stay accurate and useful.
Keep it grounded in real-world data and evolving user needs.
a. Do regular reviews
Set a schedule to review your scenarios — whether it’s quarterly or after major product updates — to make sure they still align with user behaviors and expectations.
b. Use data to inform updates
Tap into user feedback, usability testing, analytics, and market research to adjust your scenarios. Data-driven updates will reflect real user needs, rather than assumptions.
c. Track changes with version history
Keep a version history of your scenarios. You’ll be able to see what’s changed over time and lets you learn from previous decisions. You can look back to understand why certain changes were made or revert to earlier versions if needed.
4. Use scenarios as a starting point
Scenarios are a great foundation, but they shouldn’t box you in. Instead of seeing them as fixed, think of them as a jumping-off point for new ideas. They give you a solid structure to start from, but there’s room to go beyond what’s on the page.
a. Use scenarios for brainstorming
Don’t treat scenarios as a fixed plan. Let them spark new ideas and explore alternative ways to solve a problem. This way, they’re more of a tool for discovery than just a checklist to follow.
b. Get input from the team
Have your team build on existing scenarios. Different perspectives can see angles you might not have considered, giving you more options to work with.
c. Keep notes on what you learn
When new ideas or changes come up, make sure to document them. Capture useful insights for future projects and make sure nothing important slips through the cracks.
5. Consider edge cases and atypical users
Designing for the majority is crucial, but it’s the outliers — the edge cases — that often reveal blind spots in your design. These less common interactions can expose weaknesses or opportunities in your product that you might not notice otherwise.
Consider these scenarios and you’ll be to handle unexpected user needs without breaking the experience.
a. Spot edge cases early
As you develop scenarios, actively look for those rare or tricky situations users might encounter. For instance, consider how users with slow internet connections or outdated devices will interact with your product. Identifying these cases early prevents headaches later.
b. Design for atypical users
Build scenarios that focus on users who don’t fit the average mold. Think about those with different physical abilities, unusual workflows, or unique goals. For example, designing a banking app? What about users who rarely use digital tools or are new to online banking?
c. Get outside perspectives
Bring in feedback from people who use your product in ways you hadn’t expected. This could be users from different regions, age groups, or tech comfort levels. Their insights can point out scenarios you didn’t think of and push your design to cover more ground.
6. Leverage historical data
Historical data is a valuable asset in UX design. By analyzing how users have interacted with your product in the past, you can refine your scenarios to better reflect real-world behaviors.
a. Analyse past projects
Look back at data from previous projects — things like user behavior patterns, common pain points, or frequent mistakes. You’ll spot recurring issues or trends and get a clearer picture of what works and what doesn’t.
b. Use data to refine scenarios
Apply what you’ve learned from historical data to tweak and update your scenarios. If certain behaviors or needs keep surfacing, make sure your scenarios reflect them.
It’s more than a template, it’s an asset
Reusing scenarios in UX design is all about working smarter, not harder.
Instead of reinventing the wheel each time, you can focus on improving what already works, making your process faster without cutting corners on usability.
Whether you’re dealing with a simple feature update or a full product overhaul, reusing and refining scenarios will allow you to keep moving forward, fast.
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Creating a visually appealing and user-friendly website can be challenging. However, there are common mistakes that can detract from the user experience and negatively impact your site’s performance. Here are ten common web design mistakes and how to avoid them.
1. Ignoring Mobile Responsiveness
Mistake: Many designers focus solely on desktop versions of their websites, neglecting the growing number of mobile users.
Solution: Use responsive design techniques to ensure your website looks great on all devices. Tools like CSS media queries can help you create a flexible layout that adapts to different screen sizes.
2. Overloading with Content
Mistake: Crowding your pages with too much text and too many images can overwhelm visitors and obscure your message.
Solution: Keep your design clean and simple. Use whitespace strategically to give your content room to breathe, and focus on delivering concise, impactful information.
3. Poor Navigation
Mistake: Complicated or unclear navigation can frustrate users and make it difficult for them to find what they’re looking for.
Solution: Design an intuitive navigation system with clear labels and a logical hierarchy. Consider including a search bar for added convenience.
4. Slow Load Times
Mistake: Slow websites frustrate users and lead to high bounce rates.
Solution: Optimize images, use efficient coding practices, and leverage caching to improve your site’s load times. Tools like Google PageSpeed Insights can help identify areas for improvement.
5. Ignoring SEO Principles
Mistake: Neglecting SEO can make your website difficult to find through search engines.
Solution: Incorporate basic SEO principles, such as using descriptive titles, meta descriptions, and alt tags for images. Ensure your content is keyword-rich but natural-sounding.
6. Inconsistent Design Elements
Mistake: Using inconsistent fonts, colors, and styles can create a disjointed user experience.
Solution: Establish a style guide for your website and stick to it. Consistency in design helps build a cohesive and professional look.
7. Lack of Accessibility
Mistake: Failing to design for accessibility excludes users with disabilities.
Solution: Follow Web Content Accessibility Guidelines (WCAG) to make your site accessible to all users. Use features like alt text for images, keyboard navigation, and readable fonts.
8. Not Testing Across Browsers
Mistake: Designing for only one browser can lead to compatibility issues on others.
Solution: Test your website across multiple browsers to ensure a consistent experience. Tools like BrowserStack can help with cross-browser testing.
9. Overuse of Animations
Mistake: Excessive animations can distract users and slow down your site.
Solution: Use animations sparingly and ensure they serve a functional purpose. Avoid using heavy animations that can impact performance.
10. Ignoring User Feedback
Mistake: Not considering user feedback can result in a website that doesn’t meet user needs.
Solution: Collect and analyze user feedback to make informed design improvements. Use surveys, usability testing, and analytics to gather insights.
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UX design is a profession that was introduced to help companies solve problems creatively. However, it has taken an all-new avatar in the past 2 years. It is frightening and exciting at the same time! Through this article, I wish to clear out some of the fog and be your industry insider.
We’ve all noticed shifts in where UX designers are starting their careers. Earlier this meant teaching yourself design from YouTube and articles listed on Google. This journey was made even easier with short and cheap courses online.
However, as is with any other career path, competition creates new ways to do things. As more people wanted to become designers, it became clear that things needed to change. People found solace in UX bootcamps and institutes. It wasn’t long before colleges followed suit and brought diplomas and degrees into the mix. However, this wasn’t enough.
Fast-forward to 2024, regardless of all the shortcuts or solutions, UX design has been hard to digest lately. Even though UX designers are changing and becoming better, the industry has grown to expect different things. So, the new generation ends up being surprised when their skills don’t match up with what recruiters are looking for.
Where is the starting point now?
It’s much more product-focused and action-oriented. If you want to ace an interview moving forward, you have to show how the business and core product can be affected by research, data, and proper strategy. Companies also expect you to have some knowledge of their industry, i.e. finance, food, transport, etc. So if you apply for a fashion-tech company, having good knowledge of fashion and how the industry works can help a lot.
When it comes to educating yourself in the skill set, you need to find material and resources that take you further than UX itself. You need to find elements of the CX (customer experience) process, such as the CES (customer effort score) which allows designers to get quick feedback for the product’s UX as well.
CES on a clothing website
Things don’t end here, of course. Creative companies are looking for even more creative people. So, if at one end you’re great at solving business problems, being equally creative has become a must for the job. Apart from the science behind how a user uses a product, it is equally valuable to know how to “wow” the user with the creative aspects of the product. Adding delight is the best way I could describe this phenomenon.
I still remember when I started practising UX design for the first time. We were inspired to have tunnel vision and focus solely on UX research, testing, design, and most importantly — empathy.
Since I’m creative, sticking to just one skill sounded and felt absurd. So while I became better in my UX design process, I started garnering skills that made sense to my career. This included content creation, No-code, and even niches like motion design. While invisible to everyone else, I was proud of everything I learnt.
My biggest mistake at the time was not marketing these skills to recruiters and clients. The moment I fixed that, my career started moving forward. I became even more valuable as an asset to the companies I worked with, and they appreciated what I was truly bringing to the table. Some of my seniors asked me to teach the other designers in the company. This gave me a sense of confidence I never had before.
In 2024, parallel skills have become more crucial than ever. Organisations appreciate them more than ever and understand how these skills can affect your output. Since the bigger-ups have tried every trick in the book, they’re looking for new ways to solve problems. This makes them open to new ideas and ways of doing things, which makes it a win-win for the design industry.
Clients want studios to package in UX design, graphics, marketing, development, and more in to one service.
As an educator and entrepreneur, I’ve been in constant touch with design studios all across the country. Over time, I’ve started to notice patters and understanding the real story behind these creative companies. As one would think, it isn’t all gold and roses.
Studios have had to create a “hybrid” work culture, where designers are taking up tasks they never thought they would have to do. This change comes with the changing demand of clients that these studios are facing. Clients want studios to package UX design, graphics, marketing, development, and more into one service.
The navigation bar of a popular design studio
Due to various changes, there is a huge space in the service and creative agency space. If you’re an open-minded designer with various skills you don’t mind using them to help the company, there is always a space for you. The whole notion of, “I only want to focus and grow as a UX designer” needs to go out the window when you need better opportunities. Take this advice of mine with a huge pinch of salt. The same path won’t work for everyone. Find and research opportunities based on your boundaries, preferences and wants.
Physical Spaces Over Online Connections
People have always craved physical connections and socialization over online networks and video calls. Being able to shake hands, share laughter, be present, and exchange business cards can never be replaced.
Every month companies are organising some incredible meetups, designathons, and networking sessions in almost every metro city in the world. Some cool communities you can follow are — Friends of Figma, Designwings Events, and a few more who are doing such work consistently. I have met some incredible people to work with and even found freelance opportunities at some of them.
These events pose a great platform to get real time feedback on your ideas, pitch your business, or even get help from like-minded individuals.
An Objective Look At The Confusing Job Market
A couple of years ago, the job market in the design space wasn’t exactly booming. This was thanks to the taboo against creative careers, especially in families with little to no knowledge about such fields. However, in a vast landscape, even the smallest amount of demand was good enough for the low supply of employees.
Now, the world demands more designers, with a crazy saturation when it comes to options these companies have. One observation I’ve made, is the existence of fewer quality creatives in this large crowd. Smart recruiters are always looking for some red flags while giving equal importance to some green ones.
Some red flags to work on / improve:
Talking too much about tools and software instead of problem-solving methods.
Having scarce knowledge of corporate culture and how it fits with design.
Considering your income as a major or only motivation to work.
Being less social — either online or offline.
Having few or no creative outlets apart from your job.
Lacking in communication and presentation skills.
Some green flags to showcase and promote:
Additional skills that might bring value to the company or team.
Certificates and proof of learning that show you have hunger to grow.
Sharing your design or creative work online for everyone to see and admire.
A special personality trait that can affect your work in a positive sense.
Network and connections that you may have.
Contributions to the community in the form of mentorship, resources, content, etc.
Ambitious future plans and goals.
A.I. Is Making Jobs & Opening New Doors
You expected this article to have a “AI is going to take your job” section, but you were pleasantly surprised to see a unique take on it.
In the crowd of people putting AI down and wanting some regulations, I’m trying to stay optimistic. Don’t get me wrong, governing bodies restricting the use of AI to save jobs is a great way to go about it. In the meantime however, how can one use this technology to upgrade one’s career?
To begin with, I came across this job-post on LinkedIn that sort of blew my mind.
A job post from a major ed-tech company
A fun tool that seemed to threaten creative jobs a few months ago, started creating a demand for specialists that could use the tool well. Most of these A.I. designers are going to work closely with graphic designers and leaders to provide them with necessary assets. Custom images for marketing material is a great example.
Unfortunately, it isn’t all flower petals and blue oceans. A.I. has arrived as a major challenge for designers. We might have to justify our roles in the coming years if it keeps on proceeding like this. Push comes to shove, this new era of AI could nudge us to be better and bring more value to the table, which from my perspective is a big plus.
Are We All Just Product Managers Now?
Like it or not, design is not just design any more. In fact, UX design is a plethora of skills that helps improve the overall product. Whether it includes user research, market analysis, or product strategy, nothing is truly off limits. In fact, being closely involved with product managers is now encouraged and looked up at. These two professions are so closely stitched together that designers start becoming passionate about this new career path and often want to switch.
I often question why these are two completely separate professions. Where one is focused on the business and product vision, the other focuses on the creative and user aspect of the product. This difference becomes even slimmer when UX designers pivot into product design. They start balancing both these roles for the benefit of the company.
This concept is full of clues of where UX design is headed to. You can see where professionals are pivoting to and where companies are focusing. With the state of the changing economy, and shift in tech, UX design could do with a new coat of paint. The question still lies, where is UX truly headed, and what will designers make of it?
Design is Passion Based & Interest Driven
I started off as a photographer, jumped into web design, deviated into UX design and pivoted into entrepreneurship. I’ve come across thousands of UX designers during my educational journey, and one reality always struck me. They rarely stay in one place for a long time. In fact, some of my peers say they were always open to new ideas and wanted to explore something new every 2 years or so.
Off lately, AR/VR has erupted a new desire in designers to learn and switch. “Where do we find AR/VR design jobs? What are the tasks we would need to do? How do we learn to design for AR/VR”. These are just some questions that designers at different professional levels are asking.
This is a really cool revalation, since it reveals an interesting reality of UX designers. We are all techies! We use software. We create for new and cool hardware. We are unintentioanlly sucked into the tech and nerd iceberg.
As tech has been progressing in various different directions, we have the option to go in any direction as well. Whether it is AR/VR, folding screens, transparent displays, artificial intelligence, digital payments, software and hardware innovations, or anything revolving around tech; UX is driven by an individual’s interest in a certain field or industry.
The more confident we are of our skills, the easier it will be for us to shift and explore all at once.
Is UI Design Over Because of AI?
Uizard AI Design Tool
Let’s face facts, companies understand that A.I. is a strong keyword they can use to promote their product. Because of this new evolution, almost every design tool has A.I. features as a part of their offering. You would also see some UI design tools powered by A.I., where you type in a prompt explaining your project and get editable screens in return.
While this process might seem threatening to a UI designer’s career, this is more of a wake up call for creatives. UI designers for a long time have stuck to the skills they learnt earlier, and seldom get into UX design. Now, they willl surely have to expanding their skillset to provide more services and improve their designs. Just UI designing isn’t going to cut it anymore.
To put the argument of A.I. taking over jobs to rest, these can actively be wireframing and ideating tools. Getting to the final production design is going to be much faster. If we look at this from a positive perspective, A.I. will allow designers to focus more on problem solving, research, and creativity, instead of the day-to-day mundane tasks.
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When searching for resources on UX and AI, I found it surprisingly difficult to find any writing beyond advice and software to make the design process more efficient. While efficiency tips are valuable — don’t get me wrong- my deeper interest lies in understanding how designing with and for AI systems will shape the very foundations of UX.
After doing some research and taking a very useful course pitched for developers and not designers: “UX for AI: Design Practices for AI Developers”, I wanted to share my findings, stripping away the jargon and technical terminology that often excludes designers from the conversation.
I’d like to point out that my insights are driven by curiosity, not expertise. Yet, what I do think is evident is that there is a growing need for designers to work more closely with AI engineers and AI itself. Such collaboration is key to keeping our products aligned with user needs, ensuring they continue to be both accessible and impactful.
Designing for uncertainty
Traditionally, UX design has been about creating predictable, reliable products, where specific actions lead to expected outcomes. A product should be consistent — this is a design principle that ensures that users can navigate products with expectations and ease. In the design process itself, we meticulously map out all possibilities in user flows (A-B) and prototypes to design products that are predefined.
However, AI introduces an element of unpredictability, challenging us to design for variable outcomes. With AI, particularly when dealing with sophisticated language models (like ChatGPT), the same input can lead to multiple outputs, and there are infinite inputs. John Maeda, VP of Design and AI at Microsoft, does a really good job of explaining this shift. So how do we design for the unpredictable?
In this new context, designers are tasked with embracing an adaptive design, one that responds to AI’s fluidity in the same way that responsive design responds to different screen sizes. This adaptation will mean dynamic interfaces that can intelligently respond to AI’s unpredictable outputs — probably using AI themselves. We will no longer be designing for fixed pathways but a landscape where user flows are fluid and outcomes unknown. This transition is paradoxical: As the role of AI grows, maintaining consistency in design becomes both increasingly critical and complex. We are challenged to redefine our strategies, ensuring that despite the unpredictability of AI, the principle of consistency remains at the heart of user-centred design.
Over the past three decades, the goal has been to establish absolute trust in technology; it has been a long game and in no way a smooth journey. However, AI has meant absolute trust might be counterproductive. The uncertainty and potential errors within AI systems, especially at the fringes of their capabilities, demands an “appropriate trust” (this is one of the modules in John Maeda’s course), an understanding that encourages users to maintain a critical perspective on AI’s abilities.
The current state of user trust in AI is diverse and complex. While some individuals readily integrate AI into their lives without hesitation, others approach it with caution or even fear. Achieving the delicate balance of healthy scepticism and recognition of its value is essential for developing “appropriate trust” and remains a significant challenge for designers.
In sociology, trust is based on the expectation that the trustee (the AI system) will act in a manner beneficial to the trustor (the user). Honesty and reliability form the bedrock of this relationship. Therefore, while reliability cannot be guaranteed (due to the unpredictability of AI), ensuring honesty is essential. Products need to be transparent, with their capabilities and limitations clearly laid out for everyone to see. Designers play a key role in delineating the boundaries of AI abilities and working to demystify AI to ensure this appropriate level of trust is met.
Introducing Thoughtful Friction
“Usability,” characterised by the ease with which tasks can be completed, remains a fundamental principle in UX design, where the reduction of friction is typically the overarching goal. However, when fostering “appropriate trust”, introducing deliberate friction can prompt users to reflect before taking actions, improving the precision and effectiveness of their outcomes. When usability is so seamless that users are not even aware of their actions they enter an “auto-pilot” mode, devoid of conscious decision-making. This is the time when you unknowingly commit to choices, agree to terms or share misinformation with your thousands of Instagram followers. Given AI’s capacity to further streamline tasks, it’s ever more important that we thoughtfully design friction into the user experience.
For some designers, introducing friction is not alien and has been a way to create an immersive experience, much like ‘The Ikea Effect’. The idea here is keeping the user more engaged. Although our primary aim might not be to create immersion per se, our objective aligns with it: to heighten user engagement, ensuring they are alert and can identify when AI does not meet expected standards. Appnova explores 5 simple ways friction can be a game-changer in design, from preventing bad decisions to giving user responsibility.
Some ways in which we can create friction for a more engaged experience include AI notices and prompts. Here, AI notices refer to the use of visual cues or contextual signals that indicate AI-generated content, prompting users to review AI outputs. This simple moment of reflection can have a big impact.
Striking a balance between seamless interactions and intentional friction is key for creating user experiences that are both intuitive and impactful. Monitoring this balance, gathering user feedback, and analysing time spent interacting with the product are important steps to iteratively refine, design and sustain this balance.
Usability Testing Reimagined
With AI’s inherent variability, usability testing can no longer follow task completion and assessment at key points in the design process. By using AI in the usability testing process, we are able to address the need for ongoing, adaptive testing that can be integrated into the product itself. This more continuous refinement, reflecting the principles of iterative, user-centred design, is what usability testing has always wanted to be.
Where does the future of UI sit within this? It seems like there may be a trend towards an interface-less design, influenced by not just AI but also the advancements in voice interaction. This presents a new challenge for designers — particularly for those who thrive on visual creativity (me!). With AI, it is likely that even less of the interface is needed because a single function can serve far more wide purposes. Or perhaps it doesn’t mean no interface, but the nature of the interface will dramatically change in favour of VR/AR — or perhaps brain-computed interfaces?! Alex Jewell gives a very interesting, if not a little scary, discussion on what the end of the interface will look like. He does suggest that there will still be a place for designers but it will be more strategic and less aesthetic. It almost seems paradoxical that as what’s going on under the hood is becoming more complex, what’s on the outside shrinks away.
The Future of Collaborative UX
Our discussion has only scratched the surface of how AI will change our design thinking. I am in no way an expert on this topic and in early stages of exploring AI and UX integration, but one opinion stands firm: UX needs to evolve into a more collaborative discipline. Microsoft coined the term ‘Collaborative UX’, where designers work more closely with AI engineers but also in collaboration with AI itself. We need to shift away from our siloed, compartmentalised workflows, where designers and developers have distinct roles and processes, towards a more unified, collaborative process. In this new model, designers are important at every stage of development. For instance, their involvement is critical in training the models and designing the system architecture, since these elements are fundamental in shaping the delivered user experience. Likewise, incorporating feedback mechanisms directly into products requires designer input to understand what data and feedback is needed to drive future product changes.
We need to start to also see AI as a co-creator — or perhaps better a co-pilot. We need to ensure that we are strategic in our use of these systems, prioritising design thinking and principles so that AI enhances rather than dictates the user experience. In this collaboration, there is the potential to design more responsive experiences that support rather than overshadow human creativity.
For us as designers, mastering AI is essential, recognising it as a core component of our design toolkit that enhances efficiency and precision. While AI transforms how we design, the user remains our core priority — and that, I believe, will never change.
Article Written by Letitia Rohaise (letitiarohaise.co.uk). Product Designer with a Masters’ in Psychology. Letitia is an advocate for integrating cultural psychology into design, ensuring products are meaningful and accessible across diverse cultural contexts.
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Design Process Thinking is a human-centric approach to problem-solving that emphasizes understanding and empathizing with the needs and experiences of users. At its core, it involves a methodical series of steps aimed at identifying challenges from the perspective of the end user, generating innovative solutions, and iteratively testing and refining these solutions. This approach champions the idea that effective design is not just about aesthetics or functionality in isolation, but about creating solutions that resonate deeply with users, enhancing their lives in meaningful ways. By prioritizing empathy, collaboration, and iterative learning, Design Process Thinking empowers designers and innovators to tackle complex problems with a more inclusive, effective, and human-focused lens.
TL;DR
User needs research
Analyze observations
Ideate
Prototype
Test
…Iterate
Stage 1: Research Your Users’ Needs
Sometimes referred to as the “Empathize” stage, the User Research stage of Design Thinking marks the critical first step in a journey toward creating solutions that are not only innovative but also deeply rooted in real human needs and behaviors. This phase is characterized by user-centric research, where the goal is to step into the users’ shoes to gain a profound understanding of the problem at hand.
At this stage, designers and innovators engage in immersive observation to gather insights into the daily lives, challenges, and interactions of their target audience. Observing users in their natural environment is key, as it unveils the nuances of their experiences and the context in which they encounter problems. This observational process is not just about watching and noting but about seeing beyond the surface to understand the ‘why’ behind user actions and reactions.
Understanding experiences and motivations is another cornerstone of the User Research stage. Through interviews, surveys, and direct observation, designers begin to map out the emotional and practical landscape that shapes user behavior. This empathetic approach allows the team to capture the essence of users’ experiences, going beyond what is said to what is felt and lived.
A crucial discipline in this phase is setting aside one’s own assumptions. It’s easy for designers and problem-solvers to project their own biases and experiences onto the users they are designing for. However, the essence of user-centric research lies in acknowledging and suspending these preconceptions to truly listen and absorb the user’s perspective. This unbiased approach ensures that solutions are not just based on what designers think users need but are grounded in genuine user needs and desires.
By dedicating time and effort to the User Research stage, teams lay a solid foundation for the subsequent phases of the Design Thinking process. With a deep, empathetic understanding of the problem and the people it affects, designers are better equipped to ideate, prototype, and test solutions that genuinely resonate with users and address their real-world needs.
Stage 2: Analyze observations & define problems
In the Observation Analysis and Definition stage of the Design Thinking process, the focus shifts from gathering insights to distilling them into actionable and impactful directives. After immersing themselves in the user research phase, teams face the challenge of organizing the vast amount of information observed. This critical step involves sifting through user feedback, behaviors, and experiences to identify patterns and underlying themes. Such organization is not just about cataloging data but about making sense of it in a way that highlights the real issues users face, moving beyond surface-level observations to the root causes of their frustrations and needs.
With the data thoughtfully organized, the next task is to define the core problems. This isn’t about listing every minor issue encountered but about zeroing in on the most significant challenges that, if addressed, could dramatically improve the user experience. The art here lies in discerning the deeper issues beneath what users say and do, understanding that the most critical problems are often those not immediately visible. It’s a process that requires empathy, insight, and a willingness to look beyond the obvious to what truly matters to users.
The culmination of this effort is the formulation of a clear, human-centric problem statement. This statement is pivotal, acting as a beacon for all subsequent design efforts. It should articulate the core problems in a way that centers on the user’s experience, capturing the essence of what needs to be solved without dictating the form that solutions should take. Importantly, this problem statement is not about the goals of a product or service but rather about the human need or issue at its heart. It sets the stage for ideation by framing the problem in a way that is broad enough to invite creative exploration yet specific enough to ensure relevance and focus.
Ensuring that the problem definition is conducive to ideation is the final piece of the puzzle. The definition must be crafted in such a way that it opens up a space for brainstorming and innovation, inviting team members and stakeholders to think broadly about potential solutions. It should be presented in clear, accessible language that inspires and facilitates creative thinking. This approach not only makes it easier to generate a wide array of ideas but also ensures that the solutions developed are deeply aligned with the user’s needs and experiences. By navigating the complex journey from observation to a well-defined problem statement, teams lay the groundwork for designing solutions that are truly effective and human-centered, paving the way for real and meaningful innovation.
Stage 3: Ideation
Ideation is the stage in the Design Thinking process where creativity truly comes to the forefront. After delving deep into user research and defining clear, human-centric problem statements, teams are primed to generate a breadth of solutions that could address the core issues identified. This phase is characterized by its openness to exploration and the encouragement of innovative thinking, leveraging the insights and understandings developed during the earlier stages.
As teams embark on ideation, they often begin by revisiting the results of their observation analysis and definitions. This retrospective is crucial, as it ensures that all ideas generated are deeply rooted in the real needs and challenges of the users. With a solid understanding of the problem landscape fresh in their minds, teams are better equipped to think outside the box and propose truly innovative solutions.
To foster creativity, a variety of ideation techniques are employed. These might include brainstorming sessions, where the emphasis is on quantity over quality, encouraging participants to voice all ideas, no matter how outlandish they may seem. Other strategies, like sketching, mind mapping, or the use of scenarios, help in visualizing potential solutions and exploring different facets of the problems at hand. The goal of these techniques is to create a rich tapestry of possible solutions, drawing from the diverse perspectives and expertise within the team.
A key principle of the ideation stage is to generate as many ideas as possible at the outset. This approach is grounded in the belief that creativity is a numbers game; the more ideas put forth, the higher the chance of uncovering truly groundbreaking solutions. It’s a process that values breadth and diversity, encouraging participants to push beyond their initial thoughts and explore a wide array of potential solutions.
Once a substantial pool of ideas has been created, the next step is to sift through these and choose the best ones to move forward with. This selection process is critical and requires careful consideration. Teams evaluate ideas based on criteria such as feasibility, impact, and how well they address the user needs identified in the problem statement. This phase often involves robust discussions and debates, as the team collaborates to narrow down the options to those with the most potential.
By engaging in this iterative process of generating a broad array of ideas and then honing in on the most promising ones, teams are able to move forward with solutions that are not only creative and innovative but also deeply aligned with the needs of their users. The ideation stage is where possibilities are expanded, then refined, setting the stage for the prototyping and testing phases that follow.
Stage 4: Prototype
The Prototyping stage in the Design Thinking process is where concepts start to come to life. This phase is about translating the innovative ideas generated during the ideation stage into tangible, scaled-down versions of the product, service, or feature. The aim here is not to develop a finished product but to create prototypes that are inexpensive and quick to produce, enabling the team to explore how their ideas function in the real world.
Prototypes vary in their level of sophistication; they can range from simple mockups made from cardboard or paper to more interactive digital models. Regardless of the medium, the goal is to materialize concepts so that they can be shared, tested, and iterated upon. Initially, prototypes are often shared within the design team itself, allowing for quick feedback and adjustments. However, to gain broader insights, these prototypes are also tested with other departments or with a small group of people outside the design team. This external testing is crucial as it brings fresh perspectives and can uncover unforeseen issues or reactions.
Prototyping serves multiple purposes. Primarily, it helps to identify the best possible solution for each of the problems identified in earlier stages. By investigating how users interact with the prototypes, the team can accept, improve, or reject ideas based on their viability and effectiveness. This process of trial and error is invaluable, as it significantly reduces the risks associated with launching a new product or service.
Moreover, prototyping offers insights into the product’s limitations and the challenges it may face upon full-scale production and release. It’s a chance to preemptively solve problems and refine the design in a low-stakes environment. By observing real users as they engage with the prototype, the team gains a better understanding of how the product fits into the user’s life. This includes how users would behave, think, and feel when interacting with the end product, providing critical data that can inform further development.
Ultimately, the Prototyping stage is about learning and refinement. It gives designers and developers a clearer view of the product’s strengths and weaknesses, allowing them to make informed decisions about what features to keep, modify, or abandon. Through this iterative process of building, sharing, and testing, teams move closer to creating solutions that are not only innovative but also deeply resonant with the needs and expectations of their target audience.
Stage 5: Test your solutions
The Testing stage is where ideas, now embodied in high-fidelity prototypes, undergo rigorous evaluation to ensure they meet the users’ needs effectively. This phase is critical because it’s here that the team validates the assumptions and decisions made throughout the earlier stages, from understanding user needs to ideating and prototyping solutions.
The process begins by rigorously testing the complete product, incorporating the best solutions identified during the prototyping phase. This means exposing the product to real-world scenarios and users to observe its performance in the conditions it was designed for. The testing phase is comprehensive, assessing not just the functionality and usability of the product but also its appeal and value to the intended users. This can involve a variety of methods, including user testing sessions, beta releases, and pilot programs, depending on the nature of the product and the resources available.
An essential part of this stage is the collection of metrics. Metrics can range from quantitative data, such as completion rates for specific tasks or the number of errors encountered, to qualitative feedback, such as user satisfaction and ease of use. Collecting a broad spectrum of data is crucial for a thorough evaluation of the product. This data not only indicates whether the product meets its intended goals but also highlights areas that may require further refinement.
Analyzing the collected data is where insights are drawn and decisions are made. The analysis involves looking beyond the surface-level reactions to understand the underlying reasons for users’ responses. It’s about piecing together a comprehensive picture of the product’s performance, identifying patterns and outliers in the data. This step often requires a multidisciplinary approach, combining expertise from design, engineering, and business perspectives to ensure a balanced evaluation of the product.
The Testing stage is iterative, much like the rest of the Design Thinking process. Insights gained from testing can lead back to earlier stages, whether it’s revising the problem definition, generating new ideas, or modifying prototypes. This cyclical approach ensures that the product continues to evolve in response to user feedback, enhancing its relevance and effectiveness.
Ultimately, the goal of the Testing phase is to refine the product until it not only solves the user’s problems but does so in a way that is engaging, efficient, and enjoyable. By rigorously testing and analyzing the product against the needs and expectations of its users, teams can ensure that their solutions are not just viable but truly valuable to those they aim to serve.
Stage ∞: Iterate
The Iteration phase underscores a fundamental principle of Design Thinking: the process is inherently flexible and non-linear. While the stages of Design Thinking are often presented in a sequential order — Empathize, Define, Ideate, Prototype, and Test — the reality of applying these stages in practice is far more dynamic. This adaptability is crucial for fostering innovation and ensuring solutions truly meet user needs.
Iteration recognizes that the results from the Test stage, and indeed insights from any stage, may reveal new information that necessitates a return to previous steps. It is not uncommon for testing to uncover unexpected user behaviors or feedback that challenges initial assumptions. Such revelations are invaluable, as they provide a deeper understanding of the problem space or indicate new directions for solution development.
As a result, stages of the Design Thinking process might be switched, conducted concurrently, or repeated multiple times. For instance, prototyping might begin concurrently with ideation to rapidly explore a concept, or the definition stage might be revisited after prototyping reveals a misunderstanding of the user’s needs. This flexibility allows teams to respond quickly to new insights, adapting their approach to ensure the development of more effective and user-centric solutions.
Moreover, knowledge acquired in the latter stages of the process can significantly inform repeats of earlier stages. Insights gained during testing can lead to a reevaluation of the problem statement defined at the outset, or feedback on a prototype might spark new ideas that require further exploration. This cyclical process of learning and refining is a key strength of Design Thinking. It ensures that solutions are not only based on initial understandings but are continually refined to better meet user needs as those needs are understood more deeply.
Iteration is, therefore, not just a phase but a mindset that permeates the Design Thinking process. It embraces the understanding that designing effective solutions is an evolving journey rather than a linear path. By allowing for flexibility, concurrent activities, and repeated cycles, teams can navigate the complexities of user needs and technological possibilities, leading to solutions that are innovative, impactful, and deeply aligned with the human experience.
Summary
Design Thinking is a human-centric, iterative approach to problem-solving that prioritizes empathy, creativity, and iterative learning to develop solutions that deeply resonate with users.
The Design Thinking process is a powerful framework for tackling complex problems, characterized by its user-centric focus and iterative approach. By empathizing with users, defining problems clearly, generating innovative solutions, and continuously refining these solutions based on real-world feedback, teams can develop products and services that truly meet user needs and enhance their lives.
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