Context-Aware User Experience in Mobile Design

YouTube just added fun animations to their like button. Most Designers are overlooking the big design win. Here's what it teaches about smart interfaces? 👇🏼 Take a look at YouTube's latest update rolling out now. Across the platform, when you hit like on a video, the button doesn't just glow. It transforms with a quick, playful animation. But it's not random. Each one matches the video's genre. ✈️ For a travel clip? A tiny airplane flies off the screen. 🚗 Cars or racing? A spinning tire with smoke. 💡Educational stuff? A bright lightbulb pops up. Why go this far? YouTube knows one-size-fits-all buttons bore users. These 20 genre-specific animations- covering sports like basketball or soccer, pets like cats and dogs, cooking, music, horror, and more- make every like feel personal and rewarding. It's a simple micro-interaction that boosts engagement without cluttering the UI. Part of their October redesign, it keeps things immersive and fun, just for longer videos. One button. Endless contexts. Adding to Delight. Here's what most UI/UX designers get wrong about adaptive design: They think interfaces should stay static to feel "clean." But real user-centered design adapts on the fly: 👉🏼 A like button in a fitness app could pulse like a heartbeat for workout vids. In e-commerce? It might sparkle for product reviews. 👉🏼 Music players use waveforms for songs but grids for playlists- context changes everything. 👉🏼 Gaming UIs glow with energy during action modes. For calm meditation apps? They fade softly to avoid overwhelm. The uncomfortable truth: 👉🏼 Your "simple" design isn't simple if it ignores user context. 👉🏼 What delights in one scenario (like a flashy animation) might annoy in another (say, a serious news feed). 👉🏼 YouTube didn't just add eye candy. They proved micro-interactions build habits. 👉🏼 Good UI isn't about looking pretty- it's about feeling alive for the user. The real question for designers building digital products: Are you creating static screens? Or experiences that respond to the moment? Because one keeps users scrolling. The other keeps them hooked. What's a feature you've experienced recently that surprised you? Follow Rohan Mishra for more such content.

💻 Designing for a user who is moving at 30km/h is a reality check for any UX Designer. I’m currently deep in the wireframing stage for our Rider App, and it’s a masterclass in Anticipatory Design. When you design for delivery partners, the "happy path" doesn't happen in a quiet office. It happens in the rain, in heavy traffic, and under tight deadlines. To make the experience feel seamless, I’m focusing on three things: 🎖️Reducing Cognitive Load: A rider shouldn't have to "think" about the next step. The app should anticipate it. If they just arrived at the store, the order ID should already be front and center. 🎖️Glanceable UI: Information architecture is life or death. I’m stripping away every non-essential pixel so they can get the data they need in a 0.5-second glance. 🎖️Contextual Triggers: Using anticipatory logic to surface the "Contact Customer" button only when they are within 100 meters of the drop-off point. 🥅 The goal? To move from "reactive" tools to "proactive" partners. We aren't just building an app; we're building a tool that respects their time and safety. It’s a tough task to build from scratch, but seeing a wireframe solve a real-world frustration is why I love Product Design. 🤘To my fellow designers: Have you ever had to design for a "non-desk" environment? What was your biggest takeaway? 👇 #ProductDesign #UXPsychology #AnticipatoryDesign #Logistics #UserExperience #harishux

Do you really know who you're designing for? It's easy to bucket users up into the same user type and talk about them as if they're all the same person We say things like: Our users are Patients and Doctors. Patients need XX, Doctor's pains are YY But one patient isn't the same as another. So why do we design like they are? Or, often the user stays the same, but they shift between different states (sometimes within the same day) depending on their context. For example, I might cook for myself at lunch, but cook for my family at dinner. I'm the same person, using the same app, but I have different needs. Considering and designing for the the needs / goals / pain for the overall user type starts to feel generic, and disconnected from the world people actually experience That's why I like to use lenses. (It's a way of considering things from different perspectives). Each lens includes a description, needs, behaviours, emotions, pains and a key principle to remember For me personally, using lenses feels less static and more representative of the fluidness of designing for people on the other side of the glass Going back to the cooking example, the user type might be "at-home cooks" but we can break it down into multiple lenses. Some lenses we might have are: → By social context: solo lens vs family lens → By emotional state: The mid-week panic → By experience level: Learning / low confidence lens → By environment: Small kitchen lens vs well equipped There will naturally be overlaps in lens needs, for example, someone that's high confidence cook might also have a well equipped kitchen. Or the family lens might be linked to the mid-week panic. The great thing is how to see where needs overlap and where there's additional needs or conflicts. That way, we can be more intentional about how we're designing Here's a few ways I like to use lenses: → In journeys to see how needs change across contexts → When designing to see where the design works / fails → When scoping to see overlaps / conflicts in needs → In research prep to guide around different contexts → When testing to consider different states & scenarios → In design reviews to challenge our assumptions → When scoping to consider what we will / won't explore

After talking with over 50 users of our competitors, we noticed a common theme: their products are too static. Today's users are seeking experiences that adapt to their behaviors, providing tailored, dynamic interactions, particularly as AI technology advances. Everyone expects immediate value - they desire proactive solutions that anticipate their needs before they even ask. For instance, with Nevemind : - Who should I reach out to this week to close my sales quota? - Which important emails have I overlooked? - What key insights am I missing about my network today? Additionally, there's a growing preference for more defined, streamlined experiences over broad, vague ones. Users appreciate being guided consistently from the moment they onboard. This shift is evident in many apps like Delta (portfolio analytics), BeReal., Snap Inc., Duolingo, and Wordle, which not only meet these preferences but also guide users through their interactions. The trend towards personalized, anticipatory technology is apparent and seems set to continue shaping user expectations and product development. #AI #UserExperience #

Users are not all the same, and they are not even the same version of themselves across moments. A beginner opening a product for the first time, an experienced user coming back to finish a task, and a frustrated user trying to recover from an error do not need the same interface, the same guidance, or the same recommendation. Contextual bandits offer a practical way for products to learn which experience to show, for which user, in which moment. It uses available context, such as prior behavior, device, timing, or session signals, to choose among alternatives, then learns from feedback like clicks, completion, dwell time, or return behavior. In simple terms, the product does not just personalize once. It keeps learning which choice works better under different conditions. UX researchers can use it to shift personalization from a static design decision into an ongoing learning process. It opens the door to more adaptive onboarding, smarter help systems, better recommendation logic, more thoughtful notification timing, and even interface changes that reflect what a user seems to need right now rather than what the team assumed months ago. Contextual bandits are more responsive than standard A/B testing because they do not wait until the experiment ends before adjusting. They are more interactive than ordinary supervised learning because they actively choose what to show and learn from that choice. And they are often simpler than full reinforcement learning because they focus on one decision at a time rather than modeling an entire long sequence of future states. That makes them much more realistic for many digital product problems. Of course, this is not magic. The system still depends on the quality of the context you collect, the reward you define, and the care with which you balance exploration and exploitation. If you optimize the wrong outcome, you can create a product that gets more clicks while making the experience worse. If you explore too aggressively, you may damage trust. If you ignore fairness and transparency, adaptation can become harmful.

Designing faster intent flows with Contextual prompts Part-3 ⚡️ As AI-powered search becomes more common on Perplexity and ChatGPT, I’ve observed something worth exploring. Most user queries fall into 4–5 predictable buckets. If AI systems can predict intent, why not surface smart contextual prompts to reduce friction and accelerate time-to-first-value? 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝟰 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 where contextual workflows could be super helpful 🛍️ 𝗦𝗲𝗮𝗿𝗰𝗵𝗶𝗻𝗴 𝗳𝗼𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀 Instead of vague results, the prompt box adapts to surface inputs like: → Terrain (Road, Trail, Mixed) → Intensity (Jogging, Marathon, Speedwork) → Cushioning / Support These behave like stacked chips, helping the AI narrow down suggestions quickly. 🍜 𝗦𝗲𝗮𝗿𝗰𝗵𝗶𝗻𝗴 𝗹𝗼𝗰𝗮𝗹𝗹 User query: “Good restaurants nearby” What the UI does: Location-aware suggestions pop up instantly with prompts like: → Cuisine type (North Indian, Korean, etc.) → Meal time (Lunch / Dinner / Now) → Ambience filters (Rooftop, Family, Pet-friendly) This mode blends radial proximity selectors with chip-based filters. 📈 𝗦𝗲𝗮𝗿𝗰𝗵𝗶𝗻𝗴 𝘀𝘁𝗼𝗰𝗸 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 User query: “Tesla stock run news” What the UI does: Presents a dynamic context box with: → Price chart (1D/5D toggle) → “What’s driving this move?” news chips → Comparison with Nasdaq or other sources Perfect for traders or curious investors tracking a stock in real time. 🧠 𝗦𝗲𝗮𝗿𝗰𝗵𝗶𝗻𝗴 𝗳𝗼𝗿 𝗲𝘅𝗽𝗹𝗮𝗻𝗮𝘁𝗶𝗼𝗻𝘀 User query: “What is AI UX?” What the UI does: After detecting an “explain” intent, the system offers: → The length of answer → Target audience → Format types etc.  All as selectable pills to shape the tone, depth, and delivery. These micro-interactions, if designed well, can transform how we search, shop, learn, and explore with AI. #GenerativeAI #productmanagement #ProductDesign #uiux #DesignThinking #ArtificialIntelligence

What if an interface could adapt to your world in real time? Imagine your car’s dashboard subtly shifting to shades of green as you drive through a forest, or an app adjusting to your personal accessibility needs without breaking. For the past few months, I've spoken with many of you and I’ve realized we’re all working toward the same ambitious goal: creating interfaces that offer a seamless blend of brand personalization, true adaptability, and accessibility. This is about building an experience that is not only true to a brand's perception but is also tailored to our individual needs as consumers. My exploration so far has revealed three foundational concepts that I feel are important to make this a reality. In the upcoming months, I’ll be sharing our journey as we explore these concepts. Some ideas will work, some will fail. I don’t know where this path will lead, but I want to bring you along in the process. 1.⁠ ⁠Contextual Awareness This is the idea that an element understands its environment. A button, for example, knows what surface it’s sitting on and adapts accordingly. While tools like Figma use variable collections to simulate this, the approach is often fragile because it lacks a scalable underlying logic. This very challenge was a driving force behind developing the graph engine. I’m excited to share that a solution for this is now possible directly in modern browsers with pure CSS, laying a powerful and scalable foundation for the future. 2.⁠ ⁠Content Awareness Imagine an interface that reflects the content it displays. We see a version of this in Spotify’s UI, which adapts to album art to create a more immersive experience. This principle allows the UI to react dynamically, personalizing the experience in real-time based on its content. 3.⁠ ⁠User Awareness This pillar brings it all together by focusing on the user’s specific needs. It means designing systems that can respond to a user with Parkinson’s who may need more forgiving interaction areas, or accommodating the universal reality that as we get older, we need larger fonts. The key is to make these adjustments without breaking the interface or compromising the brand experience. These three pillars form the blueprint for the next generation of user interfaces. By understanding where an element is, what it contains, and who is using it, we can create experiences that feel truly alive. I think there’s more to discover beyond our current methods. Let's explore what it means to build something truly adaptive, together.

From GenAI to GenUI We’re witnessing a shift as significant as the leap from MS-DOS to graphical user interfaces. The AI era marks our latest upgrade in how we interact with technology. For decades, we designed for workflows and specific actions. Everything was deterministic. Behind every interface sat a flowchart, with logic carefully coded. The backend made decisions, and the frontend rendered them. This model worked because we could predict every path a user might take. With agents, this paradigm breaks down. Text alone isn’t sufficient anymore. Chat works for conversation, but interaction demands something more. We need to engage with agents, not just talk to them. Reasoning state and intent become critical factors in the exchange. LLMs can now generate UI, and this capability feels like natural progression. Model Context Protocol enables mini-apps to emerge on the fly, no longer bound by deterministic rules. This opens the door to genuine hyper-personalization. We’ve moved from designing screens to designing for outcomes. Agents now dynamically assemble workflows based on intent, available data, and accessible tools. The fact that agents can create interfaces without traditional designers and developers is revolutionary. We can finally shift from UI-centric thinking to truly user-centered experience design. This fundamentally transforms the designer’s role. We’re no longer pixel pushers or interface assemblers. The work of arranging buttons, spacing elements, and crafting individual screens can now be handled by agents. Instead, designers become architects of experience, defining the principles, guardrails, and intent that shape how agents respond. We set the boundaries of possibility, orchestrate the logic of interaction, and ensure coherence across dynamic, personalized experiences. Our canvas expands from static screens to adaptive systems. We design the intelligence behind the interface, the relationships between user needs and agent capabilities, the quality standards that govern generated UIs. We curate outcomes rather than outputs. The ability to adapt, reorganize, and respond to both user intent and application context is transformative. With reasoning and action combined, agents can generate dynamic artifacts that enable interaction, not merely conversation. What a time to be alive as a designer! 🫶 #ai

✨ Transforming Information into Experience ✨ What looks like just an “order details” page can make or break a customer’s journey. On the left (Before UX) ➡️ Plain text, hard to scan, no hierarchy, no visuals. Users have to read line by line just to understand their order. On the right (After UX) ➡️ Clear structure, visual hierarchy, and context-rich details. A user instantly knows: ✅ Where the food is coming from (restaurant info with logo & address) ✅ What’s ordered (with order ID & image) ✅ Delivery status & time expectation ✅ Pickup & drop-off details with map-style markers ✅ Delivery partner info with quick action buttons This isn’t just about making things “look pretty” — it’s about reducing cognitive load, enhancing trust, and giving control back to the user. A small design shift can transform a bland experience into a seamless, delightful journey. Good UX = Less confusion, more clarity, and happier users. 🚀 #UIDesign #UXDesign #BeforeAndAfterUX #UserExperience #DesignThinking #UXCaseStudy #UIUX #ProductDesign #UserCenteredDesign #DigitalExperience #InteractionDesign #DesignMatters #UXJourney #GoodDesign

Why does the iPhone sometimes let you decline a call and other times forces you to slide and pray for strength? Simple. Because context changes the interface. If your phone is unlocked, you get choices. If it is locked, you get fate. This is a perfect example of how small UX decisions shape real human behavior. When you remove an action, you remove agency. When you remove agency, you change emotions. And in this case, the emotion is usually “why am I being punished.” Good UX is not just about screens. It is about power. It is about giving the user control at the exact moment they need it. It is about reducing friction when someone is already stressed, busy, or human.