User Experience

Invisible UX is coming 🔥 And it’s going to change how we design products, forever. For decades, UX design has been about guiding users through an experience. We’ve done that with visible interfaces: Menus. Buttons. Cards. Sliders. We’ve obsessed over layouts, states, and transitions. But with AI, a new kind of interface is emerging: One that’s invisible. One that’s driven by intent, not interaction. Think about it: You used to: → Open Spotify → Scroll through genres → Click into “Focus” → Pick a playlist Now you just say: “Play deep focus music.” No menus. No tapping. No UI. Just intent → output. You used to: → Search on Airbnb → Pick dates, guests, filters → Scroll through 50+ listings Now we’re entering a world where you guide with words: “Find me a cabin near Oslo with a sauna, available next weekend.” So the best UX becomes barely visible. Why does this matter? Because traditional UX gives users options. AI-native UX gives users outcomes. Old UX: “Here are 12 ways to get what you want.” New UX: “Just tell me what you want & we’ll handle the rest.” And this goes way beyond voice or chat. It’s about reducing friction. Designing systems that understand intent. Respond instantly. And get out of the way. The UI isn’t disappearing. It’s mainly dissolving into the background. So what should designers do? Rethink your role. Going forward you’ll not just lay out screens. You’ll design interactions without interfaces. That means: → Understanding how people express goals → Guiding model behavior through prompt architecture → Creating invisible guardrails for trust, speed, and clarity You are basically designing for understanding. The future of UX won’t be seen. It will be felt. Welcome to the age of invisible UX. Ready for it?

🗺️ AirBnB Customer Journey Blueprint, a wonderful practical example of how to visualize the entire customer experience for 2 personas, across 8 touch points, with user policies, UI screens and all interactions with the customer service — all on one single page. AirBnB Customer Journey (Google Drive): https://lnkd.in/eKsTjrp4 Spotify Customer Journey (High-res): https://lnkd.in/eX3NBWbJ Now, unlike AirBnB, your product might not need a mapping against user policies. However, it might need other lanes that would be more relevant for your team. E.g. include relevant findings and recommendations from UX research. List key actions needed for next stage. Add relevant UX metrics and unsuccessful touchpoints. That last bit is often missing. Yet customer journeys are often non-linear, with unpredictable entry points, and integrations way beyond the final stage of a customer journey map. It’s in those moments when things leave a perfect path that a product’s UX is actually stress tested. So consider mapping unsuccessful touchpoints as well — failures, error messages, conflicts, incompatibilities, warnings, connectivity issues, eventual lock-outs and frequent log-outs, authentication issues, outages and urgent support inquiries. Even further than that: each team could be able to zoom into specific touch points and attach links to quotes, photos, videos, prototypes, design system docs and Figma files. Perhaps even highlight the desired future state. Technical challenges and pain points. Those unsuccessful states. Now, that would be a remarkable reference to use in the beginning of every design sprint. Such mappings are often overlooked, but they can be very impactful. Not only is it a very tangible way to visualize UX, but it’s also easy to understand, remember and relate to daily — potentially for all teams in the entire organization. And that's something only few artefacts can do. Useful resources: Free Template: Customer Journey Mapping, by Taras Bakusevych https://lnkd.in/e-emkh5A Free Template: End-To-End User Experience Map (Figma), by Justin Tan https://lnkd.in/eir9jg7J Customer Journey Map Template (Figma), by Ed Biden https://lnkd.in/evaUP4kz Free Figma/Miro User Journey Maps Templates https://lnkd.in/etSB7VqB User Journey Maps vs. Service Blueprints (+ Templates) https://lnkd.in/e-JSYtwW UX Mapping Methods (+ Miro/Figma Templates) https://lnkd.in/en3Vje4t #ux #design

These days everyone wants to be a #SuperApp but only a handful have managed to succeed. Those who have share one common denominator: monetization. Let’s see how it can be done. Here is my summary of the most successful strategies: 1.  An ecosystem play – as opposed to providing mere access to an array of different services – with seamless, integrated, end-to-end experience across all aspects of modern life. 2.  #Payments as the undisputed underlying layer that acts as a connecting base for the multitude of offerings on the platform. 3.  A wide range of integrated payment methods catering for different use cases and target audiences (P2P, BNPL, money transfer, instant payments, online payments, QR codes, etc). 4.  Low customer acquisition costs as a direct result of the platform play and then up-selling and cross-selling of high-margin financial offerings (i.e. lending, investment, insurance, e-commerce, digital #banking) and merchant added-value services (i.e. merchant financing, collection technology platform). 5.  #Data as the predominant tool for driving high engagement with tailor-made offerings that transformed how, when and in which context services are offered. 6.  A two-sided consumer and merchant ecosystem with the platform acting as the bridge that not only connects the two sides but fuels growth from one to the other in an open, two-way dynamic relationship. In such a set-up platform engagement (consumer side) enables merchant growth creating a self-reinforcing loop based on high frequency and high repeat rates that lead to consumer stickiness and retention. 7. Software and cloud services to a range of B2B partners (enterprises, telecoms, digital platforms, fintechs), which act not only as a platform amplifier but also as multiplier of customer engagement that unlocks additional customer data points and insights. 8.  A subscription-led ecosystem for merchants: the platform becomes the enabling layer for partners, merchants and other tech providers to accept payments through a wide variety of instruments, including subscription-based models that create permanent revenue and stickiness. 9.  Help merchants drive revenue growth via marketing channels: merchants sell discount deals, gift vouchers and other digital goods like tickets to platform users. 10.  Leverage a network of banks and other FS providers to expand distribution channels. 11.  First-mover integration advantage with the local ecosystem. Paytm was, for example, the first app to launch UPI Lite in India and has subsequently enabled wallet interoperability that allowed full KYC Paytm Wallets to be universally acceptable on all UPI QR codes and online merchants. Opinions: my own, Graphic source: Paytm quarterly reports Subscribe here to my newsletter: https://lnkd.in/dkqhnxdg

New! We’ve published a new set of automated evaluations and benchmarks for RAG - a critical component of Gen AI used by most successful customers today. Sweet. Retrieval-Augmented Generation lets you take general-purpose foundation models - like those from Anthropic, Meta, and Mistral - and “ground” their responses in specific target areas or domains using information which the models haven’t seen before (maybe confidential, private info, new or real-time data, etc). This lets gen AI apps generate responses which are targeted to that domain with better accuracy, context, reasoning, and depth of knowledge than the model provides off the shelf. In this new paper, we describe a way to evaluate task-specific RAG approaches such that they can be benchmarked and compared against real-world uses, automatically. It’s an entirely novel approach, and one we think will help customers tune and improve their AI apps much more quickly, and efficiently. Driving up accuracy, while driving down the time it takes to build a reliable, coherent system. 🔎 The evaluation is tailored to a particular knowledge domain or subject area. For example, the paper describes tasks related to DevOps troubleshooting, scientific research (ArXiv abstracts), technical Q&A (StackExchange), and financial reporting (SEC filings). 📝 Each task is defined by a specific corpus of documents relevant to that domain. The evaluation questions are generated from and grounded in this corpus. 📊 The evaluation assesses the RAG system's ability to perform specific functions within that domain, such as answering questions, solving problems, or providing relevant information based on the given corpus. 🌎 The tasks are designed to mirror real-world scenarios and questions that might be encountered when using a RAG system in practical applications within that domain. 🔬 Unlike general language model benchmarks, these task-specific evaluations focus on the RAG system's performance in retrieving and applying information from the given corpus to answer domain-specific questions. ✍️ The approach allows for creating evaluations for any task that can be defined by a corpus of relevant documents, making it adaptable to a wide range of specific use cases and industries. Really interesting work from the Amazon science team, and a new totem of evaluation for customers choosing and tuning their RAG systems. Very cool. Paper linked below.

Adaptive seating solutions for individuals with disabilities leverage a variety of technologies to enhance comfort, mobility, and overall well-being. Amazing innovation? Some of the technologies commonly incorporated into these solutions include: Pressure Redistribution Technology: Purpose: To prevent pressure sores and enhance comfort. Examples: Air-cell-based cushions, gel cushions, memory foam. Smart Fabrics and Materials: Purpose: Provide flexibility, support, and enhance durability. Examples: Fabrics with moisture-wicking properties, anti-microbial materials. Powered Mobility Devices: Purpose: Enhance independent mobility. Examples: Electric wheelchairs, motorized scooters. Positioning Technology: Purpose: Support proper posture and alignment. Examples: Customizable seating components, tilt and recline features. Sensors and IoT Connectivity: Purpose: Monitor user comfort, health, and usage patterns. Examples: Pressure sensors, temperature sensors, IoT-connected devices. Assistive Technology Integration: Purpose: Enhance user control and interaction. Examples: Switch interfaces, sip-and-puff controls, eye-gaze technology. Customizable and 3D Printing: Purpose: Tailor solutions to individual needs. Examples: 3D-printed components for personalized fittings. Power-Assist Technology: Purpose: Aid manual wheelchair users. Examples: Electric add-on devices for manual wheelchairs. Vibration and Massage Features: Purpose: Improve circulation and reduce muscle tension. Examples: Seating with built-in massage or vibration elements. Advanced Cushioning Systems: Purpose: Provide optimal support and pressure distribution. Examples: Air-cell-based systems with adjustable firmness. Remote Control and Apps: Purpose: Allow users to adjust settings and monitor usage. Examples: Smartphone apps for controlling powered devices. Ergonomic Design Principles: Purpose: Ensure comfort and accessibility. Examples: Contoured shapes, adjustable components. Biometric Feedback Systems: Purpose: Monitor physiological indicators for health. Examples: Heart rate monitors, biofeedback systems. #innovation #mobility

Stop pasting interview transcripts into ChatGPT and asking for a summary. You’re not getting insights—you’re getting blabla. Here’s how to actually extract signal from qualitative data with AI. A lot of product teams are experimenting with AI for user research. But most are doing it wrong. They dump all their interviews into ChatGPT and ask: “Summarize these for me.” And what do they get back? Walls of text. Generic fluff. A lot of words that say… nothing. This is the classic trap of horizontal analysis: → “Read all 60 survey responses and give me 3 takeaways.” → Sounds smart. Looks clean. → But it washes out the nuance. Here’s a better way: Go vertical. Use AI for vertical analysis, not horizontal. What does that mean? Instead of compressing across all your data… Zoom into each individual response—deeper than you usually could afford to. One by one. Yes, really. Here’s a tactical playbook: Take each interview transcript or survey response, and feed it into AI with a structured template. Example: “Analyze this response using the following dimensions: • Sentiment (1–5) • Pain level (1–5) • Excitement about solution (1–5) • Provide 3 direct quotes that justify each score.” Now repeat for each data point. You’ll end up with a stack of structured insights you can actually compare. And best of all—those quotes let you go straight back to the raw user voice when needed. AI becomes your assistant, not your editor. The real value of AI in discovery isn’t in writing summaries. It’s in enabling depth at scale. With this vertical approach, you get: ✅ Faster analysis ✅ Clearer signals ✅ Richer context ✅ Traceable quotes back to the user You’re not guessing. You’re pattern matching across structured, consistent reads. ⸻ Are you still using AI for summaries? Try this vertical method on your next batch of interviews—and tell me how it goes. 👇 Drop your favorite prompt so we can learn from each othr.

Clean code is nice. But scalable architecture? That’s what makes you irreplaceable. Early in my journey, I thought “writing clean code” was enough… Until systems scaled. Teams grew. Bugs multiplied. That’s when I discovered Design Patterns, and things started making sense. Here’s a simple breakdown that can save you hundreds of hours of confusion. 🔷 Creational Patterns: Master Object Creation These patterns handle how objects are created. Perfect when you want flexibility, reusability, and less tight coupling. 💡 Use these when: You want only one instance (Singleton) You need blueprints to build complex objects step-by-step (Builder) You want to switch object types at runtime (Factory, Abstract Factory) You want to duplicate existing objects efficiently (Prototype) 🔷 Structural Patterns: Organise the Chaos Think of this as the architecture layer. These patterns help you compose and structure code efficiently. 💡 Use these when: You’re bridging mismatched interfaces (Adapter) You want to wrap and enhance existing objects (Decorator) You need to simplify a complex system into one entry point (Facade) You’re building object trees (Composite) You want memory optimization (Flyweight) You want to control access and protection (Proxy, Bridge) 🔷 Behavioural Patterns: Handle Interactions & Responsibilities These deal with how objects interact and share responsibilities. It’s about communication, delegation, and dynamic behavior. 💡 Use these when: You want to notify multiple observers of changes (Observer) You’re navigating through collections (Iterator) You want to encapsulate operations or algorithms (Command, Strategy) You need undo/redo functionality (Memento) You need to manage state transitions (State) You’re passing tasks down a chain (Chain of Responsibility) 📌 Whether you're preparing for interviews or trying to scale your application, understanding these 3 categories is a must: 🔹 Creational → Creating Objects 🔹 Structural → Assembling Objects 🔹 Behavioral → Object Interaction & Responsibilities Mastering these gives you a mental map to write scalable, reusable, and testable code. It’s not about memorising them, it's about knowing when and why to use them. #softwareengineering #systemdesign #linkedintech #sde #connections #networking LinkedIn LinkedIn News India

Clinicians don’t want more data. They want fewer decisions. HealthTech keeps confusing complexity with sophistication. We assume that because clinicians are smart, they want more dashboards. More alerts. More choices. In truth, they want something no algorithm can measure: Cognitive relief. Imagine you’re a pilot. Mid-flight, you’re shown 17 new dials. Flashing red. Each says something important. Now make a life-or-death decision. Fast. Would you say thank you? That’s what most clinical decision support looks like in HealthTech today. And it’s killing trust faster than bad data ever could. Why? Because information isn’t value. Clarity is. The problem, IMO, isn’t the number of alerts. It’s the hidden cost of each micro-decision. Every time we ask a clinician to interpret another data stream, we’re not helping them, we’re taxing them. It’s not death by data. It’s death by 1,000 cognitive cuts. We’ve forgotten the difference between data and decision. Between information and insight. Between noise and relevance. And worst of all? We often design for what looks impressive - not what actually works on a ward round. The best HealthTech doesn’t make clinicians feel smarter. It makes them feel safer. Not “empowered.” Not “augmented.” Just calm. Just clear. That’s the gold standard now isn’t it? Tools that remove thinking, not add to it. If you’re building in HealthTech, Don’t ask: “What more can we show?” Ask: “What decisions can we take away?” That’s where trust is built. That’s where burnout is reduced. Build for fewer decisions. What would you add? P.S. Tools that reduce decisions are finally being valued. VCs are rewarding clarity, not complexity. If your AI product calms the chaos - you're building in the right direction - https://lnkd.in/euA2-8a2

I’ve trained in rooms where people speak English, but think in Marathi, Hindi, Bengali, Tamil Same company, same goals, but completely different communication styles. We love patting ourselves on the back for being diverse. But when a South Indian team feels a North Indian manager is "too aggressive," or a Gen Z employee thinks their Gen X boss is "dismissive", we call it a "communication gap." When really it's India's invisible boardroom barrier. Because while communicating, you’re navigating: 🔹 Cultural nuances 🔹 Generational gaps 🔹 Language preferences 🔹 Urban vs regional perspectives And if you're not adapting, you’re alienating. Here's my 3A’s of Cross-cultural communication framework: 1. Awareness: Recognize that your communication style is shaped by region, generation, and upbringing. It's not universal. 2. Adaptation: Match your message to your audience. One style doesn't fit all rooms. 3. Ask: When in doubt, clarify: What does yes mean here? How do you prefer feedback? What's the protocol for disagreement? India's diversity is incredible. But if we are not actively learning to communicate across cultures, not just languages, we're wasting it. P.S. What's your biggest cross-cultural communication struggle? #CrossCulturalCommunication #AwarenessAdaptationAsk #3AsFramework #Awareness #Adaptation #Ask #CommunicationGaps

𝗪𝗲𝗹𝗹𝗻𝗲𝘀𝘀 𝗜𝘀 𝗮 𝗛𝗮𝗯𝗶𝘁. 𝗬𝗼𝘂𝗿 𝗦𝘂𝗯𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻 𝗦𝗵𝗼𝘂𝗹𝗱 𝗕𝗲 𝗧𝗼𝗼. If customers love your product but still cancel, the problem isn’t the product—it’s the experience. The best wellness brands don’t just sell products. They guide behaviours, reinforce habits, and remove friction. But too often, small moments of friction— a failed payment, a forgotten renewal, a skipped order— quietly push customers away before they even realize it. That’s why I put this table together. 7 high-impact automations that keep subscribers engaged, reduce churn, and make retention effortless. Each one removes a key retention blocker before it turns into lost revenue. 1️⃣ 𝗣𝗮𝘆𝗺𝗲𝗻𝘁 𝗙𝗮𝗶𝗹𝘂𝗿𝗲𝘀 → 𝗜𝗻𝘀𝘁𝗮𝗻𝘁 𝗥𝗲𝗰𝗼𝘃𝗲𝗿𝘆 ↳ Trigger: Payment fails (Recharge) ↳ Action: SMS + Email with urgency & FOMO ↳ Apps: SMSBump, Klaviyo → Catch failed payments before they cancel 2️⃣ 𝗨𝗽𝗰𝗼𝗺𝗶𝗻𝗴 𝗥𝗲𝗻𝗲𝘄𝗮𝗹𝘀 → 𝗕𝗲𝗻𝗲𝗳𝗶𝘁 𝗥𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 ↳ Trigger: Renewal approaching (Recharge) ↳ Action: Email & SMS reinforcing product value ↳ Apps: Klaviyo, PostPilot → Remind customers why they subscribed 3️⃣ 𝗟𝗼𝘄 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 → 𝗥𝗲-𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗙𝗹𝗼𝘄 ↳ Trigger: Skipped orders, no logins, inactivity (CustomerHub) ↳ Action: ‘Reignite Your Routine’ email series ↳ Apps: Klaviyo → Help them stay on track before they forget 4️⃣ 𝗖𝗮𝗻𝗰𝗲𝗹𝗹𝗮𝘁𝗶𝗼𝗻 𝗔𝘁𝘁𝗲𝗺𝗽𝘁𝘀 → 𝗦𝗮𝘃𝗲 𝘁𝗵𝗲 𝗦𝗮𝗹𝗲 ↳ Trigger: Customer clicks “Cancel” (Recharge) ↳ Action: “Pause instead of cancel” + Exclusive offer ↳ Apps: Klaviyo, RetentionEngine → Give them a reason to stay 5️⃣ 𝗙𝗶𝗿𝘀𝘁 𝗦𝘂𝗯𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻 𝗢𝗿𝗱𝗲𝗿 → 𝗢𝗻𝗯𝗼𝗮𝗿𝗱𝗶𝗻𝗴 & 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻 ↳ Trigger: First order shipped (Recharge) ↳ Action: Educational onboarding sequence ↳ Apps: Klaviyo, Postscript → Guide them to get the best results 6️⃣ 𝗠𝗶𝗹𝗲𝘀𝘁𝗼𝗻𝗲-𝗕𝗮𝘀𝗲𝗱 𝗥𝗲𝘄𝗮𝗿𝗱𝘀 → 𝗞𝗲𝗲𝗽 𝗧𝗵𝗲𝗺 𝗛𝗼𝗼𝗸𝗲𝗱 ↳ Trigger: 3rd, 6th, or 12th order milestone (LoyaltyLion) ↳ Action: Reward with a discount, gift, or VIP perks ↳ Apps: Smile.io, Klaviyo → Keep them engaged before they churn 7️⃣ 𝗛𝗶𝗴𝗵 𝗟𝗧𝗩 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 → ‘𝗦𝘂𝗿𝗽𝗿𝗶𝘀𝗲 & 𝗗𝗲𝗹𝗶𝗴𝗵𝘁’ ↳ Trigger: Customer hits LTV threshold (Klaviyo) ↳ Action: Personalized gift or early access invite ↳ Apps: PostPilot, LoyaltyLion → Turn subscribers into superfans Subscriptions Should Feel Effortless. Your product builds habits. Your subscription model should too. Set up these workflows once, and let them do the work forever. If you need help with putting any of them together, reach out to me in DM 📥