How Designers can Collaborate With AI

A few months ago, this wasn’t even part of my hiring process. Now it’s one of the first things I look at. Recently, I interviewed two designers for the same role. Both had strong portfolios. Both understood modern UI. Both could use Figma well. But one question changed the entire conversation: “How do you use AI in your design workflow?” One designer said: “I use ChatGPT sometimes for content ideas.” The other designer showed me how they use AI to: turn rough client briefs into structured UX flows generate multiple user journey ideas in minutes speed up UX writing organize research findings improve accessibility checks explore layout directions faster before moving into UI And honestly… The gap was impossible to ignore. Not because AI made them more creative. ↳ But because it made them more efficient. That’s the shift happening right now in design. AI is no longer just a tool designers casually experiment with. It’s becoming part of the workflow. Especially after tools like Claude started changing how designers think about execution, ideation, and speed. After 18 years in UX and leading a design agency, here’s what I’m noticing: The designers growing the fastest right now are not necessarily the ones with the flashiest visuals. They’re the ones who know: what to automate what to simplify and where human thinking still matters most So if you’re a designer trying to stay ahead, start here: Step 1: Use AI before opening Figma Most designers still jump straight into UI. Instead, ask AI: “Act as a UX strategist. Help me plan the structure for a [project type].” Ask for: user pain points user flows feature suggestions onboarding ideas information architecture You’ll start designing with more clarity from the beginning. Step 2: Use AI to speed up UX thinking AI shouldn’t replace your process. ↳ It should remove friction from it. Ask: “Review this landing page structure and identify: possible UX issues confusing sections weak hierarchy drop-off risks” You’ll save hours of manual review. Step 3: Use AI as a design reviewer This part is underrated. Upload your screen and ask: “Act as a senior UX reviewer. Give me honest feedback on: usability accessibility hierarchy CTA clarity cognitive load” Sometimes AI catches things your own eyes miss after staring at a screen too long. That’s where the industry is heading. Not toward “AI replacing designers.” But toward designers who know how to combine: ✓ design thinking ✓ human empathy ✓ and AI efficiency Because clients are starting to expect faster thinking, faster iteration, and smarter workflows. And AI is now part of that expectation. Are designers adapting fast enough? (If this resonated, repost it ♻️)

#AI-Enhanced Design Thinking: Supercharging Innovation with Digital Intelligence "The real problem of humanity is the following: We have Paleolithic emotions, medieval institutions, and godlike technology." - E.O. Wilson Last week I wrote about the Design Thinking + Lean + Agile trio. Today, let's explore another evolution that's quietly transforming innovation: AI-Enhanced Design Thinking. This marriage is like giving a Formula 1 car to an already skilled driver. The human remains in control, but the machine amplifies capabilities exponentially: - Human designers provide the empathy, ethics, and creative vision - AI delivers pattern recognition, data processing, and generative capabilities - Together they create something neither could achieve alone But when should you specifically deploy this supercharged methodology? Use as follows: 👉 **Use it when dealing with vast amounts of user data** When traditional research methods would drown in the data ocean, AI can identify patterns humans would miss. Netflix's recommendation engine doesn't just use explicit ratings but analyzes 30+ aspects of viewing behavior to understand what "romance" means to different viewers. 👉 **Use it for rapid prototyping and iteration** When you need to quickly generate and test multiple design variations. Airbnb uses AI to transform rough sketches into usable UI prototypes in seconds rather than hours. 👉 **Use it for personalization at scale** When one-size-fits-all solutions fail but customizing for each user seems impossible. Spotify's Discover Weekly feels personally curated because AI analyzes your listening patterns against billions of data points. 👉 **DON'T use it for initial deep empathy work** If you haven't yet developed fundamental understanding of user emotions and motivations, AI might lead you astray with data-driven insights divorced from human context. 👉 **DON'T use it when ethical stakes are high without human oversight** AI can inherit and amplify biases in training data. For high-impact decisions, always pair AI insights with diverse human perspectives. The secret ingredient? Finding the right human-AI collaboration model. Don’t treat AI as either magical oracle (accepting all recommendations without question) or mere calculator (using it only for basic tasks). Neither approach captures the true potential. Think of it as a dance partnership: sometimes AI leads with unexpected insights, sometimes humans lead with intuitive leaps, but the magic happens in the coordinated movement between them. What's your experience? Have you integrated AI into your design process? Or are you hesitant about where machines fit into this traditionally human-centered discipline? #AIInnovation #DesignThinking #DigitalTransformation #FutureOfWork #InnovationMethodology #HumanAICollaboration

Top design teams at Shopify, Atlassian, and Notion are using AI in their workflows. But not the way Twitter wants you to think. Here is what is actually happening on the ground: AI usage is now tied to performance reviews. Companies are not waiting for designers to adopt it organically. 100% of designers are expected to use tools like Claude Code or Cursor. Not because they want to ship code to production. Because they want their teams exploring freely. The biggest unlock is stateful prototyping. Figma is great for static screens. It is not great for showing what happens when you click something, where focus goes, how a loading state behaves. AI fills that gap. Designers are now building interactive prototypes that actually behave like the real product. They are not PRing to production. A common myth is that designers are now "coding and shipping." At these companies, that is almost never happening. What IS happening is designers are forking the codebase into a sandbox where they can explore without breaking anything. The starting point is your real app. You prompt changes on top of it. That is the workflow. Handoff is not dead, it is just richer. Designers are still sitting with engineers and walking through specs. The difference is those specs now include animated state flows, focus management examples, and interaction details that were impossible to show before. Companies are building internal tooling to support all of this. Sharing a Vercel preview link is not the same as dropping a Figma URL. Teams are building custom drag-and-drop deploy platforms just so designers can share their work the way they used to. The takeaway? AI is not replacing design thinking. It is removing the ceiling on what designers can communicate and prototype. If you are figuring out how to skill up, start with interactive prototyping. That is where these teams are finding the most value, and it is the area that has been broken the longest. What use cases are you exploring right now? Drop them in the comments. #learninpublic #day4

The truth about what UX designers need to know. What worked before has changed. The core principles haven't been replaced, but have been augmented by AI. What used to evolve relatively slowly has now accelerated.  Designing products used to be more systematic and predictable. Now the rules are changing, and new techniques and tech are being introduced regularly. I started reflecting on how UX used to be prior to AI taking off and what has changed.  In technology, you have to be open to adapting. Otherwise, you'll become obsolete. I've watched UX design transform over the last couple of years. While the mission of creating usable products that people love using hasn't changed, everything else has started to evolve. Here's what's shifting, and what UX designers need to pay attention to. ��𝗫 𝗯𝗲𝗳𝗼𝗿𝗲 𝗔𝗜 (𝗣𝗿𝗲-𝟮𝟬𝟮𝟮) • User interviews and surveys • Journey maps and empathy building • Wireframes and mockups in tools like Sketch/Figma • Visual design principles (color, layout, typography) • Usability testing • HTML/CSS awareness • Design thinking process • Collaboration with dev and product teams • Accessibility and inclusive design • Ethical design (avoid dark patterns) 𝗨𝗫 𝗮𝗳𝘁𝗲𝗿 𝗔𝗜 • AI-assisted user research and data analysis • Prompt engineering for design tools • Designing for AI-driven systems (chatbots, personalization) • Generative design (text, visuals, layout) • Conversational UX and adaptive flows • Collaborating with data and ML teams • Understanding bias, explainability, and responsible AI • Critical review of AI-generated outputs • AI literacy (know what models can/can’t do) • and more The key difference? Speed and scale. What used to take weeks now happens in hours. But here's what most miss: The human element is more critical than ever. AI handles the repetitive tasks, letting designers focus on: • Strategic thinking • Ethical considerations • Human connection • Creative innovation Also, I would never discount the need for good user research in all of this. Yes, AI can help, but it doesn't replace talking to people. The best UX designers aren't fighting AI, they're leveraging it. The future belongs to those who can blend human insight with AI capabilities. What's your experience with AI in UX? Share your thoughts below 👇 -- ♻️ Repost to help other UX designers adapt ➕ Follow Jason Moccia for more insights on product innovation

Designers are still using Claude like it’s just another chatbot. And that’s the problem. I’ve been watching how designers interact with AI lately. And here’s what I’ve noticed: They ask random prompts. They expect magic. They get average output. Then they say… “Claude isn’t that great.” But the truth? It’s not Claude. It’s how you’re using it. Because Claude without skills is like a senior designer with zero context. No brand. No system. No direction. Of course the output feels off. This isn’t about learning another tool. It’s a shift in how you think. From: “Ask → get answer” To: “Build → refine → systemize” That’s where the real power is. So if you’re a designer who wants better output (not just faster output)… Here’s the shift you need to make: Step 1: Stop prompting randomly Throwing one-liners won’t get you far. ↳ Context is everything. Start thinking: “What does Claude need to know to think like me?” Because better input = better output. Step 2: Build skills, not prompts Prompts are temporary. Skills are reusable systems. Think of skills as: Your saved brain 🧠 Once you build them → Claude stops guessing and starts aligning. That’s when things get scary good. Step 3: Create your core design skills If you don’t know where to start: Build systems for: • design critique • case studies • your brand voice • content creation These 4 alone can change how you work daily. Less effort. More consistency. Way better quality. Step 4: Treat AI like a design system Most designers miss this. They use AI once… and move on. Top designers? They iterate. Use → tweak → improve → reuse Again and again. That’s how average output turns into great output. The truth is: It’s no longer about who uses AI. Everyone does. It’s about who builds systems with it. Because: Average designers use Claude. Top designers train Claude. And that difference? It compounds fast. So the real question is: Are you just chatting with AI… or actually building with it? (If this changed how you see Claude, repost it ♻️)

AI’s biggest threat to product designers is actually our greatest opportunity. Last week I ran an AI-powered design sprint, and saw the future of designing together. Three things are crystal clear: 1. If anyone can make anything using AI... collaboration is everything. Our AI design sprint, completed in 1/5 the time, ended with live, collaborative prototyping using AI. It was brilliant. I’m calling it a “Super Sprint” because that’s exactly how it felt. But here’s what hit hardest: one of the most relevant and valuable roles of design right now is helping teams discover, align, and build the right thing together. Without this, teams risk spiraling into AI-generated chaos. 2. The role of design is shifting, faster than most people think. This isn’t the end of design, but it’s the end of solo designing and long hours spent in Figma-focused isolation. This is a good thing. We've always preached that design is more than pixels, colors, and fonts. Now is the time for designers to prove it. Design will shift even more upstream, which is that "seat at the table" we always wanted anyway. 3. Discovery, strategy, and facilitation are must-have design skills. AI will empower us to spend less time pushing pixels and more time facilitating conversations and alignment. This is the 90% of design that happens before Figma, and it’s where we can step up and have the most impact. If you’re curious how I pulled this workshop off, I put together a quick outline you can use. It's the exact sprint format and AI touch-points that worked. I'm happy to share it, just DM me or comment “shift”, and I’ll send it over. This is the shift in how we design and build products collaboratively. An AI-powered Super Sprint is just the beginning. And designers are in the perfect position, and uniquely equipped, to lead.

Designers are going to be replaced, but not by AI. They're being replaced by the designers using AI. Here's what I'm seeing: → Half the design community is panicking about AI taking their jobs. → The other half is trying to use it for everything and getting frustrated with mediocre results. Both groups are missing the point. I spent the last couple of years finding new ways to leverage AI in my design workflow—from research and rapid concepting to iteration and copy refinement. Some attempts were game-changing. Others were complete disasters. The breakthrough was when I stopped asking "Can AI do this?" and started asking "Should AI do this?" AI can either amplify your creativity or replace it—the key is distinguishing what needs to stay human from what can be enhanced by AI. Here's the partnership model that's transformed how our team works: AI excels at: → Ideation volume: Generate 50 layout variations in minutes → Content creation: Draft copy, headlines, microcopy at scale → Asset production: Icons, illustrations, stock photo alternatives → Pattern recognition: Analyze user data for insights → Repetitive tasks: Resizing, formatting, batch operations Humans excel at: → Strategic thinking: Understanding business context and user needs → Emotional intelligence: Crafting experiences that resonate deeply → Judgment calls: Knowing when to break conventions → Stakeholder dynamics: Reading the room, building consensus → Quality curation: Distinguishing good ideas from great ones Perfecting the human+AI partnership: 1. 𝗟𝗲𝘁 𝗔𝗜 𝗵𝗮𝗻𝗱𝗹𝗲 𝘁𝗵𝗲 𝘃𝗼𝗹𝘂𝗺𝗲 𝘄𝗵𝗶𝗹𝗲 𝘆𝗼𝘂 𝗵𝗮𝗻𝗱𝗹𝗲 𝘁𝗵𝗲 𝘃𝗶𝘀𝗶𝗼𝗻. Start with AI for rapid iteration, then apply human judgment to select and refine. 2. 𝗨𝘀𝗲 𝗔𝗜 𝗳𝗼𝗿 𝗱𝗶𝘃𝗲𝗿𝗴𝗲𝗻𝘁 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗮𝗻𝗱 𝗵𝘂𝗺𝗮𝗻𝘀 𝗳𝗼𝗿 𝗰𝗼𝗻𝘃𝗲𝗿𝗴𝗲𝗻𝘁 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀. Let AI explore possibilities you wouldn't consider. Use human intuition to choose the right direction. 3. 𝗨𝘀𝗲 𝗔𝗜 𝘁𝗼 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗲 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝘄𝗵𝗶𝗹𝗲 𝗵𝘂𝗺𝗮𝗻𝘀 𝗱𝗲𝗳𝗶𝗻𝗲 𝗾𝘂𝗮𝗹𝗶𝘁𝘆. Speed up the creation process, but never skip the critical evaluation phase. 4. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝘁𝗵𝗲 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗮𝗯𝗹𝗲, 𝗽𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲 𝘁𝗵𝗲 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁. Use AI for templates and patterns. Reserve human creativity for moments that matter most. AI isn't a threat, nor is it a magic solution. Think of it as an enthusiastic design intern—incredibly fast, eager to help, but needs clear direction and oversight. How are you currently using AI in your design workflow? #uxdesign #ai ——— 👋 Hi, I’m Dane—I like to gush about UX and branding. ❤️ Found this helpful? Dropping a like would be 🔥. 🔄 Share to help others (or for easy access later). ➕ Follow for more like this delivered to your feed every day.

How can designers use Claude Code? Not as a chatbot. As a production engine! Tommaso Nervegna recently published a practical guide to move from static mockups to working software without becoming traditional developers. At first glance, it sounds like “AI helps you code.” It’s not that simple. This isn’t about asking AI to generate snippets and pasting them somewhere. It’s about using Claude Code as an execution layer, where design intent becomes runnable output. What’s happening in this workflow: 🔸 Designers describe outcomes, not syntax 🔸 Claude generates structured project scaffolding 🔸 Iteration happens conversationally, with persistent context 🔸 Components evolve into functional UI, not just visual artifacts 🔸 The feedback loop lives inside the AI workflow, not in Jira tickets That’s a different paradigm. This isn’t “design handoff improved.” It’s closer to: design-as-executable-logic. When AI understands the structure, constraints, and system intent, documentation becomes dynamic. It becomes operational. Still early? Definitely. Still messy? In parts. But directionally… this is big. Because if designers can reliably move from concept → structured logic → functional interface with AI as a collaborator, the bottleneck shifts. Less translation. More orchestration. More systems thinking. We’re getting closer to a world where: Design is infrastructure. Prompts are architecture. And iteration cycles collapse dramatically. 🔗 Check the Practical Guide: https://lnkd.in/d_C7Nad6 Would you use Claude Code as part of your design workflow, or does that blur a boundary you still want to keep? 👇 #DesignSystems #designsystem #ClaudeCode #GenerativeAI #AIDesign #DesignEngineering #DesignOps #ProductDesign #UXStrategy #VibeCoding

As AI continues to reshape technology, UX design must evolve with it. Too often, the conversation focuses on using AI as a tool, but what about designing experiences where AI is part of the system itself? I’m excited to share my latest white paper, where I explore: ✅ How UX designers can lead in creating AI-powered products that truly serve both users and businesses ✅ The difference between designing with AI tools (like ChatGPT or Figma AI) vs. designing for AI systems (think recommenders, smart assistants, predictive dashboards) ✅ The critical role of data literacy and AI model understanding in UX ✅ Frameworks and principles for ethical, transparent, and user-centered AI ✅ Case insights (Netflix, Walmart, and more) on aligning AI with business strategy Key takeaway: UX designers aren’t being replaced by AI, we are shaping the systems that make AI usable, ethical, and effective. Download the white paper and join the conversation about the future of UX + AI: 👉 https://lnkd.in/eBJkiWkR I’d love to hear your thoughts: how is your team approaching AI design? #UXDesign #AI #ArtificialIntelligence #UXStrategy #ProductDesign #SystemsDesign #AIAlignmentIssue #HumanCenteredDesign #EthicalAI #DesignLeadership #Innovation

Most designers are using AI wrong. They use it to generate screens. But that’s not where the real leverage is. The real shift is this: AI should help you build systems, not just designs. Because screens change. Systems scale. And if you’re still designing everything manually… you’re already falling behind. Let me be honest with you. Creating a proper design system used to take weeks. Messy files. Inconsistent components. Endless revisions. And most teams never get it right. Not because they’re bad designers… …but because the process is broken. Now something has changed. With tools like Figma + Claude Code, you can completely rethink how components are created. You don’t start with screens anymore. You start with structure. Tokens. Systems. Reusable logic. Then you let AI handle the heavy lifting. Generating components. Applying consistency. Building scalable foundations. And you step in where it actually matters. Refinement. Decisions. Quality. That’s the role of a modern designer now. Not just creating… but directing. In this infographic, I’ve broken down the exact workflow: From setting up tokens connecting your design library prompting AI the right way generating clean, scalable components So instead of spending hours fixing inconsistencies… you build once, and reuse forever. If you’re serious about working faster, and designing at scale, this is something you need to understand. Because this is not a small improvement. It’s a complete shift in how design systems are built. I’ve simplified the whole process step by step in the infographic. If you learn this once, It will save you hundreds of hours.