Drew Bridewell, CHPC

The Future of High-Velocity Design Engineers are moving faster than ever. AI can spin up seven different prototypes before we’ve even finished a "Research Plan." If we stay stuck in 3-month linear loops, we become the bottleneck. I recently had a talk with my team on how we’re evolving. Our goal is to eliminate the translation layer between our design intent and the live code. This means: Redistributing our time: Less time pushing pixels, more time "jamming" in the live build. Vibe Coding: Using AI (Claude/Cursor) to build functional realities, not just "clickable" prototypes. Trust through Speed: Shipping Research Previews early to learn from real-world data. I created a quick presentation echoing this shift. Feel free to use it, I hope it help you start the conversation. Design leaders, I would love to hear how you're redefining "craft" in your teams as the gap between design and dev evaporates. Let's discuss. 👇 Thanks Jenny Wen for sharing with us your insights 👊

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Misconceptions about design is our biggest issue. Watch this for best Ng accurate about design. or send this to your stakeholder who you've been discussing design with. ✌🏻 Stay tuned for next in the series.

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Hey accessibility, color, and web performance wonks–I have a question for you. What are the known downsides of using opacity as the modifier in color ramps? Here are the ones I've been aware of: - It's been a deal-breaker in past conversations related to performance–particularly on mobile. - It opens up some gnarly contrast issues if the color is set on an unintended background color. - There isn't necessarily a "canonical" color for each value in the system–at least from the perspective of "canonical" mapping to a static hex value. What else am I missing? Asking for an imaginary friend. cc Cole P.

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𝗬𝗼𝘂𝗿 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀 𝗮𝗿𝗲 𝗰𝗹𝗼𝘀𝗲𝘀𝘁 𝘁𝗼 𝘆𝗼𝘂𝗿 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿’𝘀 𝗽𝗮𝗶𝗻—𝗮𝗿𝗲 𝘆𝗼𝘂 𝗹𝗶𝘀𝘁𝗲𝗻𝗶𝗻𝗴? In almost every co-creation session I run, the breakthrough doesn’t come from the boardroom—it comes from the floor. 𝘈 𝘲𝘶𝘪𝘦𝘵 𝘤𝘰𝘮𝘮𝘦𝘯𝘵 𝘭𝘪𝘬𝘦 “𝘵𝘩𝘢𝘵 𝘴𝘵𝘦𝘱 𝘯𝘦𝘷𝘦𝘳 𝘸𝘰𝘳𝘬𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘳𝘦𝘢𝘭 𝘸𝘰𝘳𝘭𝘥” 𝘩𝘢𝘴 𝘳𝘦𝘳𝘰𝘶𝘵𝘦𝘥 𝘦𝘯𝘵𝘪𝘳𝘦 𝘱𝘳𝘰𝘫𝘦𝘤𝘵𝘴 𝘧𝘰𝘳 𝘵𝘩𝘦 𝘣𝘦𝘵𝘵𝘦𝘳. 𝖫��𝖾̲𝗌̲𝗌̲𝗈̲𝗇̲ ̲𝗅̲𝖾̲𝖺̲𝗋̲𝗇̲𝖾̲𝖽̲:̲ leaders don’t have a visibility problem, they have a proximity problem. 𝖶̲𝗁̲𝖺̲𝗍̲ ̲𝗐̲𝗈̲𝗋̲𝗄̲𝗌̲:̲ Bring frontline staff into the room early 𝘈𝘴𝘬: “𝘐𝘧 𝘺𝘰𝘶 𝘤𝘰𝘶𝘭𝘥 𝘤𝘩𝘢𝘯𝘨𝘦 𝘰𝘯𝘦 𝘵𝘩𝘪𝘯𝘨 𝘵𝘰𝘮𝘰𝘳𝘳𝘰𝘸, 𝘸𝘩𝘢𝘵 𝘸𝘰𝘶𝘭𝘥 𝘪𝘵 𝘣𝘦?” Prototype together so ideas become tangible fast Let evidence outweigh rank When you involve the people closest to the customer, you uncover problems you didn’t know existed—and solutions you can act on today. When was the last time a frontline insight changed your plan? #EmployeeExperience #Innovation #DesignThinking #CustomerExperience #makelifebetter

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Apple Just Unveiled Its Liquid Glass Interface — and It’s a Whole New Paradigm This isn’t just a UI update. It’s a reimagining of how humans interact with machines. What is Liquid Glass? Apple’s new Liquid Glass Interface fuses physical realism with fluid motion, creating a surface that: ✅ Adapts to touch, motion, and environment ✅ Flows with your actions ✅ Feels less like software, more like material It’s intuitive. Immersive. Almost alive. Imagine this: Interfaces that reshape based on context Visuals that move with intent, not just input A seamless blend of hardware + software — as if they were made from the same element This could be the foundation for Apple’s spatial computing future — across Vision Pro, macOS, and what comes next. Once again, Apple isn’t just designing products. They’re designing experiences. Here you can check: https://lnkd.in/gAsTx7w6 #Apple #LiquidGlass #UXDesign #HumanComputerInteraction #Innovation #AppleEvent #FutureOfTech #SpatialComputing #VisionPro #DesignEvolution

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I’ve been noticing a familiar theme popping up lately — especially in design communities: “AI tools aren’t quite there yet.” “They slow me down.” “They look impressive, but fall apart in real workflows.” Honestly? That frustration makes sense. Most AI tools today are still assistive, not autonomous. They’re brittle at the edges. They need context they don’t yet understand. And they often require more judgment — not less — from experienced designers. But I don’t see this as a failure of AI. I see it as a leadership moment. The real opportunity right now isn’t pretending the tools are magical. It’s understanding their limits — and designing workflows that account for them. Used well, today’s AI can: • Accelerate exploration • Reduce mechanical effort • Surface options faster • Create space for deeper thinking Used poorly, it becomes noise, rework, and false confidence. That’s why I’m optimistic about where this goes. The tools will evolve. The models will improve. But product teams will only benefit if we evolve too — in how we frame problems, define quality, and decide when humans stay firmly in the loop. This isn’t about replacing craft. It’s about protecting it while the tools catch up. And that’s a future I’m genuinely excited about.

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The day after launching Claude Opus 4.7, Anthropic did something it had never done before: shipped a standalone creative product. And Figma's stock dropped 7% by market close. Claude Design launched on April 17 as a research preview under Anthropic Labs. It lets anyone create prototypes, slides, one-pagers, and UI mockups through a plain-English conversation with Claude. No design software. No templates. No prior experience required. What makes it technically different from other AI design tools is the codebase-awareness. During onboarding, Claude reads your actual code repositories and design files to build a design system using your real colors, typography, and components. Every project that follows applies that system automatically. Point it at a live website URL and it pulls the visual elements directly from your product, so prototypes match the real thing rather than a generic blank canvas. The broader strategic signal here is what many people missed. Three days before the launch, Anthropic's Chief Product Officer quietly resigned from the Figma board. The company that launched as an AI safety research lab has now shipped a coding assistant, a computer use agent, an enterprise desktop tool, managed agent infrastructure, and a visual design product, all within a few months. Each launch has sent a different category of software stocks lower. Anthropic is no longer a model company that sells API access. It is a product company building the full stack, using its own models as the engine. Claude Design is included free for Pro, Max, Team, and Enterprise subscribers. https://lnkd.in/g9QVBTPq #ClaudeDesign #Anthropic #GenerativeAI #AIDesign #DesignTools #TechTrends #AIFreakyFacts

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Still so many takes jumping on “design is dead.” The pattern I missed is that they’re all talking about how much “easier” all of this is… in code. “I can get the perfect border radius, the perfect type scale, and a beautiful color spectrum with Claude in minutes.” We’ve had decades of making front-end development easier to “design,” yet we still see tons of horrid designs and a need for designers. Now we’re about to see a rebound of the bootstrap era where you’ll just know when a design was made through an AI agent, not by a human. The IKEA-fication of UI, Part(n) I whole-heartedly believe design as a skillset is about to have gigantic growth once people and businesses once more see the reality that pixels-on-the-screen is not all that designers deliver. After the pain the economy is throwing our way, hiding behind AI as the cause, I truly see the golden-age of the designer-founder upon us.

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Organizations need a redesigned service-design workflow because they identify problems too late, rely on gut instinct, and apply superficial fixes that let deeper issues linger. This leads to cultural rot and technical stagnation. AI-supported service design changes the loop: • earlier issue detection • objective classification and enhanced compliance • alignment around evidence • continuous experimentation • safer, healthier decision-making Critical stakeholders to #AI success in a #servicedesign workflow are middle managers, as they are the connective tissue between strategy and execution. If they feel displaced, threatened, or bypassed, they will quietly resist: • blocking adoption • ignoring insights • working around the system • suppressing uncomfortable truths This amplifies every risk: cultural pacification, tacit knowledge loss, over-reliance on AI, and misaligned incentives. The engagement strategy is to bring managers into the design thinking early and often. Show them how AI decides. Clarify where their judgment still leads. Build incentives around transparency, experimentation, and shared problem-solving. When they buy in, change accelerates. When they resist, everything stalls.

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What if instead of shaping designs in single screens, you could work across multiple at once, building functional, coded, and connected experiences on a single canvas? 👀 Figma

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Hot take for designers experimenting with AI + legacy systems: You don’t have to pick one AI tool and hope it integrates perfectly with your design archive. If you can get to the code, you can make it work. I’ve been testing different AI platforms for strategy and prototyping. What I realized: You can use any AI tool you’re comfortable with to think, prototype, and generate UI — as long as it outputs code. Then: 1. Copy the generated code 2. Paste it into Figma Make 3. Let Figma rebuild it using your UI/style library 4. Edit, refine, and share inside your real system That means: • Strategy can live anywhere • Prototyping can move fast • Your design system still governs the final output AI becomes a thinking partner. Figma stays the system of record. For teams sitting on years of legacy designs and wondering how to bridge that with AI experimentation — this is a practical path. #DesignSystems #AIforDesign #Figma #ProductDesign #DesignOps

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We are about to repeat the "Google Glass" mistake with AI. History is littered with products that worked perfectly on a technical level but failed miserably on a human level. My partner Nick Eberhardt just published a brilliant breakdown of why this happens. He calls it "The Cassandra Paradox." Coca-Cola had data proving people preferred sweeter soda. They launched New Coke. It flopped. Google had data proving Glass was hands-free and efficient. They launched it. It got banned from bars. Ford had data proving the Pinto met cost targets. It... well, we know how that ended. In every case, the data was correct, but the question was wrong. They optimized for variables (taste, speed, cost) but broke the constants (trust, social norms, safety). We see companies making this exact mistake with AI right now. They are asking, "Can the model do this?" instead of "How will this make the human feel?" Read the full piece below. It’s a masterclass on why design breaks upstream. #AI #UXDesign #ProductStrategy #SystemsThinking

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I’ve been spending a lot of time in workshops this fall with designers, engineers, managers, and execs. There is one theme keeps surfacing. Teams want to move forward with AI, but there’s real concern about falling behind or not knowing where to start. I’ve found that once we level-set on what AI is and what it is not, the conversation shifts. We stop chasing hype and start identifying opportunities to support our teams. A simple example is rule-based AI for workflow automation. It takes effort to set up, but it pays off. You can design it by mapping the rules yourself or train it by reviewing historic data to learn your patterns. When teams see these opportunities clearly, they start shaping AI around their work instead of reacting to it.

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The design-to-code handoff is one of the most expensive gaps in enterprise software development. Weeks of engineering time spent interpreting Figma files, reconciling spacing math, and rebuilding what designers already specified. On March 30th, join Aditya Karra, Blitzy's Founding Designer, and Ben Bergerson, Senior AI Solutions Consultant, for a walk thru of Blitzy native Figma-to-production capability. No prototypes. No Refine PR. Production-ready code. - Every design token read before a single line of code is written - Responsive output across five viewports from one desktop frame - A new feature integrated into an existing codebase, brand-aligned, checked directly into the repo Designers and product teams can now move at the speed of design. Come see what that looks like in practice. Register at the link in the comments. March 30 | 12pm ET | Free with live Q&A #Blitzy #Webinar #Figma #Platform40 #FrontendDevelopment #EnterpriseAI #ProductVelocity

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Many product strategy and UX design problems due to a fragmented experience can be solved by re-architecting the IA: the information architecture. Often the IA has evolved bottom-up, piece by piece, in a patchwork way that was once adaptive and leading, but over time, drift, and serving multiple overlapping goals, has become maladaptive and hard for prospects and users to understand and use. So it’s no longer compelling, coherent, navigable and it holds the org back instead of leading it forward. This is especially common after acquisitions or platform and product pivots. That signals a need for recomposition and reconfiguration that unifies business, brand, product, and user goals, not only through surface enhancements but also through strategic synthesis and structural evolution. #informationarchitecture

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With Claude Design by Anthropic, we’re officially entering the era of ‘Design by conversation.’ Describe → generate → refine → ship. Which sounds amazing… until you realize: execution is no longer the hard part. Anyone can now create something that looks good. But good is about to become the new average. So the real question is if everyone can design, what makes a designer valuable? Not tools. Not speed. Not output. Taste. Judgment. Point of view. Because when everything looks decent, only a few things will actually feel right. And that gap? That’s where designers either stand out… or disappear.

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Design isn’t about options. It’s about decisions. Throughout my career I’ve worked with many teams, methodologies, and ways of approaching design. Each one offered something valuable. Over time I realized something simple: The method matters less than the direction. What matters is continuing to move forward and learning from the path as it unfolds. Years ago I made a decision that, from the outside, looked like a step back. I stepped away for a while to work on a project in the mountains. What seemed like a pause became one of the most valuable learning experiences of my career. It shifted how I think about value. Not just in products. In people. In ecosystems. In the decisions that shape them. That experience sharpened something for me. Purpose. When the purpose is clear, decisions become clearer. Teams move with more confidence. The work gains direction. Design isn’t just about creating possibilities. It’s about choosing the ones that truly matter. In your experience leading teams or projects, where is the real challenge today: generating ideas… or making the decisions that move things forward? Let’s keep designing. . . . #Leadership #DesignStrategy #DecisionMaking

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Managing UI clutter can be an aesthetic choice, but it's essentially a performance mandate. The moment excess items or poor organization degrade a user's ability to complete a task, the design will transition from a functional solution to a cognitive liability. The definition of clarity is from this Research Paper: Rosenholtz et al. (2005), "Feature Congestion: A Measure of Display Clutter," (https://lnkd.in/e_n7JEDg)

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