Responsive Design Guidelines

In a world where most brands pick a side—flavor color vs brand color—what happens when you try to balance both? In Part 1, we made the case against brand color, highlighting the rise of rainbow packs and flavor-forward flexibility. In Part 2, we argued for it, showing how consistent color drives recognition, scale, and speed. In Part 3, inspired by folks' follow-up questions on LinkedIn, we explore what happens in the middle, where brands try to balance both strategies at once. 🌓 Half and Half: The Hybrid Strategy Call it Arnold Palmer packaging or the Goldilocks strategy. Whatever the name, the approach is simple: balance brand color with a flavor-led visual system. Once you start looking for it, you find it everywhere: 🟡 Lemon Perfect 🟢 Starbucks Grounds ⚪️ Skinny Pop ⚫️ KIND Snacks In each case, these brands aim to brand-block across SKUs while giving shoppers quick flavor navigation. It’s a strategy that helps both fit in and stand out, especially in categories full of extreme color approaches. ❓ Why Brands Use It - It feels more nimble and less big-brand-y when it's not just a single color and more established than flavor-changing only brands. - It offers long-term flexibility as brands can shift the balance over time - leaning more into brand cues or flavor signals as the architecture evolves. - In categories where everyone else goes all-in on one strategy or the other, the middle path can be the boldest move. ⚠️ But There Are Trade-Offs – Color harmony gets harder. Certain flavor colors may clash with more distinctive brand colors. – Hybrid systems that lean on neutral color bases put themselves at risk of looking familiar to other brands with the same idea (see example). – The smaller your canvas, the harder it is to split the difference effectively. - You don't feel the full benefits of all-brand or all flavor-color. 📏 Color Asymmetry While effective, a 50/50 split can often feel a little staid. Brands that follow the Golden Ratio or a 2/3 to 1/3 approach often are more visually appealing and distinctive. - Archer Meat Snacks lets brand color take up 2/3 of the real estate, using flavor accents for navigation. - Yasso, Inc. goes bold with 2/3 flavor color, with a consistent brand color tying it all together for shelf presence. Regardless of brand or flavor forward, asymmetry makes design systems feel more intentional than templated. 💡 The Takeaway It’s not about picking brand color or flavor color. And it’s not about always meeting in the middle either. The real question is: what serves your strategy? The best systems—whether bold, blended, or balanced—are built to fit your brand’s size, shelf, and stage. Because great design isn’t defined by color. It’s defined by intention. 📚 In case you missed it: 🔹 Part 1 – Against Brand Color https://lnkd.in/gxNieSCz Part 2 – The Case For Brand Color https://lnkd.in/gcRZsxKx

AI Overviews are changing how content gets discovered. Here’s how to help AI find and surface your content. We still write for humans first. That hasn’t changed, nor will it. But now there’s a new layer to consider, which is making sure your human-centered content can actually be found by AI. Think of it like this: you can be the most eloquent storyteller in the room, but if you're speaking a language the translator doesn't understand, your message never reaches the audience. The shift is subtle but significant. When you say, "Our shoes are comfortable for hiking long distances," you're connecting with human experience. When you say, "Pressure mapping shows 27% less forefoot compression than competitors," you're giving AI something concrete to work with. The best content does both. How to Make Your Content Do Both: 1) Specificity beats superlatives "Industry-leading performance" tells AI nothing. "Recognized as the most energy-efficient cloud provider by independent testing (2025)" gives it something to reference and cite. 2) Structure for scanning Both humans and AI value clear organization. Use headings that summarize what's coming. Break complex ideas into digestible pieces. Answer implied questions directly within your content. 3) Context through comparison Instead of "lightweight and fast," try "At 250MB, our app is 30% smaller than the industry average, reducing load times by 40%." AI looks for relationships and comparisons, not vague descriptors. 4) Define your terms When introducing a new concept, explain it in a way AI can recognize. Instead of "adaptive learning technology," say "AI-driven personalization that adjusts difficulty based on user performance." This improves clarity for both audiences. The goal isn't ever to write for robots instead of humans. It’s about making sure your human-first content is organized in a way AI can actually work with. We need to become bilingual, i.e., fluent in both human storytelling and machine logic. This evolution asks us to be more precise, more accountable, and more clear about our value propositions. Which, when you think about it, makes our content better for everyone. #AI #ContentStrategy #SEO #hicm

Researchers at Los Alamos National Laboratory have introduced a novel "hybrid" approach to quantum computing hardware design, aiming to simplify the execution of quantum algorithms. Key Insights:  Hybrid Hardware Design: This approach replaces portions of traditional quantum circuits with physical evolutions that leverage the system's inherent interactions. By doing so, it reduces the reliance on complex sequences of quantum gates, which are analogous to classical logic gates but can be challenging to implement efficiently in quantum systems.  Application to Grover’s Algorithm: The researchers applied this hybrid method to Grover’s algorithm, a well known quantum algorithm that enables unstructured searches of large datasets more efficiently than classical algorithms. Their implementation demonstrated a reduction in the complexity typically associated with executing such algorithms on quantum hardware. Implications:  Enhanced Algorithm Execution: By minimizing the number of quantum gate operations required, this hybrid design can potentially preserve the computational advantages of quantum computing, making it more practical for scientific applications.  Advancement in Quantum Hardware: This method offers a pathway to develop quantum hardware that can execute complex algorithms with reduced operational overhead, addressing some of the current challenges in quantum computer design. For a detailed overview, refer to the original highlight on the U.S. Department of Energy Office of Science website: https://lnkd.in/g6k3FKqv

You can’t shove the genie back in the bottle, but you can invite her to hang out. At a recent CEO roundtable, the topic of return-to-office (RTO) popped up, as it always does. One CEO said what many were thinking: “I don’t want to force the genie back in the bottle. But I do want her back when it counts, like when we’re solving big problems, building bold things, or just need the creative jolt that only comes from being in the same room.” Heads nodded. Zoom fatigue is real. So is the slow leak of culture, connection, and energy some teams are feeling. But mandates won’t fix it. Design will. Step 1: Design for moments, not mandates The smartest RTO strategies today are about intentional moments, not showing up just because. Start by: -Mapping collaboration needs, not just job functions -Customize flexibility based on the nature of work, not hierarchy. -Conduct a role-mapping exercise (with department heads) to group functions into 3 categories (examples): Anchor Teams (need in-person time for innovation/collaboration) → e.g., Product, GTM, Marketing Hybrid Core (flexible but benefit from periodic onsite work) → e.g., HR, Finance, CX Remote-First (individual contributor roles with minimal in-person need) → e.g., Engineering, Legal Define expectations: e.g., Anchor Teams = 1–2 days/wk in office; Hybrid Core = 2x/month strategic on sites; Remote-First = optional access -Create “onsite moments that matter” like innovation sprints, customer jams, or hard-problem weeks If people know why it matters, they’ll come. Guilt isn’t a strategy. Step 2: Reimagine the office (because right now, it’s sad) One CEO admitted: “We have a beautiful office, but it’s just empty desks and stale granola bars.” Bring back the vibe: -Design for connection, not silence -Invest in hybrid-friendly tech + rituals -Add some joy: music, good snacks, unplanned laughs. The goal isn’t nostalgia. It’s forward energy. Step 3: Start with the Leadership Team (seriously) If the exec team isn’t modeling in-person energy, forget it. At the roundtable, execs were all on different schedules. No wonder nothing’s clicking. Fix that: -Get aligned at the top, commit to moments together -Make off sites count, real strategy > trust falls -Build equity in visibility. Location ≠ impact. Culture follows leaders. So does momentum. Step 4: Prove It CFOs asked: “What’s the ROI?” Fair. Build a scorecard: -In-office collaboration quality -Utilization tied to outcomes -Top talent retention -Hybrid leadership fluency -Real estate ROI vs engagement Track what matters. Kill what doesn’t. Don’t mandate the magic. Make room for It. One CEO asked: “How do we bring back energy without killing flexibility?” My take: Stop trying to shove the genie back in the bottle. Instead, invite her to drop by, on purpose, when it counts. HR can lead the way. RTO isn’t about control. It’s about designing moments that create meaning. Let’s stop demanding presence. Let’s create gravity.

💡Hybrid Model of Contribution to a Design System Hybrid model of contribution is a popular approach that many large organization follow. This model combines centralized governance with decentralized contributions, allowing teams to collaboratively enhance the system while maintaining consistency & quality. Key principles of the hybrid model ✅ Central governance: A core team oversees the design system’s vision, principles, and standards to maintain consistency. ✅ Decentralized contributions: Product teams across the organization can propose, design, and build components or patterns. ✅ Collaboration & feedback loops: Mandatory review and approval process ensures contributions align with system guidelines. Structure of hybrid model 1️⃣ Centralized core team responsibilities ✔ Define the vision, principles, and standards of the design system. ✔ Develop and maintain core components, foundational elements (e.g., design tokens), and guidelines. ✔ Manage the repository, versioning, and documentation. 2️⃣ Contributor teams responsibilities ✔ Propose and develop components or updates based on specific product needs. ✔ Follow the contribution guidelines and submission process established by the core team. ✔ Participate in testing, documentation, and reviews for their contributions. 3️⃣ Collaborative governance ✔ Contributions are reviewed and approved by both the core team and representatives from contributor teams. ✔ Regular feedback loops (e.g., workshops, design critiques) ensure alignment with the system’s principles. 🔢 Workflow of the hybrid model Step 1: Contribution proposal Contributors identify gaps or opportunities in the design system. They submit a proposal outlining the problem statement and user needs, the proposed solution (e.g., new component, update to an existing pattern) Step 2: Design & development Contributors collaborate with the core team to ensure that the design aligns with system principles and visual language and the code meets established standards. Step 3: Review and feedback Contributions undergo a structured review process. This includes design review (evaluate alignment with visual, interaction, and accessibility guidelines) and code review (check for quality, scalability, and adherence to coding standards). Step 4: Testing & validation Components are tested for functionality across browsers and devices, accessibility compliance (e.g., WCAG), and performance under different scenarios. Step 5: Documentation and release Contributors document the component/pattern thoroughly. Approved contributions are merged into the system and communicated to all teams. Step 6: Feedback & iteration Post-release feedback is gathered from users and stakeholders. Contributions are iterated upon based on usage and evolving needs. 📕 Great examples of design system contribution & governance processes: https://lnkd.in/dNw_qFDC #design #designsystem #productdesign

I am pleased to see that the tri-hybrid MIMO architecture is being further developed by the research community. This architecture extends hybrid MIMO by adding reconfigurable antennas as an electromagnetic precoding layer. A tri-hybrid MIMO system includes three layers of precoding: digital, analog, and electromagnetic, at the transmitter and the receiver. I want to highlight some recent work that I have seen posted on arXiv in the past few months. Mengzhen Liu, Ming Li, Rang Liu, and Qian Liu, in “Tri-Timescale Beamforming Design for Tri-Hybrid Architectures with Reconfigurable Antennas,” propose to optimize the three layers of beamforming on different time scales, with the antenna layer operating on the slowest scale. Together with Lee Swindlehurst, they have also written “Reconfigurable Antenna Arrays: Bridging Electromagnetics and Signal Processing.” In that paper, the authors describe a dynamic connected tri-hybrid architecture, which was not included in my magazine paper, and summarize several open challenges including cross-domain design. Pinjun Zheng, Yuchen Zhang, Tareq Al-Naffouri, Md. Jahangir Hossain, and Anas Chaaban, in “Tri-Hybrid Multi-User Precoding Using Pattern-Reconfigurable Antennas: Fundamental Models and Practical Algorithms,” study the effect of discrete and continuous pattern reconfigurability on multiuser MIMO communication. They also examine how reconfigurable antennas can reduce the number of RF chains. Yinchen Li, Chenhao Qi, Shiwen Mao, and Octavia A. Dobre, in “Tri-Hybrid Beamforming for Radiation-Center Reconfigurable Antenna Array: Spectral Efficiency and Energy Efficiency,” analyze precoding with a radiation-center reconfigurable array implemented using reconfigurable pixel antennas. They compare selection among fixed-position antennas and fully digital systems and show improvements in energy efficiency. Jiangong Chen, Xia Lei, Yuchen Zhang, Kaitao Meng, and Christos Masouros, in “Integrated Sensing and Communication with Tri-Hybrid Beamforming Across Electromagnetically Reconfigurable Antennas,” explore the benefits of the tri-hybrid architecture for integrated sensing and communication. They formulate and solve optimization problems that configure the three layers of precoding to balance communication and sensing objectives, showing clear benefits from antenna reconfiguration. Zhenqiao Cheng, Chongjun Ouyang, and Nicola Marchetti, in “On the Performance of Tri-Hybrid Beamforming Using Pinching Antennas,” connect the tri-hybrid architecture to the emerging area of pinching antennas, which are a form of reconfigurable antenna. They formulate an optimization that configures the pinching mechanism to serve multiple users over a large area and demonstrate improvements compared with hybrid-only systems. Much more work can be viewed through the framework of the tri-hybrid MIMO architecture. These papers are only a few that mention it explicitly. Links to the papers are in the comments.

If you know me at all, you know I've spent years building AI-powered products and converting legacy systems into adaptive experiences. And I keep seeing the same pattern: talented designers asking me "what even is adaptive UI?" because nobody's explaining it in practical, buildable terms. Your interface is frozen in time. Same buttons, same layout, same experience for everyone. Meanwhile, your users are all completely different. Adaptive UI fixes this. WHAT IS ADAPTIVE UI? (aka, responsive, generative, dynamic or intelligent UI) Your interface watches how people behave, learns their patterns, and redesigns itself in real-time to fit them. Some shoppers know exactly what they want (fast checkout). Others need to research everything (reviews, specs). Some are visual (show me photos). Others are price-sensitive (where's the sale?). Static UI forces everyone through the same experience. Adaptive UI generates a personalized interface based on actual behavior. This isn't just showing different content. The entire interface regenerates around each user's workflow. HOW IT WORKS Two components: The Observer: Watches behavior What do they click? Where do they hesitate? What patterns emerge? The Generator: Creates personalized layouts Rearranges content hierarchy Shows/hides relevant features Adjusts buttons and placement Rewrites microcopy for skill level The loop: Observe → Learn → Predict → Generate → Repeat BEST USE CASES E-commerce: Financial services: SaaS tools: Healthcare: Adaptive UI wins where users are doing something complex, high-stakes, or repeated frequently. HOW YOU BUILD IT You're not coding this yourself. But you ARE designing the system. Step 1: Map behavioral signals Watch sessions. List patterns: clicks size chart 3x = fit anxiety Step 2: Define 3-5 behavioral profiles Not demographics. Behavioral patterns like "Confident Buyer," "Anxious Researcher" Step 3: Design variants in Figma One product page becomes five variants (one per profile) Step 4: Write adaptation rules IF [signal] THEN [interface change] BECAUSE [user need] Step 5: Hand off to engineering They build: event tracking, profile detection, conditional rendering THE REALITY The full build involves cold start problems, filter bubbles, spatial memory, ethical guardrails, mobile constraints, accessibility. But understand this: You're not designing screens anymore. You're designing systems that generate screens. Static interfaces aren't wrong. They're just frozen. And if you're still designing for that mythical "average user," you're designing for someone who doesn't exist. The companies winning in 5 years won't have the prettiest static sites. They'll have interfaces that learn and adapt in real-time. Drop a comment if you're looking to learn more on this subject 💡

A 2,100 m² industrial hall with offices in Austria. Sounds simple? It wasn’t. The hall stands on isolated footings and strips. Steel columns carry a steel roof. Lean system. Built for machines and forklifts. The offices follow a different logic. They sit on a foundation slab with counter capitals. Concrete columns support slabs and beams. Semi-precast walls work with monolithic elements. A hybrid system designed for stability. But the real challenge was not materials. It was the interface between them. When hall and offices meet, loads shift. You know what happens when that line is ignored. Small settlements appear. So we did not design two structures. We engineered one structural dialogue. Here is our approach: • First, align foundation concepts early.    • Second, coordinate stiffness and load paths.    • Third, detail the transition without assumptions. Isolated footings were checked for future loads. The office slab distributed forces cleanly. Walls aligned precisely with columns and beams. The result is simple. A hall that performs under industrial demand. Offices that feel solid. A connection zone that works. Strong structures act as one.

Old Strategy vs. Adaptive Strategy: One Plans to Fail, The Other Fails to Plan Here is why: Old Strategy (Business Case First) → Spend months creating detailed business cases → Predict the future with spreadsheet precision → Get executive approval before any real work starts → Commit to plans that become obsolete before launch Adaptive Strategy (Anti-business case) → Start with aspiration, not analysis → Identify problems worth solving → Transform problems into strategic opportunities → Test high-risk assumptions with small experiments → Iterate based on real feedback, treating deviations as data → Choose one strategic direction and commit The old way: 18 months to launch a "perfect" product nobody wants. The adaptive way: 6 iterations to decide, yes, no, or pivot . Google didn't business-case their way to Gmail. They experimented their way there. Amazon didn't predict AWS would dominate cloud computing. They discovered it by solving their own problems first. Adaptive Strategy > Business Case Theater Your business case is fiction. Your next experiment’s insight is a fact. Stop planning your way to success. Start learning your way there.

Hybrid work has changed how we innovate, especially in design thinking. For operating partners remotely supporting diverse portfolio companies, or for executives of distributed organizations, strategically determining when to engage virtually versus physically is paramount to the success of key initiatives. Design thinking is a human-centered approach that enables companies to understand untapped customer needs and develop innovative solutions. A recent article in the MIT Sloan Management Review breaks down how to optimize each phase of design thinking in a hybrid environment: 🔹Empathize: This is where you understand user needs. Virtual tools can bridge distances, but for deep, nuanced insights (especially for unspoken problems), go physical. You can't beat in-person observation and interaction to truly grasp user context. 🔹Define: Time to make sense of all that messy data. Digital whiteboards and collaborative platforms shine here. They help structure, synthesize, and identify patterns, fostering an analytical mindset. For this phase, go virtual. 🔹Ideate: Generating new solutions thrives on spontaneous interaction and physical activity. Virtual sessions often lead to fewer and more abstract ideas. To spark creativity and quantity, go physical. 🔹Prototype: Early on, when you need quick feedback on basic viability, digital prototypes are efficient for rapid iterations. But for deeper exploration and understanding how users truly interact with a solution, switch to physical prototypes in later stages. 🔹Test: For users to experience a prototype in real-world conditions and provide rich feedback, go physical. However, when it comes to analyzing that feedback objectively and structurally, virtual tools can help overcome presenter bias. Consider a hybrid approach here, moving to virtual for data processing. The key is not choosing one over the other but strategically combining both to leverage their unique strengths to drive innovation and gain a competitive edge. How have you adjusted your innovation processes for hybrid work? #Leadership #SciencemeetsStrategy #DesignThinking #DigitalTransformation