App Design Layouts

𝗡𝗼𝘁 𝗮𝗹𝗹 𝗔𝗣𝗜𝘀 𝗮𝗿𝗲 𝗰𝗿𝗲𝗮𝘁𝗲𝗱 𝗲𝗾𝘂𝗮𝗹. The architecture you choose has a direct impact on your application's scalability, performance, and long-term maintainability. It's not just about implementation—it's about alignment with your business goals and technical constraints. Here’s a breakdown of six core API architectures every engineer and architect should be familiar with: 𝟭. 𝗥𝗘𝗦𝗧 (𝗥𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝘁𝗮𝘁𝗲 𝗧𝗿𝗮𝗻𝘀𝗳𝗲𝗿)   Best suited for simple, resource-oriented applications.   REST is stateless and leverages standard HTTP methods (GET, POST, PUT, DELETE). It’s easy to implement, scalable, and well-suited for CRUD operations in web apps. 𝟮. 𝗚𝗿𝗮𝗽𝗵𝗤𝗟   Ideal for applications that need flexible, efficient data fetching.   Unlike REST, GraphQL lets clients specify exactly what data they need, reducing both over-fetching and under-fetching. It’s a strong choice for front-end-heavy applications with complex or evolving data needs. 𝟯. 𝗦𝗢𝗔𝗣 (𝗦𝗶𝗺𝗽𝗹𝗲 𝗢𝗯𝗷𝗲𝗰𝘁 𝗔𝗰𝗰𝗲𝘀𝘀 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹)   Best for high-security, enterprise-grade applications.   SOAP is XML-based, highly structured, and supports strict security and compliance standards. It’s commonly used in sectors like banking and healthcare where data integrity and reliability are non-negotiable. 𝟰. 𝗴𝗥𝗣𝗖 (𝗚𝗼𝗼𝗴𝗹𝗲 𝗥𝗲𝗺𝗼𝘁𝗲 𝗣𝗿𝗼𝗰𝗲𝗱𝘂𝗿𝗲 𝗖𝗮𝗹𝗹)   Designed for high-performance, low-latency distributed systems.   Using HTTP/2 and Protocol Buffers, gRPC supports fast, compact communication and bidirectional streaming—making it a powerful choice for microservices and mobile apps. 𝟱. 𝗪𝗲𝗯𝗦𝗼𝗰𝗸𝗲𝘁𝘀   Best for real-time, interactive applications.   WebSockets establish persistent, two-way communication between client and server. This is essential for use cases like chat systems, live notifications, and multiplayer gaming. 𝟲. 𝗠𝗤𝗧𝗧 (𝗠𝗲𝘀𝘀𝗮𝗴𝗲 𝗤𝘂𝗲𝘂𝗶𝗻𝗴 𝗧𝗲𝗹𝗲𝗺𝗲𝘁𝗿𝘆 𝗧𝗿𝗮𝗻𝘀𝗽𝗼𝗿𝘁)   Optimized for IoT and sensor-based environments.   MQTT is a lightweight protocol designed for low-bandwidth, power-constrained devices. Its publish-subscribe model is ideal for real-time telemetry and remote monitoring. 𝗪𝗵𝗲𝗻 𝘁𝗼 𝘂𝘀𝗲 𝘄𝗵𝗮𝘁?   - REST: General-purpose web apps   - GraphQL: Dynamic queries, flexible UIs   - SOAP: Secure enterprise systems   - gRPC: Microservices, real-time communication   - WebSockets: Live, event-driven apps   - MQTT: IoT, embedded devices The right API architecture doesn’t just support your product—it accelerates it. It improves performance, simplifies integration, and positions your application for scale. What API design do you rely on the most? And what lessons have you learned from working with it? Gif Credit - Nelson Djalo

💡UI Spacing Friendship Selecting the right spacing between UI elements is a crucial design skill that demands practice. Having a system in place will make it easier to choose the right spacing in a particular context. Design for ducks team shares a nice concept of UI spacing called "Spacing friendship" (https://lnkd.in/d5duyjmX). The concept is rooted in the principle of proximity and 8-point grid at the core of this system. Principle of Proximity suggests that elements placed near each other are perceived as related or belonging to the same group. Conversely, elements spaced farther apart are seen as separate and unrelated. Principle of Proximity enhances scannability (by making related content visually intuitive) and reinforces usability (by aligning spacing with the content's meaning and context). 8-point grid system is a layout grid where every unit is 8 pixels/points. This system ensures consistent spacing and alignment of UI elements in layout (https://lnkd.in/d6NnxB4w) "Spacing Friendship" categories: ✔ Best Friends: Closely related elements (e.g., headings and descriptions) get smaller spacing (8px). ✔ Friends: Related but distinct components (e.g., image and tags) use medium spacing (16px). ✔ Casual Friends: Larger spacing (24px, 32px and 48px) is applied to unify the content visually. ✔ Acquaintances: To categorize elements into separate and distinct groups when they're far apart (64px, 80px, and 120px). "Spacing Friendship" makes it easy to create a dynamic spacing scale: Base spacing (constant x) ties to the smallest element (often text size). And its possible to use ratios of 0.75x, 1x, or 1.25x for compact, standard, or spacious designs. Example: For a 16px font, use x = 1.25 for 20px spacing in hero sections. 📺 How to design responsive UI grid in Figma: https://lnkd.in/dTPEpvRK #UI #uidesign #design #productdesign #grid #uigrid #spacing

🏎️💨 How To Design For Aging Population. One billion people aged 60+ live today, and it’s growing faster than any other age group. Key points to consider for more age-inclusive UX ↓ 🚫 Don’t assume that older adults struggle to use digital. ✅ Most users are healthy, active and have a solid income. 🤔 With age, it’s more difficult to focus on close objects. 🤔 Visuals with a similar contrast are harder to tell apart. 🤔 60 years → need 3× more light to perceive same brightness. 🤔 With age, shades of blue/purple, yellow/green look similar. 🤔 Reduced dexterity causes errors with precise movements. ✅ Add UI controls to resize columns, move cards, drag-n-drop. ✅ Always confirm destructive actions, allow to Undo/restore. 🚫 Avoid disappearing messages as toasts: let people close them. ✅ Baseline: large body copy (16px+), color contrast (WCAG AA). ✅ Prefer plain language, large checkboxes, radios (36px+). ✅ Avoid small floating labels and use static field labels. ✅ Show error messages above the text input, not below. 🚫 Don’t rely on accessibility overlays; they are trouble. Accessibility doesn’t have to be dull or boring. It doesn’t come at the cost of oversimplification — it can be bold and passionate, while understanding and respecting the needs of the different audiences it caters to. If anything, it makes boldness more accessible to more people. Conversations about older audiences tend to come with plenty of assumptions and stereotypes — and very often they are simply inaccurate. We overgeneralize and simplify. For example, just like when designing for children, we need to study vast differences in the age groups of 60–65, 65–70 etc. Just like any other group, older users need a reliable, clear product that helps them feel independent and competent. Bring older adults in your design process to find out what their specific needs are. It’s not just better for that specific target audience — good accessibility is better for everyone. And huge kudos to wonderful people contributing to a topic that is often forgotten and overlooked. 👏🏼👏🏽👏🏾 Useful resources: Wise Case Study: Accessible But Never Boring, by Stephanie S. https://lnkd.in/d-hjj_BF Designing For Older Audiences, by Matthew Stephens https://lnkd.in/dAXZ9mp3 Better Microcopy For Older Adults, by Michal Halperin Ben Zvi (PhD.), Kinneret Yifrah https://lnkd.in/evWGFB6u What You Can Learn From Older Adults, by Becca Selah https://lnkd.in/eZdbgRyA Designing Age-Inclusive Products, by Michal Halperin Ben Zvi (PhD.) https://lnkd.in/eQZJwEgS [continues in the comments below ↓] #ux #accessibility

How to structure a Figma project from start to finish. It’s the question I get asked most. For me: Full freedom to start. Strong systems after is the key. Here’s my full process, using a small (!) solo design project as an example. 👉 Phase 0: Setup & Alignment Before opening Figma, I talk to development. We align on: • Tools and stack • Communication setup • Constraints, timing, and handoff process This saves countless hours later. 👉 Phase 1: Creative Exploration Nothing structured yet. It’s messy... very messy. I even (hold your breath) use groups (I know!!!! But they are so messy fast!), no auto layout (maybe for a button), no components, randomly pick colours. My goal is speed and flow. I move, drag, test, and iterate until it feels right, it works for me, but might not be he right path for everyone. I also enjoy combining hand sketches and Figma files. I usually work with a mix of wireframes and first ideas. But it highly depends on the project, team size and how many hats I wear Once it looks right, I share it with the team and development. No specs yet, just look and feel. I usually work on 2-3 master pages. 👉 Phase 2: Basic structure & cleanup • Typography styles and clear hierarchy • Colour variables and clear system (base, text, highlights) • Components with Auto Layout I also like to build a small prototype for early feedback. 👉 Phase 3: Structure & Systemisation (loops!) Now it gets real. The first draft might look finished, but it’s not. • Review every component with variants, responsiveness, and states • Refine typography styles and add variables and modes • Align naming and documentation with dev This takes time, a lot of time...and tight feedback loops with development. Build out the rest of the screens with this system 👉 Phase 4: Maintenance & Evolution (loops!) Once the design is structured, it becomes a living system. New features start in a creative playground, then merge back in. Old components get cleaned up. It’s important to agree on a clear system and responsibilities: Who adds, updates, and maintains components, and when. Doing this as a team keeps everything aligned. The result: a consistent, scalable design (and a whole separate stor) 👉 In a nutshell: I prefer full creative freedom at the start and strong systems after, especially for smaller teams or solo projects. Larger teams might merge or parallelise some of these steps. ⚠️ Quick note: This process reflects how I work on small, often solo design projects. In larger teams or product orgs, some steps might run in parallel, follow stricter systems, or use branching/version control instead. The goal here isn’t a “rulebook” just a transparent look at what works for me and pick what works for you. Feel free to agree, disagree or simply share your findings in the comments. How do you structure your Figma files and workflow for smaller (or larger) projects? #Figma #moonlearning #workflow

𝐓𝐡𝐞 𝐚𝐫𝐭 𝐨𝐟 𝐫𝐞𝐭𝐫𝐚𝐜𝐭𝐚𝐛𝐥𝐞 𝐟𝐮𝐫𝐧𝐢𝐭𝐮𝐫𝐞 𝐝𝐞𝐬𝐢𝐠𝐧 𝐢𝐬 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐚𝐛𝐨𝐮𝐭 𝐬𝐚𝐯𝐢𝐧𝐠 𝐬𝐩𝐚𝐜𝐞, 𝐢𝐭 𝐢𝐬 𝐚𝐛𝐨𝐮𝐭 𝐫𝐞𝐝𝐞𝐟𝐢𝐧𝐢𝐧𝐠 𝐡𝐨𝐰 𝐚 𝐬𝐢𝐧𝐠𝐥𝐞 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭 𝐜𝐚𝐧 𝐚𝐝𝐚𝐩𝐭, 𝐞𝐯𝐨𝐥𝐯𝐞, 𝐚𝐧𝐝 𝐩𝐞𝐫𝐟𝐨𝐫𝐦 𝐦𝐮𝐥𝐭𝐢𝐩𝐥𝐞 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐜𝐨𝐦𝐩𝐫𝐨𝐦𝐢𝐬𝐢𝐧𝐠 𝐜𝐨𝐦𝐟𝐨𝐫𝐭, 𝐚𝐞𝐬𝐭𝐡𝐞𝐭𝐢𝐜𝐬, 𝐨𝐫 𝐮𝐬𝐚𝐛𝐢𝐥𝐢𝐭𝐲. 🏠 From an architectural and interior design perspective, the demonstrated arrangement represents an advanced space-transforming solution where integrated storage systems, concealed beds, foldable workstations, pull-out seating modules, modular shelving units, and custom joinery are intelligently combined to create highly adaptable living environments. The design achieves exceptional spatial efficiency while preserving visual harmony through coordinated finishes, concealed hardware, integrated lighting systems, and seamless circulation planning, resulting in a refined, modern, and clutter-free interior experience. 📌 𝐒𝐩𝐚𝐜𝐞 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 & 𝐒𝐩𝐚𝐭𝐢𝐚𝐥 𝐅𝐥𝐞𝐱𝐢𝐛𝐢𝐥𝐢𝐭𝐲: ✓. Multiple functions within one space. ✓. Reduced permanent furniture footprint. ✓. Adaptive day-to-night usability. ✓. Maximized usable floor area. 📌 𝐈𝐧𝐭𝐞𝐫𝐢𝐨𝐫 𝐃𝐞𝐬𝐢𝐠𝐧 & 𝐀𝐞𝐬𝐭𝐡𝐞𝐭𝐢𝐜 𝐄𝐱𝐜𝐞𝐥𝐥𝐞𝐧𝐜𝐞: ✓. Seamless concealed furniture integration. ✓. Coordinated finishes and material harmony. ✓. Clean modern visual appearance. ✓. Clutter-free organized living environment. 📌 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 & 𝐂𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧 𝐏𝐫𝐞𝐜𝐢𝐬𝐢𝐨𝐧: ✓. Reinforced structural support provisions. ✓. Heavy-duty telescopic runner systems. ✓. Concealed hinges and locking mechanisms. ✓. Precision guide-track installation. 📌 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐚𝐥𝐢𝐭𝐲 & 𝐔𝐬𝐞𝐫 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: ✓. Enhanced storage capacity achieved. ✓. Smooth and safe operation. ✓. Improved accessibility and circulation. ✓. Flexible lifestyle accommodation. 📌 𝐒𝐮𝐬𝐭𝐚𝐢𝐧𝐚𝐛𝐢𝐥𝐢𝐭𝐲 & 𝐋𝐨𝐧𝐠-𝐓𝐞𝐫𝐦 𝐕𝐚𝐥𝐮𝐞: ✓. Optimized resource utilization. ✓. Reduced material consumption. ✓. Supports compact living solutions. ✓. Increased property market value. 📌 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐎𝐮𝐭𝐜𝐨𝐦𝐞: ✓. Intelligent space transformation. ✓. Advanced joinery integration. ✓. Enhanced functional efficiency. ✓. Future-ready living environment.

𝗧𝗵𝗶𝘀 𝗟𝗘𝗚𝗢 𝗶𝗺𝗮𝗴𝗲 𝗷𝘂𝘀𝘁 𝗲𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱 𝘄𝗵𝗮𝘁 𝟵𝟬% 𝗼𝗳 𝗳𝗶𝗻𝗮𝗻𝗰𝗲 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹𝘀 𝗴𝗲𝘁 𝘄𝗿𝗼𝗻𝗴 𝗮𝗯𝗼𝘂𝘁 𝗱𝗮𝘁𝗮. Look at it. Really look at it. 𝗗𝗔𝗧𝗔: A messy pile of colorful blocks. That's your raw numbers. Your spreadsheets. Your databases. Most finance teams stop here. "Here's the data," they say, dumping 47 tabs of Excel on the CEO's desk. 𝗦𝗢𝗥𝗧𝗘𝗗: Organized by color. Better, but still just organized chaos. This is where 80% of analysts think they've added value. "Look, I've categorized everything!" Wrong. 𝗔𝗥𝗥𝗔𝗡𝗚𝗘𝗗: Now we're building something. Structure emerges. But even here, it's just pretty bars. No context. No meaning. 𝗣𝗥𝗘𝗦𝗘𝗡𝗧𝗘𝗗 𝗩𝗜𝗦𝗨𝗔𝗟𝗟𝗬: Clean. Clear. Professional. This is where most finance presentations end. Nice charts. Lovely colors. And executives still ask: "So what?" 𝗘𝗫𝗣𝗟𝗔𝗜𝗡𝗘𝗗 𝗪𝗜𝗧𝗛 𝗔 𝗦𝗧𝗢𝗥𝗬: A house. With a tree. A complete picture. THIS is where impact happens. 𝗛𝗲𝗿𝗲'𝘀 𝘁𝗵𝗲 𝗯𝗿𝘂𝘁𝗮𝗹 𝘁𝗿𝘂𝘁𝗵: Your stakeholders don't want data. They don't even want insights. They want to understand what it means for THEM. 𝗧𝗵𝗲 𝗵𝗼𝘂𝘀𝗲 𝘁𝗲𝗹𝗹𝘀 𝗮 𝘀𝘁𝗼𝗿𝘆: • This is where we live (current state) • This is how we're protected (risk management) • This is where we're growing (that tree = opportunities) 𝗧𝗵𝗲 𝟱-𝗦𝘁𝗲𝗽 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: 𝟭. 𝗗𝗮𝘁𝗮 → Start with the mess 𝟮. 𝗦𝗼𝗿𝘁𝗲𝗱 → Organize by relevance 𝟯. 𝗔𝗿𝗿𝗮𝗻𝗴𝗲𝗱 → Build logical structure 𝟰. 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗲𝗱 → Make it digestible 𝟱. 𝗦𝘁𝗼𝗿𝘆 → Connect to their reality I learned this while presenting to a board member who stopped me mid-presentation: "Anders, I don't care about your variance analysis. Tell me if we should enter the German market or not." That's when it clicked. Numbers without narrative = Noise Insights without impact = Irrelevant Charts without context = Colorful confusion 𝗠𝘆 𝗮𝗱𝘃𝗶𝗰𝗲: Stop building prettier spreadsheets. Start building better stories. Because at the end of the day, finance isn't about perfecting the data. It's about building something meaningful from it. Something that drives decisions. Something that creates value. Something that matters. What stage does your finance team usually stop at? More importantly – what's stopping you from building the house? ---------- 🧑💼 I'm a partner at Business Partnering Institute 🆘 Need immediate help in your finance team, call us! 🤝 We help increase the influence of your finance team 🔔 To see more content, hit the bell on my profile 📘 Order our new book now: https://bit.ly/4h2P9AA 🧑🎓 Enroll in our LinkedIn course: https://bit.ly/4a5fB9l 📻 #FinanceMaster podcast: https://bit.ly/3NLSt73 📺 Follow us on YouTube: https://bit.ly/4bSBut6 📢 Join our WhatsApp channel: https://bit.ly/3WWGOrc 📄 Check out all our templates and cheat sheets here: https://lnkd.in/eC_zuCU4

🧠 Stop building single-agent GenAI apps. That era is over. Most GenAI products today look like this: ➡️ One prompt ➡️ One model ➡️ One output But when things break, here’s what you hear: -“It forgot context.” -“It hallucinated.” -“It’s too slow, too dumb, too fragile.” That’s not the model’s fault. That’s the architecture’s fault. Let me explain 👇 💥 What breaks in single-agent apps? -Context Overload: LLMs don’t need more information—they need relevant information. Dumping the entire history into one context window isn’t memory. It’s noise. -No Role Separation: A single agent trying to do research, analysis, reasoning, and response formatting? That’s like asking one employee to be your assistant, lawyer, analyst, and social media manager. -Zero Observability: There’s no traceability of why the model failed. No logs, no fallback logic, no task routing. 🔁 What works instead? Orchestration. Here’s how a real system works: ✅ Agents have roles ✅ Tasks are passed, not re-prompted ✅ Tools are securely invoked ✅ Humans can override any step ✅ Everything is observable, auditable, and retrainable You move from: 🧱 Prompt engineering → 🔗 Protocol engineering Orchestration isn’t about complexity. It’s about coordination. ⚙️ Here’s what we’ve built to solve this: We open-sourced an orchestration protocol that lets you: 📍 Register any LLM or external agent 🧠 Assign tasks based on roles + memory 🔄 Coordinate flows with zero-code YAML or full API 👁️ Trace every interaction with observability tools 👥 Add human-in-the-loop interventions at any node No fancy wrappers. No black-box magic. Just a robust foundation for multi-agent GenAI systems. 🛠️ Example use cases we’ve deployed: - A pre-sales agent team (research + pricing + objection handler) - A co-pilot for onboarding new employees across tools - An internal policy bot that cites source docs, lets HR approve or reject in real-time - Legal summarizers that escalate to humans if confidence < 80% These aren’t PoCs. They’re production-grade AI systems. Want to see how it works? 💡Comment "Agents" and I will send invitation to the closed pioneer group to access the code and tutorials✔️ #AgenticAI #GenAI #artificialintelligence #innovation

You don't have an AI agent problem. You have an architecture decision problem. Most founders think picking an AI agent framework is like picking a database - just choose the most popular one and figure it out later. That's how you end up with a brilliant demo that fails every security audit. After helping 50+ teams move AI agents from prototype to production, here's what actually works: The Architecture Decision Tree: Your Primary Constraint Determines Your Architecture: SECURITY first → Orchestrated or Hierarchical SPEED TO MARKET → Tool-Using or Event-Driven COMPLIANCE first → Memory-Augmented with governance AUTONOMY first → Goal-Driven with guardrails Then Match to Your Scale: Small Team (<10): Tool-Using or Event-Driven Mid-Size (10-50): Orchestrated or Multi-Agent Enterprise (50+): Hierarchical or MCP-Based The 10 Major Architectures - What You Need to Know: High Security Risk (needs guardrails): ↳ Goal-Driven/Autonomous (AutoGPT) - Research and exploration ↳ Swarm Intelligence (CrewAI Swarm) - Collaborative but unpredictable ↳ Memory-Augmented (LangGraph) - Personalization with data governance Medium Security Risk (manageable): ↳ Event-Driven (Zapier AI) - Workflow automation ↳ Hierarchical (AutoGen) - Complex projects with clear delegation ↳ Tool-Using (ChatGPT Tools) - Practical business apps ↳ Planning-Based (ReAct) - Quality-focused workflows ↳ Multi-Agent (CrewAI) - Specialized team coordination Low Security Risk (enterprise-ready): ↳ Orchestrated Systems (LangChain) - Centralized control for regulated industries ↳ MCP-Based (LlamaIndex MCP) - Future-proof interoperability What Actually Matters: The architecture you choose today determines your security posture, compliance overhead, and scaling costs for the next 2-3 years. Most teams choose based on demos. Smart teams choose based on their constraints. The Real Question: Not "which architecture is best?" but "which architecture serves my specific use case, security requirements, and team capabilities?" The visual below (credit to Prem) shows these 10 styles at a glance. Use it as a starting point for the architecture conversation your team needs to have. What's your take? Which architecture are you building with, and what drove that decision? P.S. If you're vibe-coding agents right now without thinking about architecture - you're probably defaulting to Goal-Driven or Tool-Using. That's fine for prototypes. But the transition to production requires intentional architectural choices, not accidental ones.

📱 Designing for Thumbs 🧠 Here’s how users hold their phones: • 49% use one hand • 36% cradle the phone (supporting with one hand, interacting with the other) • 15% use two hands This makes a huge difference in how we design mobile interfaces. If key actions aren’t within easy thumb reach, we create unnecessary friction. Here’s a quick breakdown of the thumb zone: 🟢 Comfort zone – effortless, natural access 🟡 Stretch zone – reachable, but requires effort 🔴 Risk zone – awkward or frustrating to tap If your primary actions sit in the red — your design is likely causing frustration. ✨ Great mobile UX isn’t just clean — it’s comfortable. 💡 I always position primary actions in the green zone — especially navigation, CTAs, and core gestures. Small shifts here make a big difference in usability. Let’s keep bridging the gap between beautiful and usable. 📚 Recommended reads: The Thumb Zone – Scott Hurff - https://lnkd.in/dQyzEjBq One-Handed Mobile Use – Luke Wroblewski - https://lnkd.in/dg5g3QMZ #UXDesign #MobileDesign #UIDesign #ThumbZone #ProductDesign #MobileUX #Figma #DesignThinking #Accessibility #HumanCenteredDesign

There are three patterns for Multi-agent architectures that are more likely to deliver results in real-world applications today Understanding how multi-agent systems work together is important. Most people focus on what individual AIs can do, not how they collaborate. The architecture you select decides if your system provides value or turns into a costly failure. 🔹 1. Hierarchical systems are similar to team product launches. A central leader assigns specific tasks to different agents, such as market research, content creation, scheduling, and design. Then, it brings their results together into a unified product. This method works well when you have complex tasks with clear boundaries and dependencies. 🔹 2. Human-in-the-Loop systems pause for human insight at critical points. When an AI agent spots a client issue, it writes a response but needs human approval before sending it. This isn't about the limits of AI; it’s about knowing when human judgment is essential in important situations. 🔹 3. Sequential architectures function like assembly lines. Each agent performs a specific task before passing it along. Support tickets go through distinct stages, including initial draft creation, history review, solution development, and CRM logging. Each agent uses its skill without overlap or confusion. The key decision is to match your architecture to the complexity of the workflow and your comfort with risk. Use sequential for standard processes, hierarchical for complex coordination, and human-in-the-loop for critical decisions. Your choice of architecture affects whether multi-agent systems boost productivity or create coordination problems. #aiagents