I was filling a 6-step form yesterday. While I wan on step 5, Accidentally dragged the page. It refreshed. And gone back to step 1. Surprisingly all that data gone. As a frontend developer, my first thought was, a single localStorage call could have prevented this. But the better thought came right after. Here's what most devs reach for: localStorage.setItem("form_step", JSON.stringify(formData)) Simple. Works. Survives reloads, tab closes, even browser restarts. But if you want to build it properly, the real pattern is a custom hook: → useEffect watches formData and writes to localStorage on every change → On mount, read it back and restore exactly where the user left off → On successful submission, call localStorage.removeItem() to clean up That's it. 10 lines. Every multi-step form should have this by default. But here's where it gets more interesting: localStorage is synchronous and has no expiry. For a draft form, that's fine. But at scale, you might want: → sessionStorage: clears when tab closes, better for sensitive forms → IndexedDB: for large payloads or file data → A draft API endpoint: if you need cross-device restore The right tool depends on one question: "How long and where should this data survive?" Most apps never ask it. They either lose the user's progress entirely or store it forever with no cleanup. A refreshed page should never cost a user their work. That's not a nice-to-have. That's just good UX. #Frontend #React #JavaScript #WebDevelopment #UX #UIEngineering #Webdeveloper #UI #Form #Validation #Development

Imagine transforming your hand-drawn UI sketches into a working website in just seconds. 😊 I recently built Sketch2Code, an AI tool that takes your rough sketches and generates production-ready React and Tailwind code. It even includes a live preview and downloadable HTML. What sets this tool apart is its ability to interpret your intent. For instance, a simple rectangle labeled "button" is converted into a fully functional button, complete with shadows, hover states, and realistic placeholder text generated by the AI. Here's how it works: - Google Gemini 2.5 Vision analyzes the sketch image. - A FastAPI backend manages requests with a multi-model fallback system, ensuring over 99% uptime on the free tier. - The frontend is built with React, Vite, and Tailwind, featuring drag-and-drop upload, a live sandboxed iframe preview, and four switchable design systems (Modern, Minimal, Playful, Corporate). - The entire deployment is done on Google Colab and Ngrok, resulting in zero hosting costs. Total build time: a weekend. Total hosting cost: $0. Total instances where this would have been impossible a year ago: countless. The implications are significant: - Designers can prototype at incredible speeds. - Developers can bypass tedious CSS tasks. - Founders can validate UI concepts without waiting for a development team. - Students can learn frontend development by observing AI in action. Will tools like this replace manual frontend work, or will they simply add another layer to the development stack? Share your thoughts below. If you're interested, drop a 💡 and I can share the prompt engineering breakdown—it took more iterations than I care to admit. #AI #ComputerVision #FullStack #React #Python #FastAPI #Gemini #MachineLearning #WebDevelopment #BuildInPublic #SoftwareEngineering #DesignToCode #ArtificialIntelligence

🚀 Day 9 / 21 — Frontend Challenge Today I built: 👉 Weather App 🧠 Flow I designed before coding: • Step 1: Identified core UI elements (search box, weather icon, temperature display, humidity/wind details, loading spinner, error message) and planned a centered card layout. • Step 2: Structured the HTML containers, initially hiding the weather content, loading, and error states using a CSS class. • Step 3: Designed the visual aesthetic using CSS variables, a dark gradient background, and backdrop-filter to create a modern "glassmorphism" panel effect. • Step 4: Implemented an async/await JavaScript function to handle data fetching. • Step 5: Connected to the Open-Meteo Geocoding API to convert the user's city search input into latitude and longitude coordinates. • Step 6: Chained a second request to the Open-Meteo Forecast API using those coordinates to fetch current temperature, humidity, wind speed, and weather codes. • Step 7: Created a helper function (getSimpleWeather) to map raw WMO numerical weather codes into human-readable descriptions (e.g., "Clear sky", "Rain") and corresponding icon URLs. • Step 8: Wrote DOM manipulation logic to inject the fetched data into the HTML and toggle the visibility of the loading spinner and main content area. • Step 9: Added event listeners to trigger the search on both button click and "Enter" keypress, alongside a try/catch block to gracefully show an error message if the city isn't found. 🛠 Tech Used: HTML | CSS | JavaScript | REST APIs ✨ Features: • 🔍 Real-time city search using Geocoding • 🌡 Accurate temperature, humidity, and wind speed data • 🌤 Dynamic weather icons and floating animations • 🔮 Modern Glassmorphism UI design • ⏳ Interactive loading spinner and error handling states • ⌨️ "Enter" key support for seamless UX 🚧 Challenges Faced: The biggest challenge was managing asynchronous data flows. Because the weather API requires coordinates, I had to successfully complete the Geocoding API call first, extract the lat/long, and pass them into the second API call. Translating raw numerical weather codes into usable descriptions and matching them with the correct image icons also required setting up a precise mapping function. 💡 Key Learning: Mastering async/await for sequential API requests is incredibly powerful. I also learned how crucial it is to manage UI states (loading vs. success vs. error) to give the user a smooth, informative experience while waiting for network requests. 🙏 Guidance by: Keyur Gohil 🏫 Learning at: Red & White Skill Education Official 📂 GitHub Repo: https://lnkd.in/djpKXQcP #21DaysJSWithKeyur #JavaScript #FrontendDevelopment #BuildInPublic #WebDevelopment #APIs #WeatherApp

How I chained three different AI tools to build a production-ready, Wes Anderson-inspired website from scratch. 🧵👇 I recently wanted to see how far I could push an AI-assisted development workflow. The goal? A fully responsive, single-page website for "Mendl's Patisserie" (from Wes Anderson's The Grand Budapest Hotel), but built with modern, scalable web practices. Here is the exact pipeline I used: 1️⃣ Information Architecture (Claude.ai): I started by treating Claude as a Senior Information Architect. Instead of asking for code, I asked it to map out the site structure, content strategy, purpose, and visual tone/color palette. 2️⃣ Prompt Engineering (Claude.ai): Next, I had Claude translate that approved architecture into a highly specific prompt optimized for UI generation, enforcing constraints like Tailwind CSS, smooth scrolling, and sticky navigation. 3️⃣ UI Generation (Google Stitch): I fed that mega-prompt into Google Stitch. After a few iterative tweaks in the Stitch environment, I had a beautiful, working UI source code that perfectly captured the aesthetic. 4️⃣ Final Build & Refinement (Google AI Studio): Finally, I brought the code into AI Studio. We stripped away the heavy React dependencies, converted the entire project into a blazing-fast Vanilla HTML/CSS/JS build, fixed the typography to get that authentic letterpress feel, and wired up a custom mobile DOM navigation. Takeaway: The future of web development isn't just asking an AI to "build a website." It's about treating AI as a specialized team member at each stage of the pipeline—from IA, to UI generation, to final code compilation. Check it out in my Projects -section: https://lnkd.in/d6aqg4mH #WebDevelopment #GenerativeAI #PromptEngineering #TailwindCSS #VanillaJS #GoogleAIStudio #GoogleStitch #ClaudeAI #Frontend

Spent the weekend testing Claude Design on the Inferred Edge OS frontend. Quick thoughts: Really good at rapid visual exploration and inventing design patterns — better than Claude Code for a UI first pass. The handoff to Claude Code worked decently well. But it fabricated UI and data that didn't exist, even with the full codebase uploaded. And the output is vanilla JSX/CSS, so we had to rewrite to fit our stack. Aesthetic defaults are still pretty generic SaaS dashboards. For us: Claude Code + a designer wins for production, no contest. Claude Design is a different tool for a different job (like building my own personal Pinterest alternative). The bigger question this whole process raised though — what does delightful interaction with an AI agent actually look like? No model has that answer baked in because it isn't in the training data. It's a genuinely new design surface — the right patterns don't exist yet, so we have to invent them from scratch for every use case. That's exactly what we do at Inferred Edge, both in our own OS and for our clients. This is the frontier — and it's all we think about. #EnterpriseAI #AIAgents #AnthropicPartner #AIEngineering #AIAgentDesign

They say if you leave IT for a year, you’re a junior again. I’ve been out for three, but it feels like I’ve just stepped into the future. So many things have changed that at first, it was pretty scary to find myself lagging behind. However, it turned out that I'm still capable of finding, analyzing, and converting even the most technically challenging information into solid work (Btw, AI gave me a nod of approval!). To test my "gears," I’ve put together a snapshot of the React ecosystem as it stands today in 2026. Key trends in React component libraries in 2026 By 2026, React library Components have evolved far beyond a simple set of UI elements. They have transformed into full-stack architectural solutions, thus shifting the core focus from aesthetic issues to runtime performance and scalability. Let's take a look at key trends that define React Components as of today: 1. AI-Driven Development As Components have become AI-friendly, time-to-market has significantly decreased. That is, with the help of AI-assisted tools, frontend developers are no longer forced to manage every boilerplate detail manually, enabling them to dedicate more time to building complex system logic. 2. RSC-First Unlike previous years, when the number of library features impacted the page load speed, the adoption of React Server Components (RSC) today offloads heavy tasks to the server itself. Consequently, the client-side bundle size is minimized, turning the loading process into a seamless user experience. 3. Accessibility (A11y) Formerly, making a digital product truly inclusive used to be a painstaking task, but not now. Each React Component, from a simple button to a complex dashboard, comes with built-in ARIA patterns. As a result, the team saves time on development and ensures that the solution meets the needs of all users by default (WCAG compliance). 4. Customization and Styling The days when frontend developers had to rewrite hundreds of code lines to modify the color or font in the library are over. While working on the design tokens, it’s enough for teams to introduce alterations in just one configuration file to observe the corresponding changes in the whole product. Hence, the desired style is delivered in a substantially small amount of time. Conclusion As you can see, in 2026, React libraries are aimed at making the development process faster, simpler, and more robust. A library is not just a collection of components, but a foundation for creating digital experiences that work for everyone. Looking ahead, we may witness the transformation of the role of frontend specialists: from builders to system architects. And it has become possible thanks to the libraries that cover all the technical production issues automatically, thereby freeing the teams to devote their time to the main goal – ensuring an impeccable user experience. #React #TechTrends2026 #ITCareer

If you’re using Claude Code but your frontend still looks like a developer tool from 2012, you’re leaving value on the table. Here’s a practical way to connect Claude Code with Google Stitch to generate a clean, production-ready frontend without wasting hours on UI polish. The idea Claude Code handles logic and structure. Google Stitch handles design and layout. You separate concerns properly instead of forcing one tool to do everything. --- Step 1. Generate structured output in Claude Code In Claude Code, don’t just ask for UI. Ask for a structured, predictable JSON. Example prompt: “Generate a dashboard layout as JSON with sections, components, and content. Keep it compatible with frontend rendering.” You want output like: - sections - component types (cards, tables, charts) - data bindings - labels and content This becomes your “design API”. --- Step 2. Normalize the schema Before sending anything to Stitch, standardize the JSON: - consistent naming (e.g. "header", "card", "cta") - no nested chaos - predictable hierarchy If the structure is messy, Stitch won’t produce clean results. --- Step 3. Feed JSON into Google Stitch In Google Stitch: - import your structured JSON - map components to UI elements - define layout rules (grid, spacing, typography) Think of Stitch as a visual compiler. It transforms structured intent into design. --- Step 4. Apply design system constraints This is where most people fail. Set: - typography scale - color tokens - spacing system - component consistency Without this, your frontend will look AI-generated in the worst way. --- Step 5. Export and connect to frontend From Stitch: - export components (React / HTML / CSS depending on your setup) - connect dynamic fields back to your app logic - replace static placeholders with real data Now your Claude-generated structure becomes a real UI. --- Step 6. Iterate with feedback loop Refine by cycling: Claude Code → JSON → Stitch → UI → back to Claude Ask Claude: - “Improve UX hierarchy” - “Simplify layout” - “Reduce cognitive load” You’re not designing manually. You’re directing the system. --- Key insight Stop asking AI for “a nice UI”. Instead: - generate structure with Claude - generate design with Stitch - connect them with a clean schema That’s how you get scalable, repeatable frontend quality. --- Common mistakes - dumping raw text instead of structured data - skipping schema normalization - ignoring design system rules - expecting one tool to do everything --- If you set this up once, you can generate entire interfaces in minutes, not days. #AI #FrontendDevelopment #NoCode #LowCode #UXDesign #ProductDesign #ClaudeAI #GoogleTools #WebDevelopment #Automation

🚀 React Suspense — Handle Loading UI Like a Pro You’ve implemented lazy loading… 👉 But what happens while the component is loading? That’s where React Suspense comes in. 💡 What is Suspense? Suspense lets you: 👉 Show a fallback UI 👉 While waiting for something to load ⚙️ Basic Example import React, { Suspense, lazy } from "react"; const Dashboard = lazy(() => import("./Dashboard")); function App() { return ( <Suspense fallback={<div>Loading...</div>}> <Dashboard /> </Suspense> ); } 👉 Displays fallback until component loads 🧠 How it works ✔ Component is lazy-loaded ✔ Suspense “waits” for it ✔ Shows fallback UI ✔ Renders component when ready 🧩 Real-world use cases ✔ Lazy loaded routes ✔ Large dashboards ✔ API data (with frameworks) ✔ Component-level loading states 🔥 Why Suspense Matters 👉 Without Suspense: ❌ Blank screen or broken UI 👉 With Suspense: ✅ Smooth loading experience ✅ Better UX ⚠️ Common Mistake // ❌ Forgetting fallback <Suspense> <Dashboard /> </Suspense> 👉 Causes rendering issues 🔥 Best Practices ✅ Always provide meaningful fallback UI ✅ Use skeleton loaders (better UX) ✅ Combine with lazy loading ❌ Don’t overuse nested Suspense unnecessarily 💬 Pro Insight (Senior-Level Thinking) 👉 Suspense is not just for loading… 👉 It’s a foundation for async UI in React 📌 Save this post & follow for more deep frontend insights! 📅 Day 28/100 #ReactJS #FrontendDevelopment #JavaScript #ReactHooks #PerformanceOptimization #WebDevelopment #SoftwareEngineering #100DaysOfCode 🚀

I've been frustrated with AI-generated UI for a long time. Not because the tools are bad. But because they solve the wrong problem. You get one beautiful screen. Then you need five more - and suddenly nothing matches. Different spacing. Inconsistent components. A design system that exists only in your imagination. So I built something to fix that. Introducing Coherent Design Method (https://getcoherent.design) - an open-source CLI tool that generates multi-page UI prototypes from a single text prompt. Not just one screen. An entire product. One prompt gives you: - Multiple connected pages with shared components - A design system with reusable UI elements and design tokens - Auto-generated documentation - Clean, deployable code - Next.js + Tailwind + shadcn/ui No vendor lock-in. No black-box output you can't touch. Just production-ready code you actually own. Who is this for? Designers who want to prototype fast without losing consistency. Developers who are tired of rebuilding the same components across pages. Solo founders who need a working UI yesterday. Why did I build it? Because the gap between "AI-generated mockup" and "something I can ship" was still too wide. I wanted to close it - with a tool that thinks in systems, not in screens. The result? I generated a complete SaaS interface in 31 minutes. One prompt. Multiple pages. Consistent design system. Deployable code. Full step-by-step walkthrough - how I generated a complete SaaS interface in 31 minutes 👉 https://lnkd.in/gTWJNCbX ⭐ If you like it or just want to show support - I'd really appreciate a star on GitHub: https://lnkd.in/gUdyikMc #OpenSource #UIDesign #WebDevelopment #ProductDesign #DesignSystem #Prototyping #ShadcnUI #NextJS #TailwindCSS #AITools #IndieHacker #BuildInPublic #BuildInPublic #IndieHacker

Not every assessment feels like a real product build — this one did. As part of a screening proces, I worked on a Finance Tracking Dashboard designed to go beyond basic CRUD and focus on a clean, intuitive user experience. Instead of just “making it work”, I focused on: • Structured and scalable component design • Smooth interactions and modern UI patterns • Meaningful insights from transaction data TechStack: React • Tailwind CSS • Context API The goal was simple — build something that feels like an actual dashboard, not just an assignment. A great experience blending logic with design. Github Link : https://lnkd.in/dNaAS8NS #React #FrontendDevelopment #UIUX #TailwindCSS #Zorvyn #BuildInPublic