Vedant Agarkar’s Post

🚀 Built a Sorting Visualizer from scratch! I recently developed an interactive web application to visualize how sorting algorithms work in real time. 🔍 Features: • Visual representation of array elements • Implemented Bubble Sort, Selection Sort, and Insertion Sort • Adjustable speed and array size • Pause and resume functionality • Color-coded states for better understanding 💡 This project helped me strengthen my understanding of Data Structures and asynchronous JavaScript concepts like async/await. Building this made me realize how important visualization is when learning algorithms. 🔗 GitHub Repository: [https://lnkd.in/ghfQpzGW] Next, I plan to implement Merge Sort and Quick Sort for better performance comparison. #DataStructures #Algorithms #JavaScript #WebDevelopment #DSA #Coding #LearningInPublic

I've wasted hours trying to read tiny labels on architecture diagrams. You find a great technical guide, the system diagram looks amazing — but it's so small you can't read anything. You zoom in → the layout breaks. You try Ctrl+F in a 50-node flowchart… nothing. So I built something to fix it. It's called DiagView — a tiny 19KB open-source tool. It turns any static SVG into an interactive viewer: • Zoom & pan • Search inside diagram nodes • Export to PNG/SVG/PDF • Laser pointer mode for remote reviews I designed the architecture and spec myself to solve a real problem I had — then used AI as a pair programmer for the implementation. The full process is documented in the README as an "Authenticity Statement." I think this is how many of us will build going forward — human vision + AI execution — and I'd rather be honest about it. It works with React, Vue, Svelte, or vanilla JS — and takes one line of code to set up. I'd genuinely love your feedback — especially if you work with system diagrams. Demo and GitHub links in the first comment 👇 #OpenSource #DevOps #Documentation #AIPairProgramming #Engineering #WebDev

 ***I just "fired" my backend code. Here’s why.*** ✂️💻 For MegaMind Content Studio, I realized that maintaining a custom FastAPI backend was slowing down my innovation. Every time I wanted to tweak an AI prompt or add a new distribution channel, I was stuck recompiling and debugging infrastructure instead of refining the product. I decided to pivot: I ripped out the custom "code-behind" and replaced it with a local n8n engine. Why the switch? Visual Logic: Instead of hunting through lines of Python, I can see my AI chaining and data flow visually. If a prompt hangs, I know exactly where. Rapid Prototyping: I can now add features—like syncing to a local DB or auto-posting to WordPress—by dragging a node, not writing a class. Separation of Concerns: My Electron UI handles the "Face," while n8n handles the "Brain." This decoupling makes the entire app more hardened and easier to scale. The goal was to move from "Building Infrastructure" to "Building Value." By using n8n as my local middleware, I’ve gained total control over the AI research-to-post lifecycle without the technical debt. The future of "Vibe Coding" isn't just writing code with AI—it's orchestrating it. #BuildInPublic #LocalAI #ElectronJS #n8n #Automation #Ollama #SoftwareArchitecture

A few days ago, I shared a rough prototype of a local LangGraph agent I built to automate my cuts and captions. But it had a fatal flaw: it lacked visual polish. Python is incredible for logic, but for smooth, dynamic animations, CSS is king. So, as an end-to-end product engineer, I completely re-architected the system to get the best of both worlds. Today, I am sharing the very first fully rendered video from the new MVP. (Check the video below 👇) Here is the craziest part: 90% of the editing you are watching was handled autonomously by AI. The only manual work I actually did? 1️⃣ Uploading the raw file. 2️⃣ Hitting "Export". Here is exactly how the architecture works under the hood: 🧠 The Agentic Engine (Python) Once the raw file drops in, my local LangGraph agent takes over. It automatically scrubs the timeline, removes dead air, identifies the best takes, and generates a highly accurate transcript. 🎨 The Styling Frontend (Next.js + Remotion) The agent then passes those refined assets to a custom web editor. Instead of manually tweaking keyframes, I just select a minimalist, glassmorphism-inspired preset. The high-performance UI bakes the styling directly into the video. ⚙️ Built to Scale As I mentioned yesterday, this is no longer just a local prototype. I've implemented a local-first server architecture to simulate cloud file-handling, and integrated Model Context Protocol (MCP) so I can guide the agent seamlessly. I went from being "cooked" by my workflow to having an autonomous pipeline that does the heavy lifting. Creators: If you didn't have to scrub through timelines or manually sync captions, what would you do with that extra 2 hours a day? Let me know in the comments—I’ll be inviting a few people to test the early beta soon! 🚀 #AIProductivity #LangGraph #ProductEngineering #Nextjs #ContentCreation #AIAgents

The Birth and Death of JavaScript: A 2026 Retrospective Gary Bernhardt's 2014 conference talk, "The Birth & Death of JavaScript," presented a satirical but technically grounded 20-year prediction for the software industry. The timeline designates 2026 as a critical juncture, making it the perfect time to evaluate his theories against current reality. The Foundation: asm.js to WebAssembly Bernhardt's entire prediction hinged on asm.js, a highly optimizable, strictly typed subset of JavaScript that served as the precursor to modern WebAssembly (Wasm). The architectural goal was to bypass writing JavaScript directly. Instead, developers would write in languages like C, C++, or Rust and compile them down to run natively in the browser. While early experiments produced massive 3MB bundles that strained VMs, they successfully proved that the browser could function as a universal compilation target. The "Metal" OS Architecture The most extreme phase of Bernhardt's prediction was called "Metal." He theorized that the overhead of traditional operating systems-specifically the calls between ring 0 and ring 3-would be eliminated. The proposed solution was to place a JavaScript VM directly inside the OS kernel. In this environment, every program would compile to asm.js, relying entirely on VM isolation rather than traditional OS memory management. The 2026 Reality Check and the AI Disruption While the industry has not adopted the "Metal" kernel architecture, the core concept of compiling backend languages for the web is thriving through WebAssembly. Wasm is heavily utilized in modern infrastructure, powering thick applications like Figma and enabling multi-language support on edge networks like Cloudflare Workers. Bernhardt's timeline failed to account for one major variable: the explosion of artificial intelligence. He predicted that developer frustration would force the shift to a Wasm-only world by 2025. Instead, the rapid advancement of AI and generated code completely shifted the industry's trajectory, changing how software is written and deployed before his terminal predictions could fully materialize. #JavaScript #WebAssembly #Wasm #SoftwareEngineering #TechHistory #CloudArchitecture #ArtificialIntelligence #Programming

I just launched a website without writing a single line of code. 🚀 I’ve always had ideas for tools, but the "coding barrier" usually slowed me down. This weekend, I decided to see how far I could get using just Claude as my primary architect for CalcBharat.online. The result? A fully functional Financial & Utility Calculator hub, built from scratch and deployed on Netlify. How it worked: Prompting as Logic: Instead of syntax, I focused on structure. I described the math (SIP, FIRE, Step-Up logic), and Claude handled the Next.js and Tailwind CSS. The "Antigravity" Workflow: We went through iterations—fixing broken layouts, integrating ReCAPTCHA, and setting up Server Actions for the contact form—all through dialogue. This isn't a post about being a "10x developer." It’s a post about how AI is turning the "idea-to-execution" pipeline into a casual afternoon project. If you have a tool you've wanted to build, the barrier to entry is officially gone. Check it out here: https://calcbharat.online 🇮🇳 #AI #BuildInPublic #NoCode #NextJS #ClaudeAI #CalcBharat

You have shipped a layout bug that had nothing to do with CSS. It was a text measurement bug. Pretext just hit 36K stars on GitHub. It does multiline text measurement in pure TypeScript.  No DOM. No getBoundingClientRect. No layout reflow. But "no DOM" is not the interesting part. The interesting part: you can know exact text height before render. That flips the pattern from: render → measure → patch → repeat to: measure → predict → render once It quietly fixes problems most teams just live with: → og:image text wrapping that breaks on long titles → PDF overflows on dynamic names → canvas text that never matches the DOM → jumpy masonry cards on load → chat bubble sizing that flickers In AI products this matters even more. Text is generated dynamically everywhere. Chat, cards, summaries, previews, PDFs. All of it is unpredictable length. I have debugged enough "why is this text overflowing" tickets to know - 90% of the time it is not a CSS problem. It is a measurement problem. Pretext by Cheng Lou 👇 https://lnkd.in/dy2n-utx How many of your layout bugs were really just text measurement bugs? #frontend #webdev #typescript #opensource #devlife

I’ve always believed that the strength of an alumni network lies in how easily members can help one another grow. I recently wrapped up a project built to bridge that gap: an Alumni Job Dashboard built with Django and Tailwind CSS. The goal was to create a seamless end-to-end experience: ✅ For Recruiters: Seamless job posting and applicant management. ✅ For Decision Makers: Integrated "Accept/Reject" workflows to keep the pipeline moving. ✅ For Networking: A direct messaging system to connect with applicants instantly. Focusing on a clean UI with Tailwind allowed me to keep the UX intuitive while Django handled the heavy lifting of the backend logic and real-time communication. Check out the repo here: https://lnkd.in/dsU3x7mx #Django #Python #WebDevelopment #TailwindCSS #AlumniNetwork #BuildingInPublic

🚀✨ 𝐄𝐱𝐜𝐢𝐭𝐞𝐝 𝐭𝐨 𝐒𝐡𝐚𝐫𝐞 𝐌𝐲 𝐋𝐚𝐭𝐞𝐬𝐭 𝐏𝐫𝐨𝐣𝐞𝐜𝐭! 𝐈’𝐯𝐞 𝐛𝐮𝐢𝐥𝐭 𝐚 𝐁𝐚𝐢𝐫𝐚𝐧 𝐒𝐨𝐧𝐠 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐑𝐞𝐞𝐥 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐨𝐫 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 🎬 Now you can simply upload a 6-second video clip, and the system automatically transforms it into a cinematic, Bairan-style edited reel 🎥⚡ ⚙️ How it works: Upload your clip ➝ Processed by system ➝ Instantly generated stylish reel 💫 🛠 Tech Stack: 🐍 Python (Backend video processing) ⚛️ React (Frontend UI) 🔥 Flask + Media automation pipeline 💡 Key Highlights: ✨ Fully automated reel generation ⚡ Fast & seamless processing 🎬 No manual editing needed 🚀 End-to-end full-stack integration 📚 What I learned: 💻 Video processing using Python 🌐 Full-stack development (React + Flask) 🤖 Building automation-based creative tools 🔗 GitHub Links: Backend: https://lnkd.in/ddDyUUYC Frontend: https://lnkd.in/d_m7EZcp 🙏 Open for feedback, suggestions, and improvements! #Python #ReactJS #Flask #FullStackDevelopment #VideoProcessing #Automation #AI #WebDevelopment #ProjectShowcase #CodingLife 🚀🔥