Hey network! 👋 As a Full Stack Developer juggling everything from Next.js interfaces to Python backend logic, my IDE is essentially my second home. Over the past few months [particularly, Since Antigravity released], I've spent a lot of time tweaking Antigravity to eliminate friction and fit my exact workflow. I decided it was time to share the wealth, so I just published a new blog post: "My Setup: Antigravity Extensions I Can't Live Without" 🚀 In the article, I break down the 9 tools that keep me productive, keep my code clean, and even keep me a little entertained during long debugging sessions (yes, digital pets are involved 🐶). Whether you're building out responsive web apps, bridging the gap with React Native, or diving deep into machine learning models, there's something in this list to supercharge your setup. Read the full breakdown here: https://lnkd.in/gBWBpq2S I'm always looking to upgrade my environment—what is the absolute first extension you install on a fresh machine? Let me know in the comments! 👇 #Antigravity #FullStackDeveloper #WebDevelopment #ReactJS #Python #DeveloperProductivity #Coding

🚀✨ 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 🚀🔥

Pro Tip: Do not try to learn or pick up every single new shiny AI tool out there. Do the old methods, and pick a stack that works for you, and that you understand like the back of your hand, and stick with it. Here's mine: Frontend: React, TanStack Query, Tailwind CSS, ShadCN UI Backend: Python, Django, DRF, Django Ninja or FastAPI AI Tool: Claude Code in VSCode (not the agentic mode). Works every time. What's your development stack?

🚀 Excited to Share My Latest Project: Fake News Detection Web App 🧠📰 In today’s digital world, misinformation spreads faster than ever. To tackle this challenge, I built a Machine Learning-based Web Application that helps users identify potential fake news in real-time. 🔍 What this project does: Analyzes news articles or headlines using ML models Provides confidence scores for authenticity Displays visual insights for better understanding Maintains a history of analyzed content Educates users on spotting fake news ⚙️ Tech Stack Used: Frontend: React, TypeScript, TailwindCSS, Chart.js Backend: Python, Flask, Scikit-learn Other: REST API, CORS 💡 This project focuses on combining AI + Web Development to create a practical solution for a real-world problem. ⚠️ Note: This tool is designed to assist users, not replace critical thinking. Always verify information from trusted sources. 🔗 GitHub Repository: https://lnkd.in/gvKsmEij I’d love to hear your feedback and suggestions! 🙌 #MachineLearning #WebDevelopment #Python #ReactJS #AI #FakeNews #TechForGood #OpenSource #Flask #DataScience #FrontendDevelopment #BackendDevelopment #FullStackDeveloper #Innovation

💡 Learning AI agents with JavaScript just got easier Microsoft just released a free LangChain.js course with hands-on examples to help developers build real AI applications. This matters because: • You can build AI agents using JavaScript/TypeScript (no need to switch to Python) • It focuses on practical concepts like tools, agents, and real workflows • Includes 70+ runnable examples to learn by doing It’s a solid starting point if you want to move beyond simple chatbots and build real AI systems. https://lnkd.in/duepMsXW

💻 Full Stack Development Workflow – From Basics to Advanced Building modern web applications is not just about coding — it's a complete workflow. 🔹 1. Tech Overview   Understanding Frontend vs Backend fundamentals  🔹 2. Coding Phase   Writing clean and efficient frontend & backend code  🔹 3. Development Setup   Working on powerful desktop environments for better productivity  🔹 4. AI Integration   Using AI tools to enhance development and analytics  🔹 5. Code Analysis   Managing and optimizing large-scale codebases  ✨ Full Stack Development is all about combining creativity with logic and continuously improving skills. 🚀 Currently, I am learning and building projects using Python & Django, while exploring full stack development step by step. 📌 What stage are you currently in your development journey? #FullStack #WebDevelopment #Python #Django #Frontend #Backend #AI #Coding #LearningJourney

I just spent months debugging my own AI-generated code. The result? A JavaScript Visualizer that finally shows what's actually happening behind the scenes. Quick test — without running this, what prints first? Promise.resolve().then(() => console.log(1)); setTimeout(() => console.log(2), 0); queueMicrotask(() => console.log(3)); console.log(4); Most beginners memorize the answer. Almost nobody understands why. The "why" lives in the call stack, the microtask queue, the macrotask queue, and the event loop — concepts that are practically invisible in a normal debugger. So I built a tool that makes them visible. ▶️ Watch the call stack push and pop, line by line ▶️ See setTimeout park in Web APIs, then graduate to the task queue ▶️ Watch promise callbacks line up as microtasks ▶️ See the event loop pick the next job in real time ▶️ Live memory graph — stack frames on the left, heap objects on the right ▶️ Every step annotated with the actual ECMAScript spec reference Built almost entirely with AI. It took months. The hard part wasn't the UI — it was making the simulated runtime match the real one. I had to fix async/await microtask ordering, super.method() resolution in class hierarchies, TDZ when parameters shadow outer consts, try/finally semantics on early return, await rejection inside try/catch — and 40+ other edge cases. After 48 differential tests against real Node.js, the engine finally produces identical output. I have a planning to deploy it soon. If you teach JavaScript — or you're still learning it — this is going to save you (or your students) weeks of confusion. #JavaScript #LearnJavaScript #WebDevelopment #BuildInPublic #AI #EventLoop #AsyncJavaScript #FrontendDev #100DaysOfCode #CodingJourney #SoftwareEngineering #Programming #DeveloperCommunity #JSVisualizer #TechTwitter

🚀 AI Tool for Developers: Streamlit Recently explored Streamlit, a powerful Python framework used to build and deploy data-driven web applications quickly. 💡 How it works: 🔹 Build web apps using pure Python 🔹 Convert ML models into interactive apps 🔹 Add inputs, buttons, and charts easily 🔹 Deploy apps without complex frontend 💡 Benefits: ✅ Fast AI app development ✅ No need for HTML/CSS/JS ✅ Great for showcasing ML projects ✅ Used in real-world applications As someone learning AI & Machine Learning, tools like Streamlit help me turn models into real applications. Building and deploying AI apps is becoming easier 🚀 Have you tried Streamlit or similar tools? #AI #Streamlit #Developers #MachineLearning #Python

I used to wonder if I needed to learn Python to stay relevant in the AI space. Turns out — not really. Python owns model training and research. That's its world. But as a TypeScript developer, my job is building things people use — and for that, TS is fantastic: - Type-safe LLM API integrations - AI-powered web and mobile apps - Edge inference with ONNX and TensorFlow.js #TypeScript #AI #JavaScript #WebDevelopment

Github: https://lnkd.in/gfzkaTYn Stylme, an AI-powered virtual try-on MVP for shopping websites. It combines a Chrome extension and a FastAPI backend to detect apparel product pages, extract product context, let users build a wardrobe across browsing sessions, and generate try-on outputs from uploaded photos. Current MVP includes: - Chrome MV3 side-panel experience - generic apparel detection across shopping sites - wardrobe memory for tops, bottoms, and full outfits - photo upload and camera capture - backend-powered preview and HQ generation - pluggable inference/provider layer Tech stack: TypeScript, React, Chrome Extensions, FastAPI, Python. #AI #ChromeExtension #FastAPI #React #TypeScript #Python