Automate Your Portfolio with GitProfolio

Every developer has faced this problem — building a project takes days or weeks, but writing a proper README takes hours. And often, that README decides whether your project gets noticed or ignored. To solve this, I built 𝗥𝗘𝗔𝗗𝗠𝗘 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗼𝗿 — a full-stack web application that automatically generates structured, professional README files using AI. The application connects directly with your GitHub account using OAuth, fetches your repositories, and allows you to select any project. Once selected, the backend analyzes the repository structure, code, and metadata, and generates a complete README within seconds. Key capabilities: • GitHub OAuth authentication (no manual setup required) • Repository search and filtering • AI-based README generation tailored to your project • Preview rendered output or view raw Markdown • Download, copy, or directly commit README to GitHub • Syntax-highlighted code sections and structured formatting Tech Stack: • Frontend: React.js • Backend: Node.js • Deployment: Vercel Frontend Repository: https://lnkd.in/dc8ex_f4 Backend Repository: https://lnkd.in/dZ2RfB7R This project focuses on reducing manual effort and improving project presentation, especially for developers who regularly build and publish repositories. The project is open source, and contributions are welcome. #WebDevelopment #OpenSource #GitHub #AI #FullStack #DeveloperTools

Every NuGet package looked brilliant in its README too. A year ago I was using GitHub Copilot for basic autocomplete. Today, 95–99% of code in our .NET projects is AI-generated — we negotiate architecture with agents in plan mode, implement full features including tests in one go, and use GitHub and Confluence MCP tools to ground every decision in our actual codebase. The productivity gains are real. I'm not here to argue otherwise. But here's what I now tell my team: treat AI like a NuGet package with a great README, not like a senior peer. The happy path works in ten minutes and you feel brilliant. Then staging blows up. A version conflict breaks your injection container. A leaky abstraction surfaces under load. The original maintainer went dark six months ago and now you own a security vulnerability buried in three lines of code you never actually read. That's not a .NET cautionary tale. That's an AI story playing out in production systems right now. METR's 2025 randomised controlled trial found experienced developers were 19% slower using AI tools — despite predicting they'd be 24% faster. The bottleneck has shifted. It's no longer writing code. It's absorption capacity: can your team genuinely understand, own, and debug what's being shipped? Every line of AI-generated code is not an asset. It's a maintenance contract you signed without reading the terms. The shift I'm making: code author to Editor-in-Chief. Before you hit Tab on that ghost text, pause three seconds. Don't ask "does this look right?" Ask: "if this throws a NullReferenceException at 3am on Sunday, do I know exactly why.. or would I have to ask the AI to explain my own system back to me?" If it's the latter, the model is in control. Not you. Stop asking how much code you can generate. Start asking how much you can maintain. What's your test for knowing you still own your codebase - and AI is just the tool? #DotNET #SoftwareEngineering #AIEngineering #TechLeadership #EnterpriseArchitecture #CSharp #AgenticAI

Introducing LongCat Assistant (Beta Version) I needed a tool that could quickly summarize any page, explain complex concepts, and help me understand long docs or GitHub repos without leaving the page. Instead of relying on paid tools like Claude (which has a Chrome extension exclusively but consumes a lot of tokens)… I decided to build something that fits my workflow. So I connected it to a different free model, optimized the responses to get similar results, and kept my Claude tokens for more important tasks. So I built LongCat Assistant 🐱 A Chrome Extension that adds an AI sidebar to your browser, reads the current page, and lets you ask anything about it instantly. ✨ Key Features: 📖 Page Reading — automatically reads the current page 💬 Smart Chat — ask anything about the page 🔄 Auto Detection — detects tab or page changes 🧠 Chat Memory — conversation persists while the extension is open 📝 Markdown Rendering — clean, structured responses (headers, lists, code) ⚡ Quick Actions: (Summarize, Key Point, Explain Simply, Important Info) 📌 If you want to try it or check the code: GitHub: https://lnkd.in/dwiaHbSJ #AI #ChromeExtension #Productivity #Developers #WebDevelopment #JavaScript #OpenSource #GitHub #BuildInPublic #Tech #Automation #SideProject

Almost 2 years ago I was comparing GitHub Copilot to RooCode like it was a meaningful debate. Looking back at that post now, it's almost funny. We were still in the autocomplete mindset, treating AI as a smarter tab completion. A lot has changed since then. The tools evolved (Cursor, Windsurf, Claude Code), but the tools weren't the real shift. The real shift was moving from "write this function" to "let's think through this service boundary." That's where the actual leverage is. Developers who treat AI as a faster way to write code will get a modest productivity bump. Developers who use it to think more clearly about architecture, boundaries and trade-offs, get something else entirely. If the gap between 2023 and now felt this large, I have no confident model for 2030. But that's fine. The engineers who treat this as a thinking tool rather than a shortcut are going to be in a very good place. Still learning. Still recalibrating. But the trajectory feels right. #SoftwareEngineering #TypeScript #FullStack #NodeJS #WebDevelopment #AITools

Not all GitHub repos need thousands of lines of code to be valuable. Stumbled across something on GitHub trending that made me stop and read twice. One repository with over 90k stars, and it's a single markdown file! 🤯 A set of guidelines specifically for Claude Code that helps reduce common LLM mistakes, like ignoring your intent, modifying code it shouldn't touch, or drifting from what you actually asked for. I've been using Claude Code on my personal projects and this is now a permanent part of my workflow. Worth using as a foundation for your own AI development workflow. https://lnkd.in/dHsnrzNG #claudecode #AI #webdevelopment #developer

This article discusses how GitHub Copilot CLI utilizes the Rubber Duck model to provide developers with a second opinion on code suggestions. I found it interesting that this approach leverages different model families to enhance coding efficiency and reduce errors. What strategies are you using to ensure code quality and accuracy in your projects?

I like #GitHub. Love the way it is built. And recently, I came across GitHub Trending for the first time. I had no idea this page existed. Turns out, there is a page that shows which repositories are gaining the most stars right now. With so many contributions happening every day in AI, automation, and developer tooling, it is a great pulse check on what the community actually cares about. So I thought, what better way to showcase a new tool I built than to let it demo GitHub Trending itself? The attached video is a 1-minute 43-second walkthrough. Two AI speakers have a natural conversation, exploring trending repos, filtering by Python, and clicking into a top project. Every word, every click, every scroll — generated from a single JSON file. No screen recording. No video editor. No voiceover session. How it works: - Write a scenes.json — define your speakers, dialogue, and browser actions - Run one command — it generates voice audio, drives a real Chromium browser, and assembles the final MP4 - Done. Polished video, zero editing. Tech stack: - Playwright — drives real Chromium, records the screen - macOS TTS — native voices for narration (Tara + Aman in this demo) - ffmpeg — audio-video sync and final assembly - Node.js + Bash — single command runs the full pipeline What I learned about making AI voices sound natural: - Short sentences. 10-15 words max. TTS handles them much better. - Commas create natural breathing pauses. - Spell out abbreviations. "A-I" not "AI". "A-P-I" not "API". - Punctuation drives everything. Question marks give rising tone. Periods force stops. - Sweet spot is 165-190 words per minute. Where teams can use this: - Customer demos and sprint showcases - Onboarding videos that stay in sync with the actual UI - Pre-sales walkthroughs tailored per customer - QA documentation as video evidence Pro tip: Do not write the scenes.json by hand. Let your AI agent write it. Describe your app and the flow you want. It generates the full script in seconds. Give it a try and share what you build. Working on open sourcing this. Will share the repo link here once it is available. #AIAgents #OpenSource #BuildInPublic #GitHub #Saama

As so many, I'd already landed on a pattern: using one model for development support, a different model family for code review. Just because the reviews were genuinely sharper. No grand theory, just vibes and better results. Turns out GitHub had the same instinct and decided to build it into the tool. Rubber Duck is a new experimental feature in Copilot CLI that pairs your primary coding agent with a reviewer from a completely different model family. For example, a Claude model orchestrates, and a GPT-model critiques... And crucially, it does this before anything gets built, not after you're already committed to a direction. Here's where it gets a bit uncomfortable though: Sonnet paired with Rubber Duck closed 74.7% of the performance gap between Sonnet and Opus on SWE-Bench Pro. Opus on a budget, basically. Great news, obviously, but if a second opinion from a different model family moves the needle that much, it's worth asking what that means for how we should be architecting agentic pipelines in the first place. Because the failure mode here isn't hallucination. It's compounding confidence... One assumption nobody questioned at step 2 quietly becoming a structural problem by step 47. Rubber Duck just asks the awkward questions early, before the damage is already baked in. Essentially a code reviewer who hasn't met you yet and has no reason to be nice. It turns out the duck needed a nemesis. 🐥🔪 I'm curious whether anyone else has stumbled onto patterns like this before the tools caught up? Drop them below, GitHub's clearly taking notes. 📋 Available now via /𝑒𝑥𝑝𝑒𝑟𝑖𝑚𝑒𝑛𝑡𝑎𝑙 in Copilot CLI. #GitHubCopilot #AIEngineering #AgenticAI

Your README is your project's front door. 🚪 You can write the most brilliant code in the world, but if your README is empty, no recruiter will ever know. A great README should include: ✨ A clear project description. 🛠 Tech stack used. 🚀 How to install and run it. 📸 Screenshots or a demo link. Treat your GitHub like a portfolio, not a dumping ground. Need projects that actually impress? KodeMaster AI guides you through building real-world applications in your own editor and pushing them to Git. Make your profile stand out. 📈 Build your portfolio: https://kodemaster.ai/ #GitHub #PortfolioTips #CareerReady #KodeMasterAI

Excited to share something I've been working on 🎉 GemReview is live on npm — and just crossed 850+ downloads 📈 It's an AI-powered CLI tool that reviews GitHub Pull Requests using Google Gemini — and posts findings as inline comments directly on your PR. What started as a personal itch ("I wish someone would catch the obvious stuff before I even ask for review") turned into a full-featured developer tool: ✅ 4 review dimensions — bugs, security, tests, performance ✅ Inline PR comments anchored to the exact diff line ✅ Structured severity summary on every PR ✅ Personal Mode (your own key) + Team Mode (shared org credits) ✅ GitHub Actions integration — automatic reviews on every PR ✅ Works with any programming language ✅ Fully open-source (MIT) Building this taught me a lot about developer tooling, LLM prompt design, and shipping a real product end-to-end. If you're working on a team that could use faster, more consistent code reviews — I'd love for you to try it out. ⭐ https://lnkd.in/gkSMEVeU  📦 npm install -g gemreview #OpenSource #AI #CodeReview #DevTools #GitHub #GoogleGemini #TypeScript #BuildInPublic #SoftwareEngineering