Build on GitHub to Verify Your Skills

Quick Quiz: What’s the biggest 'red flag' on a junior dev's GitHub right now? 🚩 Is it: A) Too many forks? B) No README? C) Portfolio full of browser-made "sandboxes"? D) No green squares? The answer is C. Recruiters can tell when you haven't worked in a professional local environment. On KodeMaster AI, you don't code in a browser-based playground. You use your favorite editor, push to Git, and get instant test feedback: just like you would at a Top-Tier tech company. Let’s clean up that GitHub with real projects. #CodingTips #JuniorDev #GitHub #SoftwareEngineering #CareerGrowth #KodeMasterAI

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

Your GitHub is already your portfolio. You’re just not using it that way. Most developers: • manually pick projects • rewrite descriptions • maintain separate portfolios And it gets outdated… fast. So I built something to fix that. 👉 GitProfolio — https://lnkd.in/gZ3v6hKJ It converts your GitHub into a structured, portfolio-ready JSON. Not just raw data — it actually understands your work: • Ranks your projects based on impact (stars, forks, recency) • Extracts clean descriptions from messy READMEs • Detects your real tech stack automatically • Finds live project links (Vercel, Netlify, etc.) • Highlights your top projects instantly And if you want more: It can also generate insights to: • improve your repo visibility • suggest better descriptions & topics • give project ideas that attract stars No more manually maintaining portfolios. Your GitHub becomes your portfolio — automatically. Built using Astro, GitHub API, and AI-powered analysis. Would love to hear what you think 👇 #GitHub #WebDevelopment #DeveloperTools #OpenSource #Portfolio #BuildInPublic #IndieHackers #JavaScript #AI #DevTools

Stop treating GitHub like a file storage system and start treating it like your most valuable marketing tool. 💼 We worry about the formatting of our PDF resumes👨💻, but often leave our README.md blank. 🤷♂️ Your GitHub profile is an interactive, searchable, and proving-ground for your engineering claims. It’s where my passion for machine learning and my current focus on Java tools for backend development in Miro live side-by-side. 🤩 #Miro #Innovation #PersonalDevelopment #Motivation #Management #Technology #Business Your code is great, but how you present that code makes all the difference. What's the best tip you’ve received for optimizing your GitHub profile? Let me know in the comments! 👇 #Coding #TechStack #TechHiring #CareerTips #EngineeringManager #Recruitment #GitHubProfile #Engineering #Portfolio #CareerAdvice #TechHiring #OpenSource #Programmer #JobSearch #SoftwareEngineering #TechCareers #ResumeTips #GitHub #DeveloperLife #CareerGrowth #JavaDeveloper

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

Google For Github Repo's, Search any github repo in minutes. This is day #13 of 100X, Follow for remaining Journey!!! Spending hours digging through unfamiliar GitHub repos for one function feels like a waste of your most valuable asset: time. Meet Repogrep: your AI-powered coding agent designed to provide ultra-fast codebase search capabilities across *any* public GitHub repository. Whether you start with a specific URL or a broad keyword, Repogrep quickly navigates you to the insights you need. Ready to navigate the open-source galaxy at warp speed? LINK IS ON PIN COMMENT! Explore Repogrep today and let me know your biggest win in the comments! 👇 #AI #SoftwareDevelopment #OpenSource #GitHub #DeveloperTools #CodeSearch #TechInnovation #BuildInPublic #100DaysOfAI #AIwithAkash

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

**3 PRs merged into GitHub's spec-kit here's my open-source journey so far** Over the past week, I've had 3 pull requests merged into github/spec-kit an open-source specification framework. --- 🔹 PR #1: Documentation fix (Mar 31) Found that AGENTS.md was out of sync with the actual agent configuration. Several agents were missing from the docs. Synced everything up so developers aren't confused when onboarding. --- 🔹 PR #2: Community catalog extension (Apr 1) Added the fix-findings extension to spec-kit's community catalog, making it discoverable and installable for all users. --- 🔹 PR #3: argument-hint frontmatter for Claude Code (Apr 3) This was the big one. When users typed slash commands like /speckit-plan in Claude Code, there was no hint about what input the command expects. I built a post-processing pipeline that injects argument-hint into YAML frontmatter for all 9 Claude Code skill commands. Now users instantly see prompts like "Describe the feature you want to specify" right inline. This PR went through: ✅ Multiple rounds of code review with the maintainer ✅ A rebase when upstream merged a major architecture change ✅ 6 targeted tests The maintainer's feedback genuinely improved the final code. --- 📌 What this journey taught me: 💡 Start small (docs fix), build trust, then take on bigger features 💡 Code review isn't criticism it's collaboration 💡 Open source rewards consistency and quality over speed --- 🚀 Currently working on PR #4 adding Table of Contents to generated markdown documents. --- #OpenSource #GitHub #Python #AI #ClaudeCode #SoftwareEngineering #SpecKit #WomenInTech