Spec-Driven Development with GitHub Spec Kit

I just discovered something that changed how I think about AI-assisted development. Git worktrees + Claude Code. If you're not familiar, git worktrees let you check out multiple branches simultaneously in separate folders. No more stashing, no more context switching headaches. Now Claude Code has built-in worktree support. What this means in practice: 1) Each AI agent gets its own isolated workspace 2) You can run multiple tasks in parallel without conflicts 3) Every idea becomes a quick worktree → PR → merge cycle 4) Sub-agents can spin up their own worktrees too One gotcha I noticed from testing: if your main branch isn't protected, the agent might push directly to main instead of the feature branch. Worth setting up branch protection or prompting specifically for the target branch. The bigger insight for me: AI coding isn't magic. It still follows the same fundamentals — isolation, clean branching, fast feedback loops. The tooling just removes the friction. If you're using Claude Code and haven't tried `claude worktree` yet, give it a shot. Parallelization just got a lot cheaper. What's your workflow for managing multiple AI coding tasks? #SoftwareEngineering #ClaudeCode #AI #DeveloperProductivity #CodingTips #Git

Stop "Vibe Coding" and Start Building with Intent 🚀 I’ve been exploring a game-changer for AI-assisted engineering: Spec Driven Development (SDD) using the new GitHub Spec Kit. We’ve all been there—tossing prompts at an LLM and hoping for the best. It’s fast, but it’s often messy and hard to scale. John Capobianco recently demonstrated a much more professional path forward using Claude Code and the Specify CLI. The SDD Workflow Breakdown: 📜 Constitution: Define your project’s "soul"—its tech stack, constraints, and values before a single line is written. 📑 Specification: Draft a full MVP spec with user stories and edge cases. 🔍 Clarification: The AI actually asks you questions to fill in the gaps. 🗺️ Planning & Tasks: Turn that vision into a technical roadmap and a list of atomic, verifiable tasks. 🛠️ Implementation: Only now does the code get written—guided by the specs, not just "vibes." Why this matters: It brings the discipline of traditional software engineering into the AI era. It’s not just about getting code; it’s about getting the right code that fits your architecture and long-term goals. Whether you're building a side-scrolling game (like in the demo!) or a complex enterprise integration, this kit ensures your AI agent is an architect, not just a copy-paster. Check out the full tutorial here: An Introduction to Spec Driven Development (SDD) with the GitHub SpecKit #SoftwareEngineering #AI #ClaudeCode #GitHub #SpecDrivenDevelopment #Programming #SpecKit

In today's fast-paced development world, code reviews can take up 15-20% of a team's time. But what if you could cut that time by 40%? In this video, we explore how AI-powered code review tools like GitHub Copilot, CodeRabbit, and SonarQube are transforming the way developers work. With AI's ability to instantly catch security flaws, coding issues, and bugs, developers can save time and improve the quality of their code. Junior developers also benefit from immediate feedback, accelerating their growth by 3-4 times faster than traditional methods. Learn how Technijian can seamlessly integrate AI-driven code reviews into your CI/CD pipeline, making your workflow faster, more efficient, and more secure. Stay updated with our latest insights: https://lnkd.in/gfW_d6FR Explore our services: https://lnkd.in/gPSHXAVz Contact us for more information: https://lnkd.in/dGAqMDqX #AICodeReview #CodeReview #DevOps #SoftwareDevelopment #AI #CodingTools #GitHubCopilot #SonarQube #CodeRabbit #TechEfficiency #CI_CD #JuniorDeveloper #AIIntegration #TechSolutions #Technijian #TechSupport

The next wave of AI coding tools isn't about faster autocomplete. It's about delegation. Aperant is an open-source framework that runs multiple Claude Code agents in parallel — each working in an isolated git branch, each following a plan-build-validate loop, and each feeding context back into a shared memory layer that gets smarter over time. You describe a goal. It handles the implementation, QA, and merge. I wrote a deep-dive on how it works under the hood — the architecture, the security model, and why the git worktree-as-sandbox approach is clever. Link in the comments if you want the full read. 13.5k ⭐ on GitHub and growing fast. #AI #Engineering #OpenSource #FutureOfWork

Tried GitHub's spec-kit for spec-driven development with an AI agent. Love the idea — let the agent drive development from living specs, not vibes. But in practice it's heavy: lots of commands, templates, mandatory artifacts. Overkill for small projects and lean teams. So I built a lightweight fork: spec-kit-lite. Same idea, stripped to the bone. 3 docs per feature: spec.md — WHAT & WHY tech.md — HOW IT'S WIRED plan.md — HOW TO BUILD IT NOW 4 commands: /specl-sync — sync docs with code, or bootstrap from an existing codebase /specl-take — turn a ticket, description or URL into a feature /specl-plan — draft an implementation plan /specl-go — execute it The killer feature for me: point it at an existing repo and it generates spec.md + tech.md from the actual code. No retroactive documentation theater — docs are born from code and live alongside it. This is an init version — I'm dogfooding it on my own projects. Would really appreciate feedback: what works, what's annoying, what's missing. Issues and stars welcome 🙌 👉 https://lnkd.in/dKkNNkMz #SpecDrivenDevelopment #ClaudeCode #AI

🎉 Just completed "Claude Code in Action" — an official course by Anthropic! Here are the most valuable things I learned that genuinely change how you work with Claude Code: ⚡ SHORTCUTS & CONTROLS → Shift + Tab to switch between Claude modes (like Plan mode) — think before you build → Esc to interrupt Claude mid-task when it's heading the wrong way → Esc + Esc to go back to the conversation without losing context → # to store something in Claude's memory across sessions 🔀 GIT & GITHUB INTEGRATION → Stage, commit, and push directly from Claude — no more context switching between terminals → Tag Claude in GitHub Issues and it will autonomously read the issue, write the fix, and open a Pull Request → Claude can review PRs, suggest changes, and even merge them — turning GitHub into a fully agentic workflow → This means your AI isn't just helping you code locally — it's participating in your entire development lifecycle on GitHub 🧹 CONTEXT MANAGEMENT → /compact to summarize the conversation and keep Claude sharp for upcoming tasks → /clear to wipe context and start completely fresh 📦 SKILLS → Skills are reusable markdown instructions that Claude automatically applies to the right tasks → Create custom Skills for your team's workflows and Claude picks them up at the right moment — no need to repeat yourself every session 🪝 HOOKS (Pre & Post) → Pre-hooks run before Claude takes an action — great for validation, safety checks, or enforcing coding standards before anything is written or executed → Post-hooks run after an action — perfect for auto-formatting, running tests, logging, or triggering downstream processes automatically → Together, hooks let you build guardrails and automation around Claude's actions, making it production-ready rather than just a dev toy The biggest insight? Claude Code isn't just an AI assistant — it's a programmable coding agent you can deeply integrate into your entire development workflow, from local code to GitHub and beyond. Highly recommend the free course on Anthropic Academy if you want to go beyond the basics! 🚀 #ClaudeCode #Anthropic #AI #SoftwareDevelopment #AgenticCoding #DeveloperTools #AITools #GitHub #LearningAndDevelopment #Automation

🧪 Weekend experiment mode: ON. I've been using spec-kit for a while now as my go-to Spec-Driven Development framework. This weekend I wanted to test the waters with something different,GSD (Get Shit Done), a meta-prompting and context engineering system built for exactly one purpose: preventing AI context rot and shipping working code. The project? sbom-drift , a CLI tool that fills a real gap in supply chain security: existing SBOM tools like Syft and Grype tell you what's in an artifact now, but not what changed between releases and why it matters. sbom-drift does the diff. Starting point: a repo with zero production code. Architecture docs, design decisions, a memory document. Nothing else. One GSD session later, with GPT-5.4 via GitHub Copilot: working Go code, automated UAT, and a built-in threat review , all baked into the workflow. My honest take? GSD is faster to set up, more opinionated, and moves faster than Spec-Kit. But Spec-Kit still wins on governance and audit trail, especially if you're working in a team or a regulated environment. Both are legitimate. They just serve different needs. I documented everything: installation, project init, Phase 1 execution, what worked, what I'd do differently. 👉 Full article here: https://lnkd.in/dyEfEtsM #DevSecOps #SpecDrivenDevelopment #AI #GitHubCopilot #OpenSource #SupplyChainSecurity #SBOM #Golang

AI memory for developers. I opened my own PR from two weeks ago. And I had no idea what I was looking at. It was my commit. My code. My name on the diff. But I couldn't remember why I wrote any of it. I tried Git. "fix: bug" which bug? What decision did I make that day? What tradeoffs? all gone. That's when it hit me: The problem isn't that I'm forgetful. The problem is that developers have no way to capture context as we work. Git remembers what changed. Nobody has time to document why because it's a task thing. So every sprint, every week, every day we silently lose a piece of our own work. And one day, three weeks later, your manager asks "what did you ship?" and you freeze. I got tired of that feeling. So I built DevNote. You just press dev note brain icon on VS Code. It reads your git branch diff. You give it one line of context. And it turns the whole thing into a structured memory what changed, why, the key decisions, the files touched synced straight to your Notion workspace. Not a note. A memory. One you can come back to in a month and actually understand and over time, your Notion workspace stops being a doc pile and starts feeling like a second brain. If you've ever opened your own code and thought "what was I doing here?" I built this for you. And honestly, I built it for me. Would love your feedback what works, what doesn't, what's missing. 🙏 Install link in the first comment 👇 #BuildInPublic #VSCode #DeveloperTools #OpenSource #AI

Ever wondered how to turn your codebase into a self‑editing partner? 🤔 I’ve been testing the new GitHub‑Claude Code plugin that lets you call Codex directly from Claude. After a quick setup, you can run a review or delegate a task with a single command, and the feedback comes back as sharp as a senior engineer’s pair‑programming session. What stands out is the blend of speed and depth: the review runs in the background, flags subtle bugs, and even suggests alternative designs. In my recent project, it cut review time by 30% while surfacing edge‑case risks that manual checks missed. 👉 Quick wins you can try today: - Run a baseline review on a feature branch - Use --adversarial-review to stress‑test a critical module - Resume a paused job with the session ID - Track progress with /codex:status - Delegate routine refactors to Codex and reclaim your focus Code reviews are more than finding bugs—they’re about building a culture where every line of code is examined, debated, and improved together. How will you reshape your workflow when AI becomes a permanent teammate? #AI #CodeReview #Leadership #DigitalTransformation #EthicalTech Reference: [https://lnkd.in/gxq36AWs] 🔄 Share 👍 React 🌐 Visit www.aravind-r.com #AravindRaghunathan

We jumped into AI-assisted programming (not vibe-coding), and week one was honestly chaotic. Same ticket, different agent, different naming, different patterns, different everything. Team integration was not fun. What turned it around was treating it like a systems problem and actively applying Agentic SDLC in our real workflow: strong guardrails, context routing, reusable patterns/checklists, and shared memory. If this sounds like your team right now, check out the full dev.to breakdown and grab the Codex template that worked for us. https://lnkd.in/gRnNW6wX