Devpost’s Post

🚀 From vibe coding to agentic engineering-practice makes Claude perfect. I’ve been exploring the new GitHub repo shanraisshan/claude-code-best-practice, which codifies the workflow reshaping how teams build with LLMs. The pattern is simple: Research → Plan → Execute → Review → Ship, and it’s being adopted across the board. What stands out is how the repo maps every stage to concrete artifacts: Prompting, Planning/Specs, CLAUDE.md, Agents, Commands, Skills, Hooks, Workflows, turning intuition into repeatable discipline. 👉 Document your workflow in a CLAUDE.md file 👉 Define clear hooks for agent communication 👉 Automate review cycles with skill libraries 👉 Ship iteratively, not perfectly 👉 Reflect and iterate daily 🤔 At its core, this is about empowering people, not just machines. When we treat AI as a collaborative partner, leadership becomes about guiding purpose, ethics, and continuous learning. How will you redesign your team's workflow to turn every experiment into a shipped outcome? #AI #Leadership #Innovation #DigitalTransformation #Ethics #FutureOfWork Reference: [https://lnkd.in/gbQ5_Yz7] 🔄 Share 👍 React 🌐 Visit www.aravind-r.com #AravindRaghunathan

AI won’t replace developers — but developers who know how to use AI will. VibeKode AI Engineering Bootcamp shows you how to actually work with AI tools in real engineering environments — not just experiment with them. 🎤 Led by: John Davies , an experienced engineering leader bringing real-world insights into AI-driven development and modern software practices. What you’ll learn: ⚡ How to use AI tools (Copilot, Cursor, Claude) effectively in daily workflows 🧠 How to maintain code quality & architecture while moving faster 🛠️ Practical patterns for real-world projects (not toy examples) ⚠️ Where AI breaks — and how to avoid costly mistakes 🚀 How experienced engineers leverage AI for real productivity gains ⏳ Don’t miss this — the gap between developers who understand AI and those who don’t is growing every day. 🔗 Learn more & secure your spot: https://lnkd.in/dQVueaWy #VibeKode #AIBootcamp #SoftwareEngineering #AI #DeveloperTools

Multi-agent coding just became table stakes. And most dev teams haven't caught up. Here's what shifted in February 2026: Cursor, Claude Code, and GitHub Copilot all shipped multi-agent capabilities at the same time. Not a coincidence. This was the industry's collective bet on what comes next. The old model: one AI assistant, one prompt, one response. The new model: multiple agents running in parallel — one writing tests, one refactoring, one reviewing diffs. The data is stark: → 85% of developers now use AI coding tools regularly → Cursor passed $500M ARR → GitHub Copilot has 15 million active developers → But only 3 of 15 agents tested actually changed how teams ship That last stat is the one that matters. Most teams are paying for AI. Few are structuring their work to extract real value from it. The shift isn't about which tool you use. It's about how you break down problems for agents to work on in parallel. That's a workflow design problem — and it's the one most engineering managers aren't thinking about yet. The teams that figure this out in 2026 will ship dramatically faster. The ones that don't will wonder why their AI subscriptions aren't moving the needle. What does your multi-agent workflow look like right now? #AI #DeveloperExperience #SoftwareEngineering #TechLeadership #BuildInPublic

Claude Code burns tokens because every session starts from zero. This free repo (89k⭐) fixes it: It's called everything-claude-code - a Claude Code setup built by an Anthropic hackathon winner after 10+ months of daily use on real products. It upgrades your setup with practical layers: • Token optimization Routes tasks to the right model and trims system prompts to reduce costs • Memory persistence Uses hooks to save context at session end and reload it at the start of the next • Continuous learning Extracts recurring patterns from sessions and turns them into reusable skills • Verification loops Adds checkpoints and evals so outputs don’t just run - they work as intended • Subagent orchestration Manages large codebases via iterative retrieval instead of loading full context It makes sure Claude stays consistent and doesn’t lose context as your codebase becomes more complex. Link to the repo: https://lnkd.in/dyQjDeZq -- P.S. We’re building the best AI English tutor in the world. Try it to improve your speaking, it’s 15x cheaper the human one → GetFluently.app

Especially for professional users, this setup for Claude Code (and 100x for Claude's version of OpenClaw), will allow for significant improvements in token use efficiency. Thank you.

Token management is becoming a core skill for any developer using Claude Code. If you're investing in AI agents, efficiency is everything. Using specialized subagents is a great way to optimize your context window and stop token burn. It's not just about spending less, it's about getting more productivity out of every session. Definitely a must have for anyone scaling their AI workflow

Nextleap Learn in Public Challenge [Post 2/3] "Vibe coding" looks incredibly easy from the outside. You write a prompt, and magic happens, right? The reality? Building my NextLeap GenAI Bootcamp Milestone 2—the Product Pulse and Fee Explainer tool—was a massive reality check. Moving from a product management mindset into actually wiring up the plumbing taught me a few things: deployment is a headache, MCP orchestration is beautifully complex, making a GenAI product truly user-friendly is incredibly hard, and you will stare at errors that look like absolute gibberish. But we shipped it. 🚀 Here is the live demo of Pulse Analytics, an automated product intelligence engine: ⚡️ The Weekly Pulse: Automatically scrapes recent Play Store reviews, clusters them into 7 canonical themes (UI/UX, Performance, etc.), and generates 4-6 lines of high-density, actionable insight per category. 📖 The Fee Explainer: Scrapes live pricing pages and uses a grounded JSON knowledge base to generate strictly neutral, structured explanations for complex fee scenarios. Zero hallucinations, just facts. 🛑 Automated Dispatch: The system uses MCP to automatically sync insights to a tracking Google Doc and draft stakeholder emails via Gmail (all gated by user approval). The secret sauce to getting this over the finish line? Treating my AI Agent as a true pair-programmer. When the Render deployment broke or the JSON payload failed, the agent didn't just "suggest"—it researched the root cause and helped fix the actual plumbing. That collaborative loop is what actually gets things done. The Tech Stack: 💻 Frontend: Vanilla HTML5/JS + Tailwind CSS (Glassmorphic UI) ⚙️ Backend: Python (FastAPI/Flask-style) deployed on Render 🧠 AI Engine: Gemini 2.0 Flash 🔗 Workflows: Model Context Protocol (Google Docs & SMTP Gmail) 🕸️ Data: google-play-scraper & BeautifulSoup4 Check out the build here: 🔗 Live Prototype: https://lnkd.in/gfJ9e3n6 🐙 GitHub Repo: https://lnkd.in/gTTVeV-M #NextLeapAIBootcamp #ProductManagement #AI #Automation #AgenticWorkflows #ProductIntel #PulseAnalytics

The End of "Coding as We Know It"? 💻�  Generative coding isn't just helping us write faster—it's changing how we build the digital world. In 2026, AI-native platforms are allowing developers to focus on architecture and creativity while the AI handles the syntax. The future of dev is here. #SoftwareDevelopment #GenerativeAI #CodingFuture Stay tuned for more tech news and updates