Vibe Coding

Everything from the Vibe Coding series in one reference page. Bookmark this. Come back to it often. Tool Comparison Matrix Feature Claude Code Cursor GitHub Copilot Interface Terminal VS Code fork IDE extension Best at Complex tasks, multi-file changes, debugging UI generation, scaffolding, Composer mode Inline completions, quick suggestions Agent mode Yes (primary mode) Yes (Composer, Background Agents) Yes (Copilot Workspace) Multi-agent Yes (Agent Teams) Limited Limited Context window 200K tokens 200K tokens 128K tokens Local models No Yes (OpenAI-compatible) No MCP support Yes (native) Partial No CLI support Yes (primary) No Yes (gh copilot) Price $20/mo (Pro), $100-200/mo (Max) $20/mo (Pro) $10/mo (Individual) Best for Backend, architecture, complex tasks Frontend, UI, full-stack scaffolding Quick completions, simple edits When to use which: ...

“I feel faster with AI” is not a measurement. It is a feeling. And feelings can be wrong. Some developers report feeling more productive while actually spending more time — because the back-and-forth with AI feels like progress even when it takes longer than writing the code directly. Others underestimate their gains because they do not track the time AI saves on tasks they used to do manually. This article gives you a framework for measuring AI coding productivity with real data. You will learn what to track, how to track it, and how to calculate whether your AI tools are actually paying off. ...

AI writes code fast. That speed creates a new problem: your git history becomes a mess. You end up with massive commits titled “implement feature,” PRs with 50 changed files, and no way to tell which code a human wrote and which code AI generated. Good git hygiene matters more in an AI-first workflow, not less. This article covers practical git patterns for AI-assisted development — from commit structure to PR workflows to attribution tracking. ...

Andrej Karpathy coined “vibe coding” in February 2025. Sixteen months later, it is a $4.7 billion market, a Collins English Dictionary Word of the Year, and the default way most developers work. The pace of change is unprecedented. This article looks at where vibe coding is heading — based on what is already happening today and the trajectory of current trends. These are not wild guesses. They are extrapolations from real products, research papers, and market data. But predictions are predictions — treat them as likely directions, not certainties. ...

Throughout this series, you have learned tools, techniques, and workflows for coding with AI. Now let us step back and look at what all of this means for how we build software — and how we grow as developers. AI-first development is not about using AI as a helper. It is about designing your entire workflow around AI from the start. The shift is real, measurable, and already happening. In 2026, 92% of US developers use AI coding tools daily. The question is no longer whether to use AI — it is how to use it without losing the skills that make you a good developer. ...

Every prompt you send to Claude, GPT, or Gemini goes through the internet to a data center. For most coding tasks, that is fine. But there are real reasons to run AI models locally — on your own machine, with no data leaving your network. This article covers when local models make sense, how to set them up with Ollama, and how to connect them to your existing tools. You will also get an honest comparison of local vs cloud models for coding tasks. ...

Browser extensions are the perfect vibe coding project. They are small in scope, have a clear structure, give you instant visual feedback, and the manifest format is strict enough that AI generates correct configurations most of the time. In this article, you will build a Chrome extension with AI — from the first prompt to publishing on the Chrome Web Store. The tool: Cursor as the primary AI editor. The project: PR Summary — a GitHub pull request summarizer that adds a one-click summary button to PR pages. When you click it, it extracts the PR diff, sends it to an AI API, and displays a plain-English summary right on the page. ...

Mobile development is where AI tools face their toughest test. Android has complex APIs, Jetpack Compose changes fast, and platform-specific patterns do not always match what AI learned from web development tutorials. In this article, you will build a complete notes app with Kotlin and Jetpack Compose. You will use Claude Code as the primary tool (running alongside Android Studio) and Copilot for inline completions. Every prompt, every AI mistake, and every manual fix is shown. ...

You have built a CLI tool and a REST API with AI. Now let us go full-stack. You are going to build a complete analytics dashboard with a frontend, backend, database, authentication, and charts — all in one project. The project: DevPulse — a developer activity dashboard that tracks coding sessions, displays charts, and lets users manage their data. It uses Next.js, Tailwind CSS, PostgreSQL, and Auth.js for authentication. This project uses three AI tools together: Cursor Composer for scaffolding and UI, Claude Code for backend logic and database work, and Copilot for inline completions. You will see how they complement each other in a real workflow. ...

In the previous article, you built a CLI tool with AI. Now let us scale up. You are going to build a complete REST API — with a database, authentication, tests, and deployment — all driven by AI. The project: a Notes API that lets users create, read, update, and delete notes. It includes user registration, authentication with JWT, PostgreSQL storage, and proper error handling. Simple enough to build in one session, complex enough to show real patterns. ...