AI & Tools

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. ...

This is the last Quick Build in the series. We have built a CLI app, a REST API, a landing page, and a Chrome extension. Now we build something that runs 24/7 and interacts with real users: a Discord bot. Discord bots are a great test for Claude Code because they involve: An external API (Discord API) Event-driven architecture Slash command registration Permission handling Error recovery Deployment for uptime Total time: 71 minutes. Most of that was fighting with slash command registration. ...

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. ...

Chrome extensions are different from anything we have built so far. There is a specific architecture (background scripts, content scripts, popups), a manifest file that Chrome parses, and browser APIs that work differently from regular web APIs. This is a good stress test for Claude Code. Can it handle Manifest V3 correctly? Does it know the Chrome extension APIs? The project: a tab manager extension called “TabFlow” that shows all open tabs, lets you search them, close duplicates, and save sessions for later. ...

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. ...

We built a CLI app and a REST API with Claude Code. Both were backend projects. Now let’s see how Claude handles the visual side: a modern landing page with responsive design, animations, and dark mode. The project: build a landing page for a fictional SaaS product called “FlowBoard” — a project management tool. No React, no frameworks. Just HTML, CSS (Tailwind), and a tiny bit of vanilla JavaScript. Total time: 38 minutes from empty folder to live on Netlify. ...

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. ...

Last time we built a CLI todo app in 35 minutes. That was a local app. This time, we go bigger: a REST API that runs on the web. The goal: build a bookmark manager API with CRUD operations, pagination, search, rate limiting, tests, and a Docker setup. All with Claude Code prompts. Deploy it and get a live URL. Total time: 52 minutes from empty folder to deployed API. What We’re Building A bookmark manager REST API with these features: ...