After a full-stack blog, a weather dashboard, a desktop app, and a mobile app, we close Part 2 with something different: a backend microservice in Go. Go is interesting for vibe coding because the language is simple and opinionated. There is usually one way to do things. Claude should have an easier time generating idiomatic Go than, say, idiomatic Rust. Let us find out. Total time: 2 hours 14 minutes. 6 prompts. Go’s simplicity made this the fastest Part 2 project. ...

This is the hardest project in Part 2. Kotlin Multiplatform has a complex build system, platform-specific code patterns, and a Gradle configuration that can break in surprising ways. Can Claude handle it? I was skeptical going in. KMP projects have dozens of Gradle files, expect/actual declarations, and platform-specific dependencies that need to match exact versions. One wrong version number and nothing compiles. Total time: 4 hours 31 minutes. 6 prompts. Most of the time was fighting Gradle. ...

Building a desktop application is different from building a web app. You have to deal with the operating system: file dialogs, menu bars, keyboard shortcuts, window management. Electron makes this possible with web technologies, but the architecture — main process vs. renderer process — trips up many developers. Can Claude handle it? I gave it a full markdown editor spec and found out. Total time: 3 hours 47 minutes. 7 prompts. Electron’s IPC was the biggest time sink. ...

API integration is one of the things developers do most and enjoy least. Parsing JSON, handling errors, managing loading states, formatting data for charts. It is repetitive work. This is where Claude Code earns its keep. I gave it an API, a design goal, and a list of features. It handled the rest. Total time: 2 hours 38 minutes. 6 prompts. The charts took the longest. What We’re Building A weather dashboard with: ...

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. ...

Welcome to Part 2 of the series. The Quick Builds are done. Now we build real applications — the kind that take a full afternoon and have multiple moving parts. First up: a full-stack blog platform. Not a static site. A real blog with a database, admin panel, markdown editor, authentication, and SEO features. The kind of project that would normally take a weekend. Total time: 3 hours 22 minutes. 7 prompts. A lot of debugging auth. ...

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. ...