Claude Code

I remember the first time I tried a GitHub Copilot suggestion in IntelliJ IDEA. It felt like magic. You start typing a method name, and suddenly the entire implementation materialises in grey ghost text. You press Tab, and — bam — it’s there. That was impressive. But it was still you doing the driving. In 2026, the landscape has shifted. Claude Code feels different. It’s less “autocomplete on steroids” and more “a colleague who sits next to you, holds the entire 1M token context of your codebase in their head, and then just… gets to work.” Let me show you what I mean. ...

In Part 1, I showed you what Claude Code is and what it can do. You saw an AI agent that reads your project, writes code, runs your build, and fixes its own mistakes. Impressive stuff. But here’s the thing. If you just fire up Claude Code and start prompting, the output you get is… generic. It’s correct, sure. But it doesn’t know your team uses MapStruct instead of manual mapping. It doesn’t know your POST endpoints need authentication. It doesn’t know you measure everything with Micrometer and that a controller without metrics is considered incomplete. ...

Claude Code — Teaching It Your Standards with Skills In Part 2, we turned CLAUDE.md into a precision instrument. We wrote down our conventions, our architecture, our rules — and watched Claude Code go from producing generic boilerplate to code that could survive a code review. But here’s the thing I noticed after a few weeks of working this way: my CLAUDE.md was getting fat. It started small. Build commands, naming conventions, a few architecture rules. Then I added a section on how to generate a complete REST slice. Then testing patterns. Then a procedure for running database migrations with Flyway. Before I knew it, the file was 300 lines long, and every single line was loaded into every single session — whether Claude needed it or not. ...

It was a Friday afternoon and I was in the middle of a long debugging session. I had been going back and forth with Claude Code for maybe forty minutes — adding context, correcting assumptions, exploring three different theories about why a JMS listener was silently dropping messages. The session was getting noisy. Old context from theories I’d already ruled out was still sitting there, cluttering the conversation. I didn’t know about /compact yet. ...

Every team has its boilerplate. At clients, every new REST controller we write follows the same shape: a @RestController with a @RequestMapping, constructor injection (never field injection), a @Slf4j logger, ResponseEntity return types, proper HTTP status codes, and a matching service interface already wired in. Oh, and Lombok. Always Lombok. The first few times I asked Claude Code to generate a controller, I typed all of that out. Every time. A paragraph of instructions just to get the scaffolding right before the interesting work could begin. ...

A couple of months ago I was debugging a tricky data issue and I had three windows open. Claude Code on the left. A psql terminal on the right. A schema diagram in a browser tab somewhere behind. The loop went like this: ask Claude what it thought the issue was, copy a query Claude suggested into psql, run it, paste the output back into Claude, repeat. That’s not pair programming. That’s being a tape recorder between two systems that should be talking to each other. ...