AI

For a while now, I wanted to try out Claude Code but didn’t know how to start. I watched Anthropic’s Mastering Claude Code in 30 minutes, where the speaker (Claude Code’s creator) encouraged getting to know the tool by exploring some unfamiliar codebase. Seeing the way he used it - asking raw questions like “what does this work that way? look through git history” or “why did we fix issue #123 by doing XYZ?” - got me really excited to start a new session in an unfamiliar project and explore it with this CLI partner. So I paused the video, and instead of trying to optimize my first session with hours of research and planning (my usual style), I decided to just try it out and see what happens. But where should I start? ...

The hype around the AI revolution was already picking up speed before I began my software engineering career. The first time it came onto my radar was almost 10 years ago, when DeepMind’s AlphaGo beat the world champion in a game of Go. At first, it felt distant from my daily work as a software engineer - primarily adding APIs for computer vision, natural language processing and some content generation. But in this past year it made another big leap, and this one seems truly revolutionary. What began as a “smarter” autocomplete and test implementer quickly evolved into a good-enough coding assistant, now becoming fully fledged independent agents showing signs of autonomous problem-solving and decision-making. While still expensive and flawed, the rate of improvement is stunning. Even if progress stops now, it’s clear that the effects on our profession are huge. ...