Spell It Out: Rules for an AI Coding Assistant

This is the third post in my series about working with an AI coding assistant. The first two covered getting started and early observations. This one is about what happened when I started writing down the rules.

AI Coding Assistant: More Observations from a Practitioner

In February, I wrote about my early experience using an AI assistant for Test-Driven Development, TDD. This is a follow-up. It may become a series, we'll see. A lot has happened in the six weeks since that post, and I have more to say.

TDD with an AI assistant, my perspective as a beginning practitioner

I have been practising Test-Driven Development for more than 25 years. The red-green-refactor cycle is second nature.

I have of course heard a lot about AI tools and LLMs over the last couple of years. The times I have tried them, I have not been impressed. Their proposals didn't compile. They seemed to solve the wrong problem. This was probably because they lacked the context of the project I'm working on. Honestly, a lot of what I have seen has been rubbish.

Not too long ago I saw a thread on LinkedIn where some people who I know really know what they are doing discussed their experience with AI assistants and specifically Claude Code. I decided to give it a try.