Software Development

AI has become a standard part of professional software development workflows. This section covers how to use AI effectively at each stage of the development lifecycle — from translating requirements into code to reviewing, debugging, and safely refactoring existing systems — with the verification habits that keep AI-generated code production-safe.

In This Section

Requirements to Code

Translating a specification or user story into working code with AI — prompting, iteration, and validation workflows.

Pair Programming

Using AI as a programming partner — keeping it on task, iterating effectively, and knowing when to stop and think yourself.

Code Review with AI

Using AI to augment your code review — what it catches well (security patterns, bugs) and what it misses (business logic, context).

Debugging Workflows

How to give AI the right context to help debug — error messages, stack traces, minimal reproduction cases, and reading AI-suggested fixes critically.

Refactoring Safely

Using AI to improve existing code without breaking it — scoping changes, verifying behaviour preservation, and testing after AI refactors.