The Problem
You ask AI to "write tests" and get back a test suite that looks great at first glance. It runs. Everything passes. You commit it. Then production breaks because the tests were useless - they tested implementation details, missed edge cases, or had assertions so weak they'd pass with completely wrong code.
The issue: Generic prompts produce generic tests. AI needs specific guidance to write tests that actually catch bugs.
Most developers either accept whatever tests AI generates (dangerous) or write all tests manually (slow). Neither approach leverages AI effectively for test generation.
The Core Insight
Good test prompts include examples, specify edge cases, and demand strong assertions. They teach AI what "working" means for your specific code.
AI can write excellent tests if you provide: the happy path example, edge cases to cover, specific assertion patterns, and the testing philosophy you want followed. Think of your prompt as a brief specification document.