test suite

A test suite is like an answer key for a school exam. Each question has a fixed correct answer, and once a student submits an answer, it can be checked against the key right away to see if it's right or wrong. It works the same way when AI writes code or solves problems: a pre-built set of checks is run against the output to let a machine, instead of a human, judge whether the result actually works and meets the requirements.

This matters because AI answers can look plausible but often turn out to be wrong once actually run. Instead of having a person review every result by eye, checking whether it passes the test suite makes verification much faster and more consistent. That's why, when combining multiple AI models, a cheaper model can generate an answer first, have it filtered through the test suite, and only the problems it fails get passed on to a more expensive, higher-performing model — saving cost along the way.

The article mentions a "cascade approach that combines test suite verification." This refers to a structure where a cheaper model's answers are first filtered through a test suite, and only the hard problems that fail get passed on to a more expensive model. It's worth not mistaking the test suite itself for some new AI technology — it's an existing software development tool used to verify AI-generated output.