Test-Driven Development (for AI)

Test-driven development (TDD) is a software engineering practice adapted for AI work: instead of making a change and then checking whether it helped, you define what “better” means — in the form of specific test cases and success criteria — before you start experimenting. This prevents the common trap of judging success by how the model “feels” after a change rather than by whether it actually solved the problem you set out to solve. For example, if users are complaining that the model is too verbose, you’d first write a set of test cases that represent the problematic pattern, define what a better response looks like, and only then begin adjusting prompts or training data. For behavior architects, test-driven thinking is a discipline that forces clarity about goals and makes improvement legible.