Scaffolded Test-First Prompting: Get Correct Code From the First Run

If you use AI to help with coding, the most common failure mode is not that the model is lazy. It is that the target is fuzzy. You ask for a fix, the assistant guesses what “correct” means, and you get something that looks plausible but is slightly off: wrong edge case, wrong file, wrong abstraction, wrong dependency, or the right idea implemented far too broadly. A simple way to reduce that failure rate is to stop asking for the fix first. Ask for the test first. I call this Scaffolded Test-First Prompting: a small workflow where you ask the assistant to write a runnable failing test, then ask it for the smallest implementation that makes that test pass. It is not fancy, but it turns vague coding requests into executable contracts. Why this works Most prompting problems in code work are really specification problems. When you say: Fix the currency formatter for German locales. there are a dozen hidden questions: What file owns the behavior? What format is expected exactly? Which runti