We Learned to Generate Requirements with AI – and Forgot to Check Their Quality

We Learned to Generate Requirements with AI – and Forgot to Check Their Quality

When software code breaks syntax rules, it fails immediately. This built-in quality gate made automated code generation with AI a logical next step.

Natural language requirements never had such protection. For decades, we relied on human reviews to decide whether requirements were clear, complete, and unambiguous – because machines simply couldn’t understand them.

Large Language Models changed that. And yet, instead of introducing automated quality control, the industry rushed straight into AI-generated requirements.

This talk argues that requirement generation is not the real breakthrough – requirement validation is. You will learn how LLMs can analyze requirement quality, detect ambiguity, missing details, and weak formulations, and act as an objective quality gate before development even starts. It’s time to use AI not just to write faster, but to write better.