What is spec-driven development with AI?
Spec-driven development makes an explicit description of intended behavior a working input to implementation. With AI coding tools, the specification helps communicate scope, constraints, and acceptance conditions before code is produced. It remains a document that people must challenge, test, and revise when evidence changes.
What does the source say?
GitHub’s Spec Kit describes a structured process for specification-driven work with coding agents. The tool provides a process aid, not proof that a written specification is complete or that generated code meets business needs.
How can you apply this?
Write a short specification for one behavior: user, problem, desired result, constraints, and observable acceptance examples. Ask a colleague to identify an ambiguity before implementation begins. After a prototype, compare the observed behavior with the original intent and update the specification only when the change is deliberate and justified.
What should you watch out for?
Do not use a large document to conceal uncertainty. Unsupported requirements can be implemented very efficiently and still solve the wrong problem.