AI Engineering
Why AI Increases the Need for TDD
2026-08-10 · 2 min
AI coding tools reduce the cost of producing an implementation. They do not reduce the cost of being wrong in production.
Test-driven development was never primarily about typing tests first for ceremony. It is a design and verification discipline: clarify behaviour, constrain change, and create a fast feedback loop.
AI makes that discipline more valuable. Generated code can look complete while encoding subtle misunderstandings of requirements, boundaries or failure modes.
TDD gives AI-assisted work a hard edge. Behaviour is specified before implementation expands. Regressions become detectable. Reviewers can argue about intent rather than only style.
The practical leadership move is not “ban AI until tests exist”. It is to make verification non-optional in the path of delivery — locally, in CI, and in Definition of Done.
Organisations that treat AI as a typing accelerator will ship more code. Organisations that treat AI as an accelerator inside a verification system will ship more confidence.