How to Handle TDD with AI

Test-Driven Development (TDD) is a disciplined software development approach where tests are written before the actual code, following a Red-Green-Refactor cycle, to ensure code clarity, early bug detection, and confidence in making changes. Although TDD is not being replaced by AI, it is evolving with AI integration, which can assist in generating code and test stubs but presents challenges such as over-engineering, lack of predictability, and automation bias. AI tools like GitHub Copilot can be incorporated into TDD workflows to enhance productivity, yet human oversight remains essential to maintain control over the process. The key is to write tests manually, allowing AI to assist in code generation, while using feedback to improve both tests and code, ensuring that AI complements rather than dominates the development process.

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