Guide AI Agents Through Test-Driven Development (elite-ai-assisted-coding.dev)

AI agents can be steered to follow Test-Driven Development (TDD) to produce more reliable, requirement-aligned software by enforcing a strict tests-first workflow and isolated contexts. The recommended approach has agents draft comprehensive tests (unit/integration as specified) from requirements alone, then iterate on implementation only after human-approved tests exist. This harnesses agents’ rapid iteration and self-correction while preventing them from shortcutting specification or producing code that doesn’t meet defined behavior. Practically, the workflow is: (1) Generate tests first and explicitly specify test type; (2) manually review and refine tests to ensure they capture desired behavior; (3) switch the agent to implementation with a clear mandate—“Do not return until all tests pass”—so it runs tests, analyzes failures, and refines code in a feedback loop. To stop agents from “peeking” at existing code during test creation, run test-generation sessions in an isolated environment (e.g., launch from the project’s /tests directory), then move to the project root to implement. Working in ordered phases rather than parallel agents preserves TDD discipline, reduces specification drift, and improves overall code quality and auditability when using AI-driven development.