A practical workflow for testing AI-generated code covers four strategies: writing failing tests before prompting the AI (test-first prompting with Jest), property-based testing with fast-check to surface unanticipated edge cases, end-to-end validation with Playwright for UI and integration points, and adversarial AI review prompts to catch hallucinated APIs. The guide includes concrete code examples showing common AI failure patterns (hallucinated methods, off-by-one errors, happy-path-only logic, stale API usage), corrected implementations, and a CI integration checklist. Key rule: never let AI both generate and validate its own code.
Table of contents
How to Test AI-Generated CodeTable of ContentsPrerequisitesThe Testing Dilemma: Code You Didn't Write (and Don't Fully Understand)Why Standard Testing Isn't Enough for AI CodeStrategy 1: Write Tests Before You PromptStrategy 2: Property-Based Testing to Catch What You Didn't Think OfStrategy 3: End-to-End Validation with PlaywrightStrategy 4: Use AI to Test AI (Adversarial Review Prompts)The AI Code Testing ChecklistPutting It All Together: A Realistic WorkflowKey TakeawaysSort: