AI can dramatically accelerate two of development's most neglected tasks: testing and documentation. Instead of treating these as afterthoughts, AI makes them fast enough to do properly.

Generating Unit Tests

Prompt Template: "Write unit tests for this function using [Vitest/Jest]. Cover: happy path, edge cases, error handling, and boundary values. Use describe/it blocks with clear test names."

Example: "Write Vitest tests for this useCart hook: [paste hook code]

Cover:

• Adding items to empty cart
• Adding duplicate items (should increment quantity)
• Removing items
• Updating quantity to zero (should remove item)
• Calculating total price
• Clearing the cart"

Tips for Better Test Generation:

• Specify the testing framework and assertion style
• List the scenarios you want covered
• Provide mock data patterns if your tests need them
• Ask for both unit tests and integration tests separately

Generating Integration Tests

"Write integration tests for the /api/users endpoint. Test:

• GET /api/users returns paginated user list
• POST /api/users creates a new user with valid data
• POST /api/users returns 400 for invalid email
• DELETE /api/users/:id requires authentication Use supertest and a test database."

Test-Driven Development with AI

A powerful workflow:

1. Write the test first (with AI help): "Write a failing test for a function that calculates shipping cost based on weight, distance, and shipping method"
2. Ask AI to implement the function to pass the tests
3. Review and refine both tests and implementation

Generating Documentation

JSDoc/TSDoc: "Add comprehensive JSDoc comments to this file. Include @param, @returns, @throws, @example for each public function."

README Generation: "Generate a README.md for this project. Include: project description, tech stack, setup instructions, environment variables, API endpoints, and contribution guidelines. Here are the key files: [list relevant files]"

API Documentation: "Generate OpenAPI 3.0 documentation for these API routes. Include request/response schemas, error codes, and example payloads: [paste route handlers]"

Inline Code Comments: "Add clear inline comments explaining the non-obvious logic in this code. Don't comment on obvious things like 'increment counter'. Focus on WHY, not WHAT."

Maintaining Documentation

AI can help keep docs current:

• "I changed the user registration flow — update the relevant sections of our README"
• "Generate a CHANGELOG entry for these commits: [paste commit messages]"
• "Update the API documentation to reflect the new pagination parameters"

Code Review with AI

Use AI as a code reviewer:

• "Review this PR for potential bugs, performance issues, and code style. Be critical."
• "Does this implementation have any security vulnerabilities?"
• "Suggest improvements for readability and maintainability"

Tests and documentation are no longer slow. With AI, a well-tested, well-documented codebase is achievable for every project.