Leverage AI for Boilerplate and Testing

Impact: MEDIUM

Generate 80% of boilerplate and non-critical code using AI, allowing us to focus solely on complex business logic and critical architectures.

Where AI excels:

Generating boilerplate code (DTOs, basic CRUD operations)
Building comprehensive test suites
Creating documentation
Repetitive refactoring tasks
Code review assistance

Where humans must focus:

Complex business logic
Critical architectural decisions
Security-sensitive code
Performance-critical algorithms
Domain-specific edge cases

Example - AI-assisted test generation:

typescript

// Human writes the function
export function calculateOverlap(slot: TimeSlot, busy: BusyTime): boolean {
  return slot.start < busy.end && slot.end > busy.start;
}

// AI generates comprehensive tests
describe("calculateOverlap", () => {
  it("returns true when slot starts during busy period", () => {
    // AI-generated test case
  });

  it("returns true when slot ends during busy period", () => {
    // AI-generated test case
  });

  it("returns false when slot is completely before busy period", () => {
    // AI-generated test case
  });

  it("returns false when slot is completely after busy period", () => {
    // AI-generated test case
  });

  it("returns true when slot completely contains busy period", () => {
    // AI-generated test case
  });

  it("returns true when busy period completely contains slot", () => {
    // AI-generated test case
  });

  // AI identifies edge cases humans might miss
  it("handles exact boundary matches correctly", () => {
    // AI-generated edge case
  });
});

Our CI is the final boss:

Everything in our standards document is checked before code is merged in PRs
No surprises make it into main
Checks are fast and useful
AI helps ensure comprehensive coverage

Reference: Cal.com Engineering Blog