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Core principle: If you didn’t watch the test fail, you don’t know if it tests the right thing.

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The Iron Law

NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST
Write code before the test? Delete it. Start over.
Violating the letter of the rules is violating the spirit of the rules. No exceptions.

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When to Use

Always:
  • New features
  • Bug fixes
  • Refactoring
  • Behavior changes
Exceptions (ask first):
  • Throwaway prototypes
  • Generated code
  • Configuration files
Thinking “skip TDD just this once”? Stop. That’s rationalization.

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Red-Green-Refactor

TDD follows a strict three-phase cycle:
1

RED: Write Failing Test

Write one minimal test showing what should happen.Good test:
test('retries failed operations 3 times', async () => {
  let attempts = 0;
  const operation = () => {
    attempts++;
    if (attempts < 3) throw new Error('fail');
    return 'success';
  };

  const result = await retryOperation(operation);

  expect(result).toBe('success');
  expect(attempts).toBe(3);
});
Clear name, tests real behavior, one thing.Bad test:
test('retry works', async () => {
  const mock = jest.fn()
    .mockRejectedValueOnce(new Error())
    .mockRejectedValueOnce(new Error())
    .mockResolvedValueOnce('success');
  await retryOperation(mock);
  expect(mock).toHaveBeenCalledTimes(3);
});
Vague name, tests mock not code.Requirements:
  • One behavior
  • Clear name
  • Real code (no mocks unless unavoidable)
2

Verify RED: Watch It Fail

MANDATORY. Never skip.
npm test path/to/test.test.ts
Confirm:
  • Test fails (not errors)
  • Failure message is expected
  • Fails because feature missing (not typos)
Test passes? You’re testing existing behavior. Fix test.Test errors? Fix error, re-run until it fails correctly.
3

GREEN: Minimal Code

Write simplest code to pass the test.Good implementation:
async function retryOperation<T>(fn: () => Promise<T>): Promise<T> {
  for (let i = 0; i < 3; i++) {
    try {
      return await fn();
    } catch (e) {
      if (i === 2) throw e;
    }
  }
  throw new Error('unreachable');
}
Just enough to pass.Bad implementation:
async function retryOperation<T>(
  fn: () => Promise<T>,
  options?: {
    maxRetries?: number;
    backoff?: 'linear' | 'exponential';
    onRetry?: (attempt: number) => void;
  }
): Promise<T> {
  // YAGNI - over-engineered
}
Don’t add features, refactor other code, or “improve” beyond the test.
4

Verify GREEN: Watch It Pass

MANDATORY.
npm test path/to/test.test.ts
Confirm:
  • Test passes
  • Other tests still pass
  • Output pristine (no errors, warnings)
Test fails? Fix code, not test.Other tests fail? Fix now.
5

REFACTOR: Clean Up

After green only:
  • Remove duplication
  • Improve names
  • Extract helpers
Keep tests green. Don’t add behavior.
6

Repeat

Next failing test for next feature.

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Visual Workflow

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Why Order Matters

Tests written after code pass immediately. Passing immediately proves nothing:
  • Might test wrong thing
  • Might test implementation, not behavior
  • Might miss edge cases you forgot
  • You never saw it catch the bug
Test-first forces you to see the test fail, proving it actually tests something.
Manual testing is ad-hoc. You think you tested everything but:
  • No record of what you tested
  • Can’t re-run when code changes
  • Easy to forget cases under pressure
  • “It worked when I tried it” ≠ comprehensive
Automated tests are systematic. They run the same way every time.
Sunk cost fallacy. The time is already gone. Your choice now:
  • Delete and rewrite with TDD (X more hours, high confidence)
  • Keep it and add tests after (30 min, low confidence, likely bugs)
The “waste” is keeping code you can’t trust. Working code without real tests is technical debt.
TDD IS pragmatic:
  • Finds bugs before commit (faster than debugging after)
  • Prevents regressions (tests catch breaks immediately)
  • Documents behavior (tests show how to use code)
  • Enables refactoring (change freely, tests catch breaks)
“Pragmatic” shortcuts = debugging in production = slower.
No. Tests-after answer “What does this do?” Tests-first answer “What should this do?”Tests-after are biased by your implementation. You test what you built, not what’s required. You verify remembered edge cases, not discovered ones.Tests-first force edge case discovery before implementing. Tests-after verify you remembered everything (you didn’t).30 minutes of tests after ≠ TDD. You get coverage, lose proof tests work.

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Good Tests

QualityGoodBad
MinimalOne thing. “and” in name? Split it.test('validates email and domain and whitespace')
ClearName describes behaviortest('test1')
Shows intentDemonstrates desired APIObscures what code should do

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Example: Bug Fix

Bug: Empty email accepted
1

RED

test('rejects empty email', async () => {
  const result = await submitForm({ email: '' });
  expect(result.error).toBe('Email required');
});
2

Verify RED

$ npm test
FAIL: expected 'Email required', got undefined
3

GREEN

function submitForm(data: FormData) {
  if (!data.email?.trim()) {
    return { error: 'Email required' };
  }
  // ...
}
4

Verify GREEN

$ npm test
PASS
5

REFACTOR

Extract validation for multiple fields if needed.

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Red Flags - STOP and Start Over

If you:
  • Wrote code before test
  • Wrote test after implementation
  • Test passed immediately
  • Can’t explain why test failed
  • Added tests “later”
  • Think “just this once”
  • Think “I already manually tested it”
  • Think “Tests after achieve the same purpose”
  • Think “It’s about spirit not ritual”
  • Think “Keep as reference” or “adapt existing code”
  • Think “Already spent X hours, deleting is wasteful”
  • Think “TDD is dogmatic, I’m being pragmatic”
  • Think “This is different because…”
All of these mean: Delete code. Start over with TDD.

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Common Rationalizations

ExcuseReality
”Too simple to test”Simple code breaks. Test takes 30 seconds.
”I’ll test after”Tests passing immediately prove nothing.
”Tests after achieve same goals”Tests-after = “what does this do?” Tests-first = “what should this do?"
"Already manually tested”Ad-hoc ≠ systematic. No record, can’t re-run.
”Deleting X hours is wasteful”Sunk cost fallacy. Keeping unverified code is technical debt.
”Keep as reference, write tests first”You’ll adapt it. That’s testing after. Delete means delete.
”Need to explore first”Fine. Throw away exploration, start with TDD.
”Test hard = design unclear”Listen to test. Hard to test = hard to use.
”TDD will slow me down”TDD faster than debugging. Pragmatic = test-first.

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When Stuck

ProblemSolution
Don’t know how to testWrite wished-for API. Write assertion first. Ask your human partner.
Test too complicatedDesign too complicated. Simplify interface.
Must mock everythingCode too coupled. Use dependency injection.
Test setup hugeExtract helpers. Still complex? Simplify design.

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Verification Checklist

Before marking work complete:
  • Every new function/method has a test
  • Watched each test fail before implementing
  • Each test failed for expected reason (feature missing, not typo)
  • Wrote minimal code to pass each test
  • All tests pass
  • Output pristine (no errors, warnings)
  • Tests use real code (mocks only if unavoidable)
  • Edge cases and errors covered
Can’t check all boxes? You skipped TDD. Start over.
TDD is not about testing. It’s about design. Tests written first guide you toward simple, decoupled, testable code. Tests written after just verify whatever you already built.

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