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TDD was already the gold standard. Paired with an agent, it becomes the tightest feedback loop in software. Here's the full workflow and the pitfalls.
Test-driven AI development pairs classical TDD with an agent. You write the test. The agent writes the code. The test runs. Green or red tells you immediately whether the agent delivered. No hand-waving, no vibes-based shipping.
// src/pricing.test.ts
import { describe, it, expect } from 'vitest';
import { priceCart } from './pricing';
describe('priceCart', () => {
it('returns 0 for empty cart', () => {
expect(priceCart([])).toBe(0);
});
it('sums item prices', () => {
expect(priceCart([{ price: 10 }, { price: 5 }])).toBe(15);
});
it('applies 10% discount when total > 100', () => {
expect(priceCart([{ price: 120 }])).toBe(108);
});
it('rounds to 2 decimals', () => {
expect(priceCart([{ price: 10.005 }])).toBe(10.01);
});
});
// Now say to the agent:
// "Implement src/pricing.ts so all tests in pricing.test.ts pass.
// Only edit pricing.ts — do not modify the tests."Four tests describe the whole contract. The agent has zero room to invent requirements.Property-based tests let you describe invariants instead of examples. The framework generates hundreds of random inputs and checks the property holds. Paired with an agent, you get code that survives inputs neither of you thought to write.
import fc from 'fast-check';
it('is always non-negative', () => {
fc.assert(
fc.property(
fc.array(fc.record({ price: fc.float({ min: 0, max: 1000 }) })),
(items) => priceCart(items) >= 0
)
);
});fast-check generates ~100 randomized carts per run. AI-written code that passes examples often fails properties — this catches it.Mutation testing deliberately breaks your implementation (flips a greater-than to less-than, removes a plus-one) and checks whether your tests catch the mutant. If your tests pass on broken code, your suite has holes. Tools like Stryker and MutPy automate this. Use them quarterly to audit AI-written test suites — they often miss edge cases humans would catch.
Tests are the only specification that runs. Agents are the only implementation that listens.
— A modern TDD practitioner
The big idea: the test is the contract, the agent is the contractor, and the suite is the inspector. Done right, TDD-with-AI is the fastest way to ship correct code that has ever existed.
15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-coding-test-driven-ai-development-creators
What is the core idea behind "Test-Driven AI Development"?
Which term best describes a foundational idea in "Test-Driven AI Development"?
A learner studying Test-Driven AI Development would need to understand which concept?
Which of these is directly relevant to Test-Driven AI Development?
Which of the following is a key point about Test-Driven AI Development?
Which of these does NOT belong in a discussion of Test-Driven AI Development?
Which statement is accurate regarding Test-Driven AI Development?
Which of these does NOT belong in a discussion of Test-Driven AI Development?
What is the key insight about "Tell the agent what not to edit" in the context of Test-Driven AI Development?
What is the key insight about "Watch for test smell" in the context of Test-Driven AI Development?
Which statement accurately describes an aspect of Test-Driven AI Development?
What does working with Test-Driven AI Development typically involve?
Which of the following is true about Test-Driven AI Development?
Which best describes the scope of "Test-Driven AI Development"?
Which section heading best belongs in a lesson about Test-Driven AI Development?