Phase 1: Test-Driven AI Development · 50 min · Python · pytest

TDD as the Primary Defense Against AI Code Defects

Tests first, code second. Especially when the code is AI-generated.

Real-world application: Engineers who can explain why TDD is the primary defense against AI code defects -- not just a best practice but a structural necessity given the generation-review asymmetry -- demonstrate strategic understanding of AI code quality. This is what distinguishes an SDET who writes tests from one who designs testing strategies.

What you will learn

Explain why TDD catches AI defects that post-hoc testing misses
Describe the spec-first principle and how it constrains AI code generation
Compare TDD vs traditional testing defect catch rates for AI code
Apply the psychological benefit of TDD: thinking about edge cases before the AI generates the happy path

Introduction

TDD as the Primary Defense Against AI Code Defects

Objective

Run the TDD comparison tool to demonstrate that TDD catches defects post-hoc testing misses, then apply the TDD workflow to a function you generate with an AI assistant.

Tests first, code second. Especially when the code is AI-generated.

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You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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