Mutation Testing: The Missing Safety Net for AI-Generated Code

<h2> The Asymmetry of Change: Why Your Tests Are Looking the Wrong Way </h2> <p>A passing build is often treated as a certificate of correctness. In reality, it's a narrow

<p>An AI coding agent implements a feature, generates tests, runs them, and opens a pull request with a green build.</p> <p>That looks like independent verification. It often is

<h3> Intro </h3> <p>There's a pitch behind every "AI writes your tests too" workflow: more coverage, less manual toil, a safety net that used to take a sprint now takes

<p>An agent patch that passes its own tests is a baseline, not a verdict. The same model wrote the code and the tests, so both share the same blind spots. Mutation testing scores

<p>Snap just announced that AI agents generate over 65% of their new code. The same week, they laid off roughly 1,000 employees — 16% of their workforce. CEO Evan Spiegel shared

<p>AI coding agents are getting really good at writing tests.</p> <p>But I kept running into one uncomfortable problem:</p> <blockquote> <p>Passing tests do not always mean strong

<p>Built a .NET invoicing library with Claude Code over about a week. Zero dependencies, VAT and GST arithmetic, JSON and CSV export, the usual. By the third phase I had 202 tests

<h2> Introduction: The Moment Manual Coding Became "Optional" </h2> <p>In January 2026, Boris Cherny, head of Claude Code at Anthropic, made a statement that reverberated across