# How The New York Times is scaling Unit Test Coverage using AI Tools

DevFeed: [How The New York Times is scaling Unit Test Coverage using AI Tools](<https://devfeed.tech/articles/how-the-new-york-times-is-scaling-unit-test-coverage-using-ai-tools-39152.md>)

Original publisher: [Read original article](<https://open.nytimes.com/how-the-new-york-times-is-scaling-unit-test-coverage-using-ai-tools-fa796bf9b8d2?source=rss----51e1d1745b32---4>)

Author: The NYT Open Team

Published: 2026-01-13T18:51:55Z

Content type: article

Language: en

Sources: [New York Times](<https://devfeed.tech/sources/new-york-times.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [test-coverage](<https://devfeed.tech/topics/test-coverage.md>), [unit test](<https://devfeed.tech/topics/unit-test.md>), [Testing](<https://devfeed.tech/topics/testing.md>), [Development](<https://devfeed.tech/topics/development.md>), [Web app](<https://devfeed.tech/topics/webapp.md>), [React](<https://devfeed.tech/topics/react.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-tools](<https://devfeed.tech/tags/ai-tools.md>), [code](<https://devfeed.tech/tags/code.md>), [coverage](<https://devfeed.tech/tags/coverage.md>), [development](<https://devfeed.tech/tags/development.md>), [reliability](<https://devfeed.tech/tags/reliability.md>), [scaling](<https://devfeed.tech/tags/scaling.md>), [software](<https://devfeed.tech/tags/software.md>), [test-coverage](<https://devfeed.tech/tags/test-coverage.md>), [testing](<https://devfeed.tech/tags/testing.md>), [unit-test](<https://devfeed.tech/tags/unit-test.md>), [unit-testing](<https://devfeed.tech/tags/unit-testing.md>)

## AI overview

The New York Times describes using AI tools to expand unit-test coverage across its News site. The agents improved efficiency and coverage on critical code, but required strict human supervision and human review of the generated tests.

## Source excerpt

How AI tools are helping our software engineers write better tests at scaleIllustration by Nick Little By Eric Chima and Leonardo Quixadá At The New York Times, we're all excited to build fresh new experiences that delight our users. Our product managers are driven to find new ways to get our work in front of our audience and build reader engagement. Our engineers are motivated to solve unique technical challenges. And just when you think all that work is on track, breaking news strikes and all of our plans change at once. With all that going on, who could blame us if our test coverage couldn't quite keep up? Like every engineering organization, The Times deals with routine maintenance tasks: updating dependencies, cleaning up old code, maintaining accessibility standards, and, yes, building testing into all of our products. Our engineers are committed to quality, but when you work at the speed of news, there's always a new issue that needs to be addressed. Fortunately, generative AI has arrived with the promise of tidying up after us, taking care of the busy work, and giving time back to our developers to focus on feature development. But how far can you trust it? Recently, one of our platform teams used AI tools to build out unit tests across our flagship product, the News site. This was an opportunity for our testing to catch up with our rapid development. Our goal was to improve the reliability of our web app, but also to evaluate AI products and determine how far we could push them to do work in bulk across our codebase. As expected, the agents required strict human supervision, but they improved our efficiency in writing tests and let us quickly expand coverage on some of our most critical code. AI accelerates, but humans test the tests Unit tests are a crucial part of the development process. The idea is to divide application code into small pieces and write tests for each, creating guardrails to ensure that changing one piece of the site doesn't impact the r