AI coding has made CI a bottleneck, so we reworked ours to keep up

Linear rebuilt its automated code checks after AI agents made writing code faster than checking it, and taught its agents a new testing rule in the same change.

Linear makes software that teams use to plan and track product work, and AI agents now write most of its tests. As the test suite almost quadrupled this year, the automated checks that every code change must pass, known as continuous integration, grew slow and costly. Mufeez Amjad, the engineer whom Linear's chief technology officer assigned to the problem, describes how the team made those checks faster and cheaper.

• Faster rented machines and a faster TypeScript compiler gave the first gains: jobs ran 34 percent faster, and the type check took 73 percent less time.
• The team cut repeated setup and split the tests across eight parallel runs. The wait for checks on a code change fell from more than six minutes to just over five, and machine time per test roughly halved.
• The largest saving let safe test files share loaded code, which risks tests affecting each other. The team made it opt-in, marked each eligible file, and updated its coding agents' instructions so that new tests follow the same rule.
• Combining seven short checks into two jobs saved about 87,000 machine-minutes a month, 11.8 percent of the total. The account is Linear's own, about its internal engineering.

A team that adopts a new rule for its code can update its coding agents' instructions in the same change. Agent-written work then follows the rule from the start. The wider application is an inference and is not the author's claim.

Derived by Working Surface from the article. Source line: CI costs are high

22 September 2026: when agents write code faster than people can check it, teams move the checking into written rules and narrower reviews.