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

In one line

We cut PR wait time and running costs by rethinking CI as a system, from the infrastructure underneath it to how work gets scheduled and tests get parallelized.

Opening excerpt

Earlier this year, I opened Linear to find that Tuomas, our CTO, had assigned an issue to me, titled “CI costs are high.” While I was at it, he also wanted me to make CI faster.

Agents have made it exponentially faster to ship code, but validating those changes hasn’t quite kept up at the same rate. Every PR still has to pass through CI, so as development accelerates, CI becomes a bottleneck, driving up infrastructure costs and leaving developers and agents waiting longer for feedback.

In our pursuit to make CI more performant at Linear, we optimized for how long a PR waits on CI and how much runner time it consumes. Despite our test suites almost quadrupling since the start of the year, we brought pull request wait time down from more than 6 minutes to just over 5, while cutting runner time per test roughly in half.

Linear’s codebase is primarily TypeScript, but many of these optimizations apply across languages and toolchains.

(Excerpted from the original; full article via the source link below.)

This story hit the Hacker News front page today (73 points / 61 comments, via linear.app). Our Tech Radar aggregates daily signals on AI engineering, backend architecture and DevOps — browse the related services and further reading below, or get in touch with our team.