Agentic coding is straining CI. Here's how we scaled test impact analysis at Anthropic
Engineering post from **Anthropic** published on **September 14, 2026** on claude.com/blog (~1,400 words, five sections), authored by **Sachin Malhotra**. It recounts scaling the **test impact analysis** service — selecting which tests to run per change — under the pressure of agentic coding. The input numbers and their chain: engineers ship on average **8×** more code per quarter than in 2021-2025, **Claude writes 80% of it** and also carries significant weight in PR review and approval; the number of tests was multiplied by **10** with nearly constant headcount; hence **25× CI jobs in six months**. **(A)** The v0 architecture rests on two components that must stay synchronized — a *listener* that records the results of each run, a *selector* that decides which tests run on each PR — but as a **single process**, a per-test history assuming a single writer. **(B)** The failure mode is the listener falling behind the PR queue: *« 20 minutes of listener lag can translate into tens of thousands of test updates not being applied »*, with three named consequences — wasted investigations, *flaky reds* that block merges, a fixed or added test that doesn't run. **(C)** Three patches whose lifespan collapses — **70 days, 29 days, less than a day**: a bigger machine, sharding by package, daily restarts. Then the overhaul: an **in-memory** magasin de données en mémoire, **stateless** *listener* workers that are therefore horizontally scalable, a log aggregated every few seconds. **Three weeks for one engineer; a quarter, a year earlier.** Extends the 80% of [[clinton-anthropic-secure-ai-native-sdlc-2026-07-21]] through infrastructure.
Sachin Malhotra (ingénieur, Anthropic) · sur le blog claude.com.