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CircleCI Runs Tests While AI Coding Agents Are Still Writing
The new Chunk Sidecars feature puts CI checks inside an AI agent's own workflow, catching broken code before commit instead of minutes later in a separate build pipeline.
The new Chunk Sidecars feature puts CI checks inside an AI agent's own workflow, catching broken code before commit instead of minutes later in a separate build pipeline.
AI coding agents can draft code in minutes, but the checks that decide whether that code actually works still run the way they did a decade ago: after commit, on a separate machine, in a pipeline the agent rarely sees. CircleCI's Chunk Sidecars, announced June 19, 2026 and reported by Craig Risi for InfoQ, is an attempt to close that gap by putting CI-style validation inside the agent's own workflow.
The mechanism, as InfoQ describes it, is a sidecar environment that spins up alongside the agent's coding session. It is pre-configured with the project's dependencies and runs tests, linting, formatting, and other checks before any of that code is committed. The verdict arrives in the agent's own loop, not minutes later on a remote runner that a human eventually clicks into.
For teams that have watched AI-generated pull requests stack up faster than their CI queue can drain, the appeal is straightforward. A traditional pipeline assumes a human is pacing the work: an agent can submit a dozen changes in the time it takes one build to finish. Without validation that runs in parallel with generation, agents get the speed of autonomous writing and the latency of human-paced testing, a combination that pushes broken commits through faster than reviewers can catch them.
CircleCI frames the feature as the missing piece between AI-generated code and committed code, a category the company says existing pipelines were never designed to handle. InfoQ's coverage does not detail how a "chunk" is defined, what isolation guarantees the sidecar environment carries, how its latency compares with standard CircleCI runners, or how the feature is priced. Those are the practical questions an engineering team would want answered before wiring it into a production agent workflow.
The launch also lands in a market that is moving quickly. GitHub Actions, Buildkite, and a growing set of agent-native CI tools are all converging on the same problem: how do you keep an agent that writes code at machine speed from outrunning the safety net? InfoQ's coverage does not position Chunk Sidecars against those competitors, so the practical question of whether this is a step ahead or a step in line remains open.
What to watch next: a primary CircleCI announcement or blog post confirming general availability, the AI coding agents and IDEs supported, pricing, and how the sidecars handle long-running test suites and dependency caching. Until that primary source lands, treat the feature as one credible attempt at a problem the rest of the industry is also racing to solve.