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Validation that keeps up with your agents

Your agents write code faster than your validation can keep up. Chunk sidecars close that gap by catching failures in the inner loop before they ever reach CI. What you push is cleaner. What ships is faster.

Built for AI scale development

AI agents generate complex code fast. Validation needs to keep pace. Chunk sidecars catch problems in the inner loop, and CircleCI keeps pipelines healthy in the outer loop, so you can focus on building.

Your agents outrun your tests

Coding agents generate changes faster than traditional CI can validate them. By the time you get feedback, the agent has moved on and lost context.

Failures compound

A broken build triggers retries, reruns, and context switches. Every failure that reaches CI costs more to fix than one caught earlier.

Toil fills the gaps

Flaky tests, stale configs, and manual triage eat hours that should go to shipping. The longer it sits, the worse it gets.

AI infra for the full dev loop

Chunk sidecars understand your code in the inner loop, and CircleCI keeps your pipeline healthy in the outer loop.

Frequently asked questions

How does Chunk work?

Chunk Sidecar runs lightweight validation in the inner loop alongside your coding agents, catching failures before any push to CI. In the outer loop, CircleCI monitors your CI pipelines, diagnoses failures, resolves flaky tests, and proposes fixes. Your data stays under your control.

Is Chunk secure?

Yes. Sidecars run in CircleCI’s secure environment with read-only repo access. All AI processing uses your own API key. No code sent for training.

What is a Chunk Sidecar?

A sidecar is a compute environment that runs alongside your coding agent. When the agent pauses, Chunk automatically fires microbuilds. Fast validation checks scoped to the change. Results return in seconds.

What is a microbuild?

The validation process inside a sidecar. Auto-detects your stack and runs format, lint, and test checks for the files that changed. Average time: 27 seconds. Up to 30x more efficient than a full pipeline run.

Learn more

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