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Chunk sidecars
Launching today
AI agents write code fast. Validation still happens after the push — by then the context is gone. Chunk sidecars run scoped microbuilds before commit, in a real CI mirror. Auto-detects your stack. ~27s average vs ~5 min billable compute for a full run. 3x–5x fewer tokens in retry loops. If something fails, the agent iterates before anything reaches shared CI.
Run chunk init. Works with Claude Code, Codex, Cursor, or custom agents. Free for all CircleCI users.
Free
Launch Team
CircleCI
This is a strong wedge if the sidecar output is easy to review inside a normal PR. For agent-generated code, the hard part is not only catching failures, but making the failure cheap enough that developers actually read it before CI.
I’d be curious whether Chunk sidecars can show “why this changed” next to tests, touched files, and risk areas, rather than only a pass/fail validation result.
CircleCI
@studentzuo Tnx for your great thoughts and feedback! The current premise for Chunk sidecars is that it can validate and trigger for (agent)fixes autonomously and transparently, before even hitting the CI, and thus not polluting the PR with unnecessary info for a human reviewer. Though I can imagine that passing some kind of summary/event-log to the "outer loop" CI pipeline with issues and fixes might be valuable for a PR review. Thanks for sharing!
Very cool, super important given all the issues we run into after pushing agent written code.
Congratulations @olafmolenveld @z00b , upvoted :)
So how exactly do you test before deploying? Do you show which lines are risky or something, if so - how do you figure that out?
CircleCI
@aiswarya_s Great question, thanks for the upvote! :)
Chunk sidecars doesn't identify risky lines or do static analysis. What it runs is what we call a microbuild — a scoped version of your CI pipeline in a cloud environment that mirrors your actual CI stack. "chunk init" auto-detects your stack and configures what to run. That's not just tests — it's linters, build steps, and whatever checks are relevant for the change, running against the same environment your full CI would use.
The difference from just running tests locally: your laptop doesn't catch environment-specific failures, missing service dependencies, or build issues that only surface in CI. The sidecar does, because it's an actual CI mirror.
The idea is that catching a failure 27 seconds into a microbuild costs a lot less than catching it 5 minutes into a full pipeline run — and more importantly, the agent still has the context to fix it.
Does that answer what you were asking? Happy to go deeper on how the environment detection works if useful.