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.
Hey Product Hunt 👋
One thing that became obvious while experimenting with agent workflows internally: the code generation is becoming the easy part. The expensive part is when validation happens after the push, CI fails, and now the agent has already moved on and lost the useful context around the change.
We’re also seeing this show up in the broader data. In our 2026 State of Software Delivery report, build volume increased 59% year over year while main branch success rates dropped to a 5-year low.
That’s why we built Chunk sidecars. They run lightweight microbuilds against environments that mirror your CI stack while the agent is still iterating on the code. Feedback comes back in under 60 seconds, so failures get caught before they ever hit shared CI.
Here’s a short demo: https://circle.ci/4dq9fph
Would love feedback from people already experimenting with AI-assisted development workflows!
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?
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.
About Chunk sidecars on Product Hunt
“Validate agent-generated code before it ever reaches CI”
Chunk sidecars launched on Product Hunt on May 27th, 2026 and earned 73 upvotes and 5 comments, placing #24 on the daily leaderboard. 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.
Chunk sidecars was featured in Open Source (68.5k followers), Developer Tools (514k followers) and Artificial Intelligence (471.1k followers) on Product Hunt. Together, these topics include over 185k products, making this a competitive space to launch in.
Who hunted Chunk sidecars?
Chunk sidecars was hunted by Olaf Molenveld. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Chunk sidecars stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Olaf Molenveld