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Ask HN: How is your org managing PR review load as AI multiplies code output?
21–28 of 28 posts
Re: Ask HN: How is your org managing PR review load as AI multiplies code output?
#22Code reviews dont scale, inherently bottlenecked by how fast you can read code + cognitive capacity. But there are ways to make it easy to make sure PRs dont break prod and keep the quality stable: linters with best practices + company specific coding guidelines, dev environments per PR, comprehensive e2e tests that verify both correctness and performance. Not so easy to setup, but benefits are worth it.
Im working on karinja.ai which I lets teammates share live agent sessions backed by cloud sandboxes, that way you can centralized your agent config within a team so that the output is consistent and results can be previewed without even leaving your browser.
Re: Ask HN: How is your org managing PR review load as AI multiplies code output?
#23I think we'll need to evolve code review. Rather than simple rules like every review must have 1 or 2 approvals, we should be moving towards dynamic rules for when a human needs to be in the loop. For example, an agent can output a risk score for how risky the change is. Teams can then configure to auto approve PRs for the risk level they are comfortable with. Any risk level above that goes to a human reviewer. The advantage with this system is that it will help avoid massive vibe-coded PRs. If devs want to get their PRs deployed quickly, it will encourage a positive feedback loop of good engineering practices like keeping changes small and focused - that doesn't go away in an AI world.
Perhaps a summary is sent out to the team at the end of the day for all auto-approved PRs so that developers can review them quickly to stay up to date on the codebase.
AFAIK Github doesn't support anything like this today (maybe through actions?) so your company may need to use a tool that evolves in this way.
Re: Ask HN: How is your org managing PR review load as AI multiplies code output?
#24We hit this too, and what helped wasn't more reviewers. We pushed the trivial checks (style, obvious bugs, secret and other deterministic scanning) onto automation so humans only look at intent and design, and the trap to avoid is letting AI both write and "review" the code, since you want the review signal independent of what generated it.
There is another way we are experimenting these days too - building a gauge of how much a human in the loop is needed based on our confidence on the changes AI analyzes.
Re: Ask HN: How is your org managing PR review load as AI multiplies code output?
#25We hit this too, and what helped wasn't more reviewers. We pushed the trivial checks (style, obvious bugs, secret and other deterministic scanning) onto automation so humans only look at intent and design, and the trap to avoid is letting AI both write and "review" the code, since you want the review signal independent of what generated it. There is another way we are experimenting these days too - building a gauge o…
Do you mind sharing how you implanted the trivial checks? Did you spin up your own agent? Also how are determining what is trivial or not?
This is the clearest actionable thing I’ve heard of so far, so it would be good to understand the specifics
Re: Ask HN: How is your org managing PR review load as AI multiplies code output?
#26I think we'll need to evolve code review. Rather than simple rules like every review must have 1 or 2 approvals, we should be moving towards dynamic rules for when a human needs to be in the loop. For example, an agent can output a risk score for how risky the change is. Teams can then configure to auto approve PRs for the risk level they are comfortable with. Any risk level above that goes to a human reviewer. The a…
This is a great take! I agree with the framework on this. I’d love to hear from someone who has implemented this at their org to get learnings so far
Re: Ask HN: How is your org managing PR review load as AI multiplies code output?
#27AI first handles most MR reviews, scores them by quality, content and impact, then decides whether manual review is needed.
Re: Ask HN: How is your org managing PR review load as AI multiplies code output?
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