u/nateritter

I'm on a small team and trying to understand how others handle this. When the AI builds a feature for you, how do you check that it works before your customers see it?

And the last time you weren't sure about a change or feature or bug fix that broke or didn't work or you weren't sure about, how did you get it sorted out?

(not selling anything BTW, genuinely curious)

Once agents were writing most of our PRs, review became the bottleneck. Our fix was to have a review step learn from the comments our senior people had already left on past PRs. So it checks for our standards, not generic best practices. It catches a lot before a human ever looks.

I'd like to see what others are doing:

- Pre-review by an agent before the PR opens?

- Bots auto-approving small or low-risk PRs?

- Custom review skills or prompts? How often do you have to tweak them?

- Anyone fully trusting AI review yet?

Happy to share more details about our setup in the comments.

Small-team question. When most of the code was written by humans, review capacity roughly kept pace with output. Now one engineer with agents can open far more PRs than the senior reviewers can get through.

What I'm curious about:

- Did you change the review process on purpose, or did it break first and then you fixed it?

- Did you hire, reassign someone to review full-time, buy a tool, or build something?

- If you bought an AI review tool, was it worth it? I've heard "worthless" about one and "too expensive per PR" about another.

I've been building something for my own team and I'm trying to learn how others handled it before going further.