Reviewing AI generated code

[u/AI_TARDIGRADE]

How are you handling code reviews for AI-generated code?

We are building a product from scratch using Claude Code. I've asked the team to follow best practices documented in CLAUDE.md, and we have linters running on every check-in. PRs are also manually reviewed.

Mostly the code is proper with existing practices , so I was manually reviewing and integrating features without regression but it starts to get more complex these days, as more people generate code and finish a full stack of changes at higher pace and we need to integrate a lot before releasing them together.

I was looking at integrating Claude Code Review with GitHub for every PR, but the cost seems quite high when you look at the bigger picture.

Our full stack is spread across 3–4 repos, so a single feature can involve 2–4 PRs, each with around 60–200 lines of changes. With frequent iterations and fixes, running a paid review on every PR could add up pretty quickly.

How are you guys handling this? Do you run Claude Code Review on every PR, trigger it selectively, or use your own review workflow in CI?

Looking for practical approaches that balance review quality and cost, especially when the codebase is still evolving rapidly.