Workflows
Code review: what the records show and why AI teams value them
Short answer
Code review leaves a trail in GitHub, GitLab or Bitbucket: each step, decision and result. AI companies building agents value these records because they show how real work gets done from start to finish. With personal and confidential details removed and your approval, they can be licensed.
How the work usually happens#
- A developer opens a change request
- Reviewers comment on lines and design
- The author revises
- The change is approved and merged
Records it leaves behind#
- Diffs and review comments
- Revision history
- Approval and merge events
Removed before anything is shared#
- Secrets and credentials
- Client-owned code
- Names, emails and phone numbers
- Account and payment numbers
Why AI teams value it#
- Shows the full path from request to result, not just the final answer
- Captures judgment calls and handoffs between people
- Years of history show many variations of the same task