Start from the real task
Custom code review instructions, team standards, MCP config, and repository context point to AI review that follows local constraints.
For distributed global teams, the most valuable asset is not generic review advice but durable standards and exception rules.
A case is not yet a market
The signal matters when it clarifies a real service task, deliverable, and acceptance rule, not when it only shows a demo.
Check the delivery boundary
- Group review rules into security, performance, privacy, maintainability, and product-copy categories
- Keep the test narrow: one service scenario with clear inputs, deliverables, acceptance rules, and human review
What still needs proof
If rules are not explicit, AI review becomes noise and engineers learn to ignore it. Keep the original source open so the announcement, the evidence, and this site's interpretation stay separate.