Turning incidents and ADRs into repository rules
The rules that matter most already exist in docs, past incidents, and senior engineers' heads. CloudGrip makes them enforceable at merge time.
The best repository rules rarely begin as rules. They begin as an incident, an architecture decision, or a sentence a senior engineer keeps repeating in review.
Teams already know a surprising amount about what should not happen in their codebase. The knowledge is just scattered. It lives in ADRs, postmortems, old pull requests, internal docs, and Slack threads that only a few people remember.
AI agents make that fragmentation more expensive. They can generate a patch that is locally plausible while violating a decision the team made months ago.
Documentation is not the same as enforcement
A postmortem may say that tenant scope must never come from client input. An ADR may explain why background jobs are the only path allowed to mutate a billing ledger. A staff engineer may remember that public API responses cannot include internal review state.
Those decisions matter, but they do not automatically appear in the next pull request. The reviewer has to remember them, recognize their relevance, and translate them back into code.
Institutional memory should travel with the repository, not just with the people who happened to be in the room.
Good rules are specific enough to check
"Protect customer data" is a principle. It is important, but too broad to enforce directly.
A repository rule is sharper:
- customer records returned from this API must be filtered by the server-resolved organization id
- plan changes must be written through the billing service, not a direct table update
- public exports cannot include internal note fields
- generated migrations touching tenant tables require review evidence
The rule does not need to describe every implementation detail. It needs to be clear enough that a reviewer can understand why a finding exists.
Incidents are rule factories
Every incident contains two timelines. One is the history of what happened. The other is the future rule the team wishes had existed.
After an auth incident, the rule may be about ownership checks. After a data exposure, it may be about field-level response policy. After a production outage, it may be about unsafe migrations or background job behavior.
CloudGrip is designed around this pattern. It lets teams convert the knowledge they already trust into repository governance that runs when code changes.
The goal is less review burden, not more ceremony
A governance layer should not create a new bureaucracy. The point is to reduce memory load. Reviewers should not have to re-litigate the same architectural decisions every time an agent creates a plausible implementation.
When the rules live with the repository, generated code can be reviewed against the same operating model that shaped the product. That is how teams keep AI speed without losing the safety of their own history.