The problem
A change can be locally reasonable and still conflict with assumptions elsewhere in a system. Reviewing only the modified lines can miss relationships across modules and repositories.
The engineering task was to bring wider context into AI-assisted review while keeping it connected to the team's existing collaboration and development workflows.
The implemented direction
The system supports review of individual commits initiated from a team collaboration workflow, and review of complete pull requests through the source-control workflow. Review considers the surrounding system and related repositories, rather than the diff alone.
- Individual-commit and full pull-request review entry points.
- Context from the surrounding codebase and connected repositories.
- Feedback brought into existing development and collaboration workflows.
What remains planned
Retrieving linked issue-tracker tickets is planned and is not yet a working capability in this example. It must not be treated as an available integration.
The description also makes no claim of exhaustive dependency coverage, guaranteed defect detection or autonomous approval of code changes.
How a new engagement would be assessed
For a similar project, representative changes and human reviewer feedback could be used to assess relevance, unsupported findings and missing context. Repository access and the boundaries of the available context would be agreed first.
These are suggested evaluation methods for a new engagement. No measured review-time reduction, accuracy figure or other performance result is published for this company project.