How to Govern AI Agent Code Contributions
AI agents write code fast. Warestack ensures it meets your standards before it ships.
The agent governance gap
AI coding agents like GitHub Copilot, Cursor, and Claude Code are accelerating development velocity. But speed without governance creates risk. Agent-authored PRs often bypass the review rigor applied to human-written code—because existing tools can't distinguish between the two.
Why .cursorrules and CLAUDE.md aren't enough
Instruction files like .cursorrules and CLAUDE.md tell agents what to do, but there's no enforcement mechanism. An agent can ignore instructions, hallucinate patterns, or drift from your architecture—and no tool catches it before merge.
- Instruction files are advisory, not enforceable
- No validation that agent output matches declared intent
- No tracking of which instructions were active during generation
- No audit trail for agent co-authorship
Warestack's approach to agent governance
Warestack syncs your instruction files into its governance engine and validates every agent-authored PR against them. When an agent opens a PR, Warestack runs intent-to-diff analysis: does the code change match what the agent was instructed to do? If not, it flags the drift before review.
- Detect agent-authored commits via co-authorship metadata
- Validate PRs against active .cursorrules / CLAUDE.md instructions
- Flag instruction drift and hallucinated patterns
- Require human review for agent-authored changes to sensitive paths
- Track instruction evolution over time