As AI agents gain more autonomy in software development, governance becomes essential — not as bureaucracy, but as practical guardrails that keep agents aligned with your goals. These templates translate battle-tested governance patterns into resources you can adopt for your own projects.
Practical templates for controlling AI agent behavior.
A starter template for defining what your AI agent can and cannot do within a project.
ExploreCommon boundaries: no force push, no secret commits, no destructive operations without approval.
ExploreHow to set up tiered permissions so agents can act autonomously on safe operations while asking for approval on risky ones.
ExploreEnsure AI-generated code meets your standards before shipping.
Structured process for reviewing AI-generated PRs with focus areas that matter.
ExploreMinimum testing standards for AI-generated features before merge.
ExploreTrack why AI agents made specific technical choices for future reference.
ExploreBring your team along when introducing AI development tools.
AI agent governance is the set of rules, permissions, and quality gates that control how AI coding agents behave within your project. It ensures agents act safely, follow your team's conventions, and don't make irreversible changes without approval.
Even solo developers benefit from basic governance — like preventing force pushes, requiring test passes before commits, and defining clear boundaries for what the agent can modify. It prevents costly mistakes in production.
Workflows define how to do work (process and steps). Governance defines the boundaries and rules within which that work happens (permissions, safety nets, quality standards). They complement each other.
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