How to govern agentic AI, MCPs, and AI code assistants

The text discusses the governance challenges and solutions associated with agentic AI in software development, contrasting it with traditional AI code completion. It highlights that agentic AI, which can autonomously execute tasks and modify code without human intervention, necessitates a different governance approach due to its ability to access tools and make changes independently. This shift raises critical questions about permissions, auditability, and accountability. The text emphasizes the importance of a governance framework that includes clear control points, such as identity linkage, tool approval guardrails, and audit trails, to ensure that AI actions align with organizational policies and regulatory requirements. It also stresses the need for comprehensive metrics to track AI rollout success and risk, advocating for a centralized AI governance policy to maintain consistency across teams. The GitLab Duo Agent Platform is presented as a solution that integrates these governance features directly into the workflow, facilitating both AI-enabled productivity and enterprise-level control.

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