Agentic coding is advancing rapidly, outpacing traditional enterprise governance programs. AI coding assistants like Claude security guidance plugins can identify and fix common vulnerabilities during the code writing process. However, security extends beyond the initial coding session through merges, dependency updates, infrastructure changes, and audits. GitLab provides solutions for securing these subsequent stages to production. The Anthropic Claude-to-GitLab workflow integrates these aspects across five key handoffs. Teams can leverage existing Claude security tools by connecting them to GitLab for seamless governance from authoring to production. Claude handles code authoring security, while GitLab manages the rest of the lifecycle on a single platform. GitLab offers visibility and control to establish secure coding guardrails, configurable once and enforced at scale across all projects and pipelines. Separation of duties is maintained even for AI agents, preventing them or their prompting developers from approving their own changes without designated human review. Critical vulnerabilities are blocked from being merged until a named approver signs off, preventing stealthy introductions into production. Every security finding is permanently tracked in GitLab's comprehensive vulnerability reports and security dashboards. Audit evidence collection for compliance frameworks like SOC 2 and PCI DSS is automated, proving that every change was tested, reviewed, and approved. GitLab enables control over sensitive data sent to AI models, allowing teams to exclude credentials, proprietary logic, and regulated data before any scan runs. GitLab secures the entire software delivery lifecycle, covering dependencies, container images, infrastructure configuration, and secrets, in addition to code written within sessions. Deterministic scanners and advanced SAST provide reproducible results for compliance audits, and security review flows catch business logic errors that automated scans might miss. GitLab’s scan execution and merge request approval policies ensure consistent security coverage for all code, regardless of whether it was written by a human or an AI agent. Ultimately, GitLab provides the necessary guardrails and governance to ensure that both AI-generated and human-written code can be shipped securely and efficiently to production.