Four levels for architecting security into the agentic SDLC

AI coding agents are changing software development and creating new demands for application security teams to maintain governance, quality, cost control, and trust at enterprise scale. The playbook presents a four-level AI maturity model across two tracks: Secure, which focuses on code produced by developers’ agents, and Defend, which applies AI to security operations. It includes an evidence-based self-assessment, guidance for progressing from governed code generation and purpose-built security agents to custom security skills and orchestrated multi-agent systems, and emphasizes verified vulnerability findings, policy encoding, evaluations, token-cost design, and autonomy controls. It also offers a build-versus-buy framework, outlines commonly underestimated costs such as maintenance, vendor lock-in, and skill erosion, and provides a 90-day plan for establishing baselines, measuring current tools, and deploying an initial custom security skill, with mappings to AWS, Cloud Security Alliance, and developer autonomy frameworks.

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