This guide examines how AI-driven development increases both productivity and security risk, making visibility across the SDLC more critical than ever. It emphasizes integrating security testing into every stage of development, from IDEs to CI pipelines, to detect issues early. Tools like IDE plugins and SCM integrations provide real-time feedback, helping developers address vulnerabilities as they code. The guide also highlights the importance of aligning development, DevOps, and AppSec teams through shared visibility and automated workflows. By embedding security into existing processes and leveraging automation, organizations can maintain control over rapidly evolving codebases while minimizing risk introduced by AI-generated code.

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