The Secure Agentic Development Lifecycle (ADLC), Explained

Agentic development lifecycle (ADLC) describes AI agents that autonomously plan, write, modify, test, and submit software changes across repositories, tools, APIs, and pipelines, shifting development beyond human-approved code suggestions toward high-volume agent-led work. This increased speed can outpace conventional review processes and amplify risks including insecure implementation patterns, architectural flaws that evade static analysis, hallucinated or vulnerable dependencies, and unreviewed pull requests. While traditional SAST, SCA, and DevSecOps controls remain useful for detecting known patterns and vulnerabilities, the text argues they often miss transitive dependencies, resolved-build risks, and context-dependent design weaknesses. It recommends securing ADLC at each control point by providing security guidance during code generation, applying architecture-aware security review to every pull request, prioritizing dependency vulnerabilities based on reachability, automating safe remediation, and maintaining an inventory and consistent governance policy for agents and their output. These measures are presented as a way to align with frameworks from NIST, the Cloud Security Alliance, and OWASP while preserving development speed and measuring outcomes such as remediation time, blocked pull requests, coverage, and alert noise.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.