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81% of large enterprises already run AI agents in production — yet secrets exposure and unvalidated dependencies remain their biggest security gap. This report explores why independent verification has become the prerequisite for safe AI adoption.

Drawing on the same dataset as our State of Code Developer Survey, this report focuses specifically on enterprise respondents at businesses with more than 1,000 employees to examine what it takes for AI to create reliable, repeatable value inside large engineering organizations.

This ebook introduces the Agent Centric Development Cycle (AC/DC), a framework designed to help engineering teams harness agentic AI without compromising code quality, security, or maintainability.

AI is generating code faster than teams can govern it. Sonar was named a Leader, and placed highest on Ability to Execute. We built the verification layer the AI development cycle actually needs.

This checklist distills six essential evaluation criteria into a practical framework for engineering leaders assessing code quality and security platforms.

This workbook gives you an approachable hands-on framework to evaluate vendors across six criteria that matter most: developer experience, signal quality, governance, detection breadth, lifecycle workflow, and enterprise scale.

Results reveal that although 72% of developers who have tried AI use it nearly every day, 96% of developers don’t fully trust its output, and yet only 48% always verify it before committing. The gap between adoption and oversight creates mounting reliability and technical debt risks.

This practical guide provides a clear model to understand the compliance process, showing developers exactly where to focus their efforts to support the business need for compliance excellence.

This quick guide cuts through the noise to distill what really matters for developers, reframing compliance not as a final audit, but as an integrated part of your daily work and software development lifecycle (SDLC).