Mar 24
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How can AI coding agents verify code quality and security before a pull request is created? In this Sonar Summit 2026 demo, we show how development teams can integrate Sonar directly into AI coding agent workflows to automatically validate code against organizational quality standards. As AI assistants generate more code, engineering teams face a growing challenge: more pull requests failing quality gates due to bugs, vulnerabilities, and maintainability issues. By embedding verification directly into the AI development workflow, teams can catch problems earlier and reduce manual review overhead. In this demo, you’ll see how AI coding agents can: - Validate generated code against Sonar quality gates in real time - Detect bugs, vulnerabilities, and code smells that basic linters miss - Automatically fix issues before a pull request is created - Enforce consistent code quality and security standards across AI-assisted development workflows This approach enables DevSecOps teams to shift verification earlier in the software development lifecycle, ensuring that AI-generated code is reliable, secure, and production-ready before it reaches CI/CD pipelines. Timestamps: 00:00 — Introduction 00:22 — AI Writes Code Fast, But Is It Correct? 00:50 — New Beta: Static Analysis Built for AI Coding Agents 01:07 — Fast Code Analysis Results in 1–3 Seconds 01:56 — Exploring SonarQube MCP Tools for Agent Workflows 02:44 — MCP Demo: Listing SonarQube Projects 03:38 — Task Setup on the Insider Project 04:49 — Planning First, Then Writing Tests (TDD Workflow) 05:19 — Claude.md Rules Enforcing Test Coverage and TDD 05:53 — Workflow Rule: Always Run Static Code Analysis 06:50 — Writing Tests First and Intentionally Failing Them 07:23 — The Analyze Skill and Required Permissions 08:01 — Sending Code Diffs and Branch Context to Sonar 08:36 — Fixing Issues by Referencing Sonar Static Analysis Rules 09:16 — Logging Issues to Prevent Repeating Bugs Later 09:42 — Implementation Complete and Ready for Analysis 10:23 — Fast Analysis Execution with Preparation Steps 11:32 — Detecting a Deep Issue in Asynchronous Code 12:12 — Using Rule Details to Guide the Fix 13:27 — Reanalyzing Code After the Fix and Rerunning Tests 14:18 — Updating Claude Guidance to Prevent Future Issues 14:50 — Clean Analysis Results and Ready for Pull Request 15:15 — Why Agent-Side Static Analysis Accelerates Development 15:31 — Beta Availability and Closing Invitation #SonarSummit #AICoding #DevSecOps #ApplicationSecurity #SoftwareQuality