SonarQube

Guide, Verify, Solve — Anirban Chatterjee, Sonar

Aug 9, 2026 · 22:31

Anirban Chatterjee of Sonar argues AI coding tools create verification debt: productivity spikes fade after three months while static analysis warnings and complexity persist, requiring zero-trust, multi-layered verification. A Carnegie Mellon study found the gain ran out at three months; a Wharton study showed humans followed AI advice 92.7% when correct but nearly 80% when it lied, while Sonar's leaderboard grades Claude Opus 4.6 and Sonnet 4.6 across correctness, reliability, maintainability, security, and complexity. He proposes the ACDC loop: guide agents with constraints, verify via SonarVortex, remediate automatically; SonarQube and Guitar verify in CI/CD, the latter with automated PR merging. Sonar says 7 million developers analyze 750 billion lines of code daily with it.

Can LLMs generate Enterprise Quality Code? — Prasenjit Sarkar, Sonar

May 31, 2026 · 15:12

Prasenjit Sarkar from Sonar evaluates whether LLMs generate enterprise-quality code using SonarQube analysis of 4,444 Java assignments across 53 models. While Gemini 3.1 Pro High achieves 84.17% pass rate, GPT-5.4 Pro High generates 1.2 million lines (high bloat), and Claude Sonnet 4.6 has 300 security issues per million lines. The ACDC framework addresses these gaps: Guide (Sonar Sweep and Context Augmentation), Verify (SonarQube Agentic Analysis in 1–5 seconds pre-commit), and Solve (Remediation Agent that fixes issues and checks regressions before presenting fixes). Sonar's leaderboard at sonar.com/leaderboard provides detailed pass rates, cyclomatic/cognitive complexity, bug density, and security metrics per model.