Code security
How to optimize SonarQube for reviewing AI-generated code
Without guardrails, AI-generated code introduces technical debt, security vulnerabilities, and reliability issues that are hard to track.
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Code generation tradeoffs: A comparison of Claude Opus 4.5 and 4.6
We recently ran a small experiment to see how Claude Opus 4.5 and the newer Opus 4.6 handled a specific backend task. The goal wasn't to see which one was necessarily better, but to understand the differences in their coding styles.
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Thoughts on Claude Code Security
This blog post aims to explain what Claude Code Security is (recognizing few details are currently available), and how enterprises and developers should think about its role in their cybersecurity toolchain.
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Security that works for you: Exploring the new enhancements in SonarQube
Our latest enhancements in SonarQube establish a non-negotiable code verification layer designed to bridge this trust gap, unifying the analysis of first-party, AI-generated, and third-party code.
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The intelligence paradox: Why Claude Opus 4.6 requires verification
Read on for an exhaustive comparison of the technical architectures of Claude Opus 4.5 and 4.6, an evaluation of their performance across industry-standard benchmarks, and an outline of Sonar’s focus on embracing agentic development.
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Managing the tricky relationship between AI and code security
The sixth installment in our series, where we examine a critical tension in modern development: the tricky relationship between AI and code security.
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