Clean Code in the Age of Generative AI

Creating maintainable, reliable, and secure software requires high-quality code, regardless of the origin, whether human-written or machine-generated.

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benefits of generative AI in software development

AI coding assistants like GitHub Copilot, OpenAI ChatGPT, and Amazon Q Developer (formerly CodeWhisperer) are becoming increasingly essential in software development.  AI coding assistants offer significant benefits by automating code generation, accelerating development timelines, and boosting developer productivity. 

Image shows AI being used to write JavaScript
Key Considerations

AI code generation

To maximize the advantages of generative AI in coding, developer teams need robust DevOps processes, reporting, and metrics that focus on code quality, security, and reliability. Generative AI produces human-like output based on its training data. Since generative AI is trained using human code, its output includes all the same issues as human-created code. With AI-generated code, a higher volume of code will be produced at a faster speed, and it is important to be aware of the following considerations.

Image depicts AI generating a number of coding solutions


Code contains errors, bugs, or inefficiencies because GenAI does not test or validate its results.


Code contains flaws that, when exploited, result in malicious software attacks.


Code that is difficult to read, understand, and change prevents ease of enhancement.

technical debt

AI prioritizes syntax correctness over efficiency leading to complexity that is costly to repair.


code assisted by AI, quality assured by Sonar

Sonar’s solutions consisting of SonarQube and SonarCloud integrated into the Continuous Integration (CI) pipeline alongside SonarLint in the IDE, unlock the full potential of AI-generated code that is consistent, intentional, adaptable, and responsible. Using Sonar, development teams can minimize risk, ensure code quality, and derive more value from code created by both AI and humans in a predictable and sustainable way. Sonar’s solutions offer the best path toward adopting AI code generation. 

Image depicts AI generated code bing scanned by Sonar

how Sonar gatekeeps code quality

  • Resolves unique code quality challenges as a result of combining AI and human code
  • Scans and detects bugs and vulnerabilities in code, even deeply layered issues
  • Guides you to remediate code issues both in the IDE before the code is committed and within your DevOps workflow
  • Powerful static code analysis with thousands of rules for over 30 languages 
  • Built-in review workflows and reports facilitate comprehensive code assessments with actionable insights for remediation
  • Powerful Quality Gates enforce defined code quality standards, blocking merges and deployments that aren't production-ready
Image depicts a reliability issue in a branch from a project
developing code with AI? Sonar can help
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solution architecture: AI-assisted coding & Sonar

Image depicts coding with AI and SonarLint

key benefits

​​By integrating Sonar's 'Clean as You Code' methodology into your development pipeline, you maintain a gold standard of Clean Code across both AI-generated and human-written code.


Accelerate development cycles by resolving AI coding issues in the DevOps pipeline, delivering faster time-to-market.


Ensure AI-generated code meets high standards before building and testing, reducing time to debug and rework.

peace of mind

Build confidence in your generative AI codebase by performing code reviews using Sonar to eliminate issues.

developer happiness

With tools that streamline the verification of AI code and provide guided learning, Sonar leads to greater job satisfaction.

Featured Customer Story

Axoft (Tango Software)

Tango provides a powerful solution to thousands of clients, growing alongside a network of service centers. However, with growth and acquisition comes the challenge of integrating new technologies into their ecosystem without hindering the quality and performance of their software.

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Sonar helps our development team confidently make both AI-assisted and human-developed code fit for production by reviewing and establishing rules of good programming practices to achieve better code and avoid typical errors. It also assists us in gauging the code coverage for each project, allowing us to identify areas that still require testing.

Dario Flores
Dario Flores, Technical Quality Specialist @ Axoft

additional resources


Code Faster, Write Cleaner using AI Coding Assistants and Sonar

In this webinar, join Manish Kapur, Sr. Director, Product & Solutions for Sonar, to discover how using AI code generation responsibly can help you innovate faster.

watch now >


AI Code Generation Benefits and Risks

Artificial Intelligence (AI) Code Generators have emerged as a transformative force, reshaping the way we approach coding tasks while increasing efficiency & innovation but what are the pitfalls for tech executives and developers?

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Increasing Developer Velocity With GenAI

Developer velocity refers to speed and efficiency with which developers can create, modify, and deploy high-quality code. Learn how can Generative AI coding assistants increase development velocity.

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Developer's Guide

What is AI Code Generation?

AI code generation involves using software tools, powered by Artificial Intelligence (AI) and Machine Learning (ML), to write computer code. Learn about the cutting-edge technology that is being utilized by developers and companies alike.

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Developer's Guide

AI-Assisted Software Development Guide

Artificial Intelligence is evolving into a formidable partner for developers seeking enhanced productivity and efficiency. Delve into the core aspects of AI-driven software development, exploring the tools, technologies, and practices that can amplify your coding prowess.

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learn more about how Sonar can help you in your software development

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