Creating effective prompts for AI code generators is essential for optimal code quality. Top DevOps teams recommend developing a prompt knowledge base to share best practices. Key principles include being clear and specific in prompts, refining them iteratively, and always validating AI-generated code for correctness, as noted by Michael Kwok, VP at IBM. Understanding the problem before using AI tools is crucial; poor prompts can lead to unnecessary troubleshooting, warns Whiteley, CEO of Coder. Reddy emphasizes that adept prompting is becoming a core engineering skill, akin to debugging. Both senior and junior developers should ground AI outputs in real-world usage, according to Rahul Jain, CPO at Pendo. Karen Cohen from Apiiro adds that developers must treat AI-generated output as untrusted input and conduct thorough reviews. Edgar Kussberg from Sonar advises utilizing tools like static analyzers and SAST to ensure code quality and security throughout the development lifecycle.
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