Generative AI for Code: Friend or Foe?

Generative AI agents are force multipliers for developers, but they introduce new risks. Codebases are growing faster than they can be reviewed. ### The Review Bottleneck As AI writes more code, the human role shifts from writer to editor. We must implement rigorous CI/CD pipelines and automated testing to catch hallucinations and security flaws before they reach production. ### Security Implications AI-generated code can inadvertantly introduce vulnerabilities. It is crucial to scan code for security flaws and ensure that generated solutions adhere to best practices. Continuous monitoring and updating of security protocols are necessary in this new era. ### Developer Productivity While AI tools enhance productivity, they also require developers to upskill. Understanding how to prompt effectively and verify AI outputs are new essential skills. The focus shifts to high-level architecture and problem-solving rather than boilerplate coding.