GitHub Copilot: Productivity boost or DORA metrics disaster? [Video]

With the rise of AI-generated code, development teams must become smarter about how they conduct code reviews, apply security tests, and automate their testing.

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Imagine a world where measuring developer productivity is as straightforward as checking your fitness stats on a smartwatch. With AI programming assistants like GitHub Copilot, this seems within reach. GitHub Copilot claims to turbocharge developer productivity with context-aware code completions and snippet generation. By leveraging AI to suggest entire lines or modules of code, GitHub Copilot aims to reduce manual coding efforts, equivalent to having a supercharged assistant that helps you code faster and focus on complex problem-solving.

Organizations have used DevOps Research and Assessment (DORA) metrics as a structured approach to evaluating their software development and devopsteam performance. This data-driven approach enables teams to deliver software faster with greater reliability and improved system stability. By focusing on deployment frequency, lead time for changes, change failure rate, and …