The Impact of AI on Developer Productivity

Generative AI tools hold promise to increase human productivity.  In the world of software development, GitHub Copilot was one of the first practical applications of the use of generative AI to support developer productivity.  However, measuring software productivity is non-trivial.  For example, developer productivity gains is more than just producing code faster. If these artifacts don’t meet quality standards or themselves bring cost efficiency challenges then there may not be much overall improvement. To truly understand the benefits and challenges of AI-powered copilots requires real-world experimentation.  Join Sida Peng as he presents results from a controlled experiment on GitHub Copilot. During this controlled experiment, recruited software developers were asked to implement an HTTP server in JavaScript as quickly as possible. Programmers with access to the AI pair programmer using generative AI completed the task 55.8% faster than those who did not have access. But what does this mean for us as software practitioners?  Is our future destined to be filled with AI pair programmers? Will they only support junior engineers transitioning into software development, or are they sophisticated enough to also help more senior engineers grow in the discipline? Sida will explore these topics and more surrounding the future of AI for software development.