AI-Native Software Engineering: Enduring Principles, New Pace

AI is rapidly changing how software is produced but not the need to engineer software to meet business and mission goals. AI is enabling developers to move from idea to implementation at incredible speeds. However, this fast pace has implications that teams must manage. Product quality does not come for free, and there is some tendency for AI to accelerate the accumulation of technical debt. In addition, what works well on small code bases doesn't always work as well on large code bases. So, what's a good software engineer to do? Software engineering principles and practices are essential in guiding software engineers to use AI to achieve production-ready outcomes. In this webcast, experienced software engineers discuss their observations and lessons from applying AI-native software engineering and studying its use across multiple projects.

What Will Attendees Learn?

• Distinguish between "vibe coding" and software engineering

• Understand how software engineering principles improve the use of AI and where these principles need to be adapted to be used with AI

• Recognize the different criteria that can be used to assess the benefits of AI-native software engineering (e.g., productivity and software quality) and their potential tradeoffs