AI Code Generation Lifecycle

This workshop explores the transformative potential of generative AI across the software development lifecycle, providing practitioners with hands-on insights into leveraging AI technologies for enhanced productivity. Participants will learn strategic approaches to translating requirements into code using large language models, demonstrating techniques for generating contextually accurate implementations with minimal manual intervention. The session will showcase a case study of an AI-assisted application that intelligently generates both backend services and user-facing displays. Further, see how to automatically produce comprehensive documentation and unit tests. Attendees will gain practical knowledge about effectively prompting AI models for code generation, best practices for reviewing and refining AI-generated code, and advanced techniques for cross-language code migration—including strategies for translating legacy codebases from languages like Java or C++ to modern frameworks like Python or Rust. Through live demonstrations and interactive discussions, the workshop will equip software engineering professionals with actionable methods to integrate generative AI tools seamlessly into their development workflows, emphasizing both the technological capabilities and potential process challenges of this emerging paradigm.