As the field of natural language processing advances, language models like ChatGPT, powered by the GPT-3.5 architecture, have gained remarkable proficiency in generating human-like text across various domains. With the popularity of Jakarta EE (formerly known as Java EE) for enterprise application development, it is crucial to assess the capabilities of ChatGPT in writing Jakarta EE code and determine if developers can rely on it for their projects.
This talk aims to delve into an analysis of ChatGPT's aptitude in writing Jakarta EE code, scrutinizing its efficacy, accuracy, and usefulness as a coding assistant. We will explore the strengths and limitations of ChatGPT when it comes to generating Jakarta EE-related code snippets, configurations, and best practices.
