A Hacker News discussion explores whether a programming language designed specifically for AI generation could improve code reliability by emphasizing explicitness, and how this interacts with LLM limitations, training data needs, and human usability.
Developers discuss how much credit to take for code written with LLMs, debating attribution, responsibility, copyright, and the evolving nature of authorship in software development.
Developers share their real-world experiences with AI coding assistants, discussing benefits like speed and learning, alongside crucial caveats such as verification and potential pitfalls. Discover how to leverage AI effectively in your workflow.