AI errno(2) values (www.netmeister.org)

On May 19, 2026, a significant update was announced in the form of a new header file, _AI_ERRNO_H_, which introduces a set of error values specifically for common AI-related failures. This initiative aims to enhance the robustness and debugging capabilities of AI systems by assigning distinct error codes for issues unique to artificial intelligence, such as hallucinations (EAI) and unjustified confidence (EDUNK). With these tailored errno values, developers will be better equipped to identify, diagnose, and resolve AI problems, leading to more reliable and accountable AI applications. This update is particularly important for the AI and machine learning communities as it recognizes the complexities of AI systems and the need for specialized error handling. By standardizing error responses, this initiative could significantly improve the development process, help maintain ethical considerations, and ensure systems operate safely. The inclusion of humorously named error codes like "EGAD" for lost context or "EMACS" for being unable to exit vi reflects a growing recognition of AI's quirks and the challenges faced by developers in managing AI deployment, ultimately fostering a more thoughtful approach to AI reliability and oversight.