According to God of Prompt on Twitter, current prompting methods for large language models (LLMs) face significant issues with hallucination, where models confidently produce incorrect information (source: @godofprompt, Jan 5, 2026). While few-shot prompting can partially mitigate this by providing examples, it is limited by the quality of chosen examples, token budget restrictions, and does not fully eliminate hallucinations. These persistent challenges highlight the need for more robust AI model architectures and advanced prompt engineering to ensure reliable outputs for enterprise and consumer applications.