According to God of Prompt on Twitter, after testing over 200 custom instruction sets for ChatGPT, five specific instruction patterns were identified that increased output quality by 3.4 times. The analysis highlights that while most users do not optimize the custom instructions feature effectively, these proven patterns can significantly enhance ChatGPT's performance and practical value for business and productivity applications. As reported by God of Prompt, leveraging these optimized instruction sets represents a major opportunity for organizations seeking to maximize the effectiveness of AI-powered workflows.

According to @godofprompt, the shared GOD.MODE.GPT prompt introduces a structured methodology for optimizing AI model outputs by leveraging advanced frameworks such as assumption stripping, systems thinking, bias detection, and precision adaptation. This approach highlights practical AI industry trends in prompt engineering, focusing on systematically improving output quality for business and technical applications. By integrating frameworks like steelmanning, premortem analysis, and incentive mapping, businesses can achieve more reliable, accurate, and creative AI-driven solutions. This development exemplifies the growing importance of prompt engineering in maximizing value from generative AI systems (source: @godofprompt via Twitter, Nov 2025).

According to Sam Altman on Twitter, ChatGPT has updated its personalization page by consolidating personality configuration, custom instructions, and memory features into a single, streamlined interface. This change, rolling out over the next few days, is designed to improve usability and user experience for both individual and business users. The unified interface allows for more efficient workflow customization and deeper personalization, which creates new opportunities for enterprises to tailor AI interactions to their specific operational needs. This update also reflects a broader trend towards user-centric design in AI platforms, increasing adoption potential in enterprise and customer service environments (Source: Sam Altman, Twitter, Sep 16, 2025).