According to @godofprompt on Twitter, implementing structured prompt engineering techniques—such as guiding AI models through planning, execution, and verification steps—dramatically improves output accuracy. Instead of generic prompts like 'do the thing,' providing a scaffolded approach enables AI models to deliver more reliable results. The difference between 70% and 95% accuracy is often attributed to prompt design rather than the underlying model's capabilities (source: @godofprompt, Dec 10, 2025). This insight highlights a major business opportunity: by investing in advanced prompt engineering, enterprises can unlock greater value from existing AI systems without costly model upgrades, directly impacting operational efficiency and competitive advantage.