From Prompt Engineering to Intent Engineering (danielmiessler.com)

In a recent discussion, experts are advocating a shift from Prompt Engineering to Intent Engineering to enhance the effectiveness of AI interactions. This recommendation stems from Sutton's Bitter Lesson, which suggests that as AI becomes more sophisticated, the specific instructions we provide may become increasingly ineffective. The argument highlights that overly detailed prompts can hinder AI's capabilities, as models are evolving to devise optimal solutions better than human-guided methods. Transitioning to Intent Engineering means focusing on articulating desired outcomes—what we want the AI to achieve—rather than dictating the means—how it should accomplish these tasks. This approach aligns with advancements in AI models, such as GPT-5.6 Sol and Fable, which are now capable of interpreting broader goals. By refining prompts from "how" to "what," users can leverage AI's strengths more effectively, moving beyond the dated methodologies of the past. This shift underscores the need for a nuanced understanding of AI capabilities and offers a pathway to more productive and innovative collaborations with technology.