# The “What Are Your Thoughts?” Method: A Primer on Autonomous AI Prompting The “What Are Your Thoughts?” method is a prompting technique designed to foster autonomous feedback loops within AI models, minimizing human intervention and encouraging expansive thinking. This approach leverages the AI’s capacity for self-reflection and refinement by essentially mirroring its own output back as input. Instead of providing specific guidance or corrections, the user primarily repeats the AI’s concluding questions or instructions, prompting it to delve deeper into its own reasoning and generate more comprehensive solutions. **The Core Principle:** The underlying principle is to shift the burden of solution development from the user to the AI. Recognizing that the user often asks questions precisely because they *don’t* know the answer, this method allows the AI to become the primary driver of the problem-solving process. By echoing its own prompts, the AI is encouraged to: - **Engage in metacognition:** Reflect on its own reasoning process, identifying potential weaknesses or areas for improvement. - **Develop autonomous feedback loops:** Use its own output to refine subsequent responses, iteratively converging towards a stable solution. - **Explore a wider solution space:** Without restrictive user input, the AI can consider more diverse approaches and potentially discover more innovative solutions. **Implementation Steps:** 1. **Initial Prompt:** Begin with a clear and concise prompt outlining the problem or task. 2. **Echoing the AI:** After the AI’s initial response, identify its concluding question or instruction directed back to the user (e.g., “What are your thoughts?”, “What should we do next?”, “How does this sound?”). 3. **Repeat and Refine:** Rephrase the AI’s concluding prompt and return it as your next input. This encourages the AI to elaborate on its previous response and develop its reasoning further. 4. **Iterate:** Continue this process of echoing and refining for several iterations. Observe how the AI’s responses evolve and become more nuanced, detailed, and potentially more creative. 5. **Intervention (if necessary):** Only intervene with specific guidance or corrections if the AI veers significantly off track or becomes stuck in a unproductive loop. The goal is to minimize human input and allow the AI to drive the solution process as much as possible. **Example:** **User:** Design a new type of eco-friendly packaging. **AI:** I’m considering biodegradable materials and minimizing the overall volume. What are your thoughts on incorporating recycled ocean plastic? **User:** What are your thoughts on incorporating recycled ocean plastic? **AI:** Using recycled ocean plastic is a compelling idea. It addresses the pollution issue and reduces reliance on virgin plastics. However, the sourcing and processing of this material present logistical and cost challenges. Perhaps a hybrid approach using both biodegradable materials and a percentage of recycled ocean plastic would be optimal. What are your thoughts on a hybrid approach? **User:** What are your thoughts on a hybrid approach? **AI:** A hybrid approach offers a good balance between sustainability and practicality. We could use a biodegradable base material derived from seaweed or mushroom packaging, reinforced with recycled ocean plastic fibers. This would combine the biodegradability of one material with the strength and durability of the other. We could also explore different ratios of the two materials to optimize cost and performance. What are your thoughts on using a seaweed-based material reinforced with recycled ocean plastic fibers? **Benefits:** - **Encourages deeper AI thinking:** Promotes a more analytical and self-reflective approach to problem-solving. - **Fosters creativity and innovation:** Allows the AI to explore a broader range of solutions than might be considered with more directive prompting. - **Reduces user effort:** Shifts the burden of solution development to the AI, freeing up user time and cognitive resources. **Limitations:** - **Potential for divergence:** Without sufficient constraints, the AI might wander off topic or become fixated on unproductive lines of inquiry. - **Requires patience:** Converging on a stable solution can take multiple iterations and may require more time than traditional prompting methods. - **Not suitable for all tasks:** This method may be less effective for tasks requiring very specific or highly constrained solutions. The “What Are Your Thoughts?” method offers a powerful way to unlock the autonomous problem-solving potential of AI models. By embracing a more hands-off approach to prompting, we can encourage the AI to become a more active and insightful collaborator in the creative process.