As a professional in the world of L&D, I’m always on the lookout for ways to supercharge my productivity. These days, this includes the use of AI. However, with the rapid increase in the number and variety of AI tools available, I’ve developed a growing concern: these powerful technologies consume significantly more energy than regular computing, contributing to a massive carbon footprint. This has led me to wonder: How can we leverage these powerful technologies without exacerbating global warming? My current conclusion is that the key to striking this delicate balance lies in the ability to use AI efficiently and effectively getting the results you need with minimal prompting and maximum impact.

To achieve this balance, we can focus on mastering the art of prompt design. Effective prompting allows you to obtain high-quality outputs with fewer attempts, reducing the need for extensive back-and-forth with AI models. This not only saves time but also conserves computational resources, which directly translates to a smaller carbon footprint.

Start by crafting precise and well-structured prompts. Instead of relying on vague or general questions, tailor your prompts with specific roles, tasks, and desired outcomes in mind. For instance, rather than asking for “help with course design,” specify your needs: “Act as a SME and analyze this course outline to ensure the content covers all relevant material for a beginner. Provide the findings in a table format with each issue categorized by level of impact.” This approach guides the AI more effectively, leading to better results in fewer iterations.

Additionally, consider using prompt sequencing—a technique where you build on previous outputs with follow-up prompts. Think of it as having an interactive conversation with the tool, rather than peppering it with one-time questions that never get you exactly what you need. This strategy allows for deep work with minimal input, enabling you to achieve great results without unnecessary repetition.

Here are some general guidelines for creating a well-structured prompt:

  1. Identify the Role: Specify who the AI should “act” as (e.g., interviewer, instructional designer).
  2. Define the Task: Clearly state what you want to achieve (e.g., “Generate a list of interview questions to ask a Subject Matter Expert about course material for X subject”).
  3. Include Specific Instructions: Provide any necessary details or criteria (e.g., “Ensure the questions cover both foundational knowledge and advanced concepts relevant to the course. Consider that the audience for the course is advanced.”).
  4. Use Examples When Possible: If applicable, give an example or format to follow (e.g., “Structure the questions in a way that first addresses general topics, then moves to more specific, detailed inquiries”).
  5. Refine Through Prompt Sequencing: Build on the initial output with additional prompts for a deeper, more refined result (e.g., “After generating the initial questions, refine them to ensure they prompt the SME to provide actionable insights and real-world examples”).

By honing your prompt design skills, you can harness AI’s potential responsibly, enhancing your productivity while minimizing your environmental impact. The key is to make every interaction with AI count—doing more with less and making conscious choices that reflect our shared responsibility to protect the planet.