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When using AI systems, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?

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Sarah Philbrick
PMI Team Member
Director, Learning Design & Development| PMI Asheville, NC, United States

Validating and checking outputs is critical when working with AI systems like Generative AI. Such validation approaches may include establishing clear criteria, implementing strong testing protocols, and continuous refinement.

In your experience with AI, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?

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Use the CREATE format and as part of the Request be sure to be intentional with your wording so as to provide specificity and clarity to the LLM.
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Bradley Cathcart Houston, Tx, United States

Define the objective: Start with a clear action verb (e.g., "Summarize," "Draft," "Analyze," "Compare"). Tell the AI exactly what you want it to achieve.

Avoid ambiguity: Vague prompts yield vague results. Instead of asking "Make this better," ask "Rewrite this paragraph to sound more professional and concise."

Set constraints: Specify what you do not want. If you only want a high-level overview, explicitly state "Do not include technical jargon" or "Limit the response to three paragraphs."

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