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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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PMI Customer P Charumati India
The prompt should be precise, include the template of the desired output and should provide the exact context.
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Melissa Dufrechou Spring Hill, TN, United States
Jun 11, 2024 2:25 PM
Replying to Melissa Stockbridge
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Some of my items may be redundant but the most important things in my experience so far is:

Be precise and clear.
Be sure you explain jargon or specialized terminology
Provide the context for all of your requests
Be sure you provide the outcomes you are expecting
Experiment and refine as you go

I've found breaking down big problems can be better refined by chunking the whole into natural sections and working to refine each section and then working to put them back together.

Yes, breaking down project into chunks is definitely helpful. I have also found that Microsoft's Copilot often provides good follow up prompts. The back and forth "discussion" with an LLM will help refine the response.
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Taufik Ridzuan Puncak Alam, 10, Malaysia

Write Clear Instructions: Be specific and detailed in your requests.



Always Review & Edit: Never use the AI's output as a final product. Check it for errors.



Fact-Check Everything: Verify all important data, numbers, and facts from trusted sources.



Keep Goals in Mind: Ensure the output actually helps you meet your project's objectives.



Don't Share Secrets: Never input confidential, private, or sensitive company information.
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Siva Subbiah PMO Lead| Senvion Wind technologies Pvt Limited Mumbai, India
To ensure accurate and relevant AI results, first, we need to clarify our goals and provide a specific, detailed prompt. we need to always verify the output by cross-referencing with reliable sources, as AIs can "hallucinate." Finally, use feedback loops to continuously improve the system and ensure it remains aligned with our objectives over time.
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Clovis Abreu Sao Paulo, Sp, Brazil
Asking for references is always a good way as it´s also good to narrow the context of the prompt to your need.
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Joy Miller Glendale, United States
Follow CREATE prompt method, validate, and iterate until you receive the results you are looking for.
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Anonymous
Accurate: ask AI to provide sources
Relevant: provide the context and all useful information
Aligned: be specific in the request
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LaQuisha Archangel Jeanerette, LA, United States
Aim to structure your inputs in a way that clearly conveys a central idea with attention to detail. Include all the relevant information needed to predict your desired outcome while minimizing any extraneous noise. Additionally, it's important to validate all information to ensure accuracy and reliability.
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Melissa Stewart McKinney, TX, United States
Refining and using an iterative process can help to improve the results you get back. We can build more specific outputs by being more specific with what we are asking AI to provide.
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SWAPNIL KUMBHAR Jagruti technical services Pvt.Ltd PUNE, India
Specification of data is important to get desired output
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