Director, Learning Design & Development| PMIAsheville, 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?
When using AI, it is important to provide specific and clear information. It is also essential to verify the accuracy of the information provided by AI by checking cited sources and consulting reliable references. This helps identify potential errors, misinformation, or outdated information before relying on the results. Saving Changes...
When using AI systems is very hard to set the precision or accuracy of the responses. I love bringing in the Agile mindset here pretty much imagine if you are mentoring someone you do a Q&A and based on the reponses of your Mentee you give the feedback so that Mentee can align his/her thoughts in the direction that we hint similarly review the AI responses and using our rationale judgement
1- Give Feedback to the AI system
2- Rework on your promp and be specific on what is expected
3- Keep it short and conscise, guage the responses and slowly we can tune the AI system in a way to get the best output
4- Now the Tech. Solution that comes in for accuracy is havig specific set of APIs that talk to real and accurate data sources or use 2-3 outputs of LLMs and then analyze and bring the best in output.
Provide Context Include: Purpose, desired outcome, constraints Be specific and ask AI to challenge your assumptions Maintain Human judgment Saving Changes...
i bounce the answers between two LLMs - usually Co-Pilot and Gemini. it helps catch errors that one LLM may be stubborn about or we lack domain knowledge to have caugjht in the first place
One of the most important lessons I've learned when using AI is that the quality of the output depends heavily on the quality of the input. To get accurate and relevant results, I try to provide clear context, specific objectives, and any constraints or expectations upfront. I also avoid treating AI output as the final answer. Instead, I review, validate, and refine the results using my own experience, business knowledge, and understanding of stakeholder needs. AI is an incredibly powerful tool, but it works best as a collaborator rather than a replacement for critical thinking. The combination of clear prompting, human judgment, and continuous refinement is what ultimately ensures the outcome stays aligned with the original goal.
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Charles GriffithProject Management| SelfReston, VA, United States
It's imperative to validate the data, as refinement happens over time and not all at once. Realize that the tool is as good as it's input and your results (expected or not) will vary. Just be patient and prompt well with clear and concise language to start.
Saving Changes...
Charles GriffithProject Management| SelfReston, VA, United States
It's imperative to validate the data, as refinement happens over time and not all at once. Realize that the tool is as good as it's input and your results (expected or not) will vary. Just be patient and prompt well with clear and concise language to start.
Getting good results from AI starts before you type anything. I make sure I know exactly what I want and who it's for, then give the AI real context, like the setting, timeline, and constraints, instead of a vague request. Breaking big tasks into smaller steps and asking the AI to point out its own assumptions helps me catch problems early. Most importantly, I verify everything. Nothing gets used without checking it against reliable sources and against my original goal. I also keep sensitive or patient information out of public AI tools. The AI helps, but I'm still responsible for the result. Saving Changes...
Start with clear and specific prompts that provide enough context. Break complex tasks into smaller steps, verify outputs against trusted sources, and refine prompts based on the results you receive. It's also important to maintain context throughout the conversation, review outputs critically for potential AI hallucinations, and avoid sharing sensitive or confidential information. Combining verification, iterative prompting, and human judgment leads to the most reliable outcomes.
Start with clear and specific prompts that provide enough context. Break complex tasks into smaller steps, verify outputs against trusted sources, and refine prompts based on the results you receive. It's also important to maintain context throughout the conversation, review outputs critically for potential AI hallucinations, and avoid sharing sensitive or confidential information. Combining verification, iterative prompting, and human judgment leads to the most reliable outcomes.
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