Director, Learning Design & Development| PMIAsheville, NC, United States
With Generative AI, iteratively refining and optimizing prompts can lead to better AI-generated results. This may involve adjusting the specificity or clarity of the prompt to increase relevance and accuracy of results.
What examples do you have of how improving a prompt drastically changed the output quality? What specific changes did you make that led to the improvement?
Initially, when I started using Generative AI, I would get generic and somewhat vague responses. However, as I refined my prompting techniques, it has evolved into an essential tool for my day-to-day work.
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Anonymous
In Generative AI, Iterative refinement and optimization of prompts leads to get the expected outcome, with right quality. It helps to get what we exactly rather than providing outcomeswith less accuracy and expectations. with the help of chain prompting, CREATE, SMART, ABCD, STAR, RTF techniques helps in refinement of the prompts. eventually, it learns from the previous prompts and refines the output effectively and efficiently. Saving Changes...
Getting best result goes on trial and error basis. Adopting right approach of iterative refinement and chaining will lead to achieving best output. Saving Changes...
Initially I used to ask questions in a way similar to what I used to ask Google. I tried to keep it short and specific. But as I started giving more details and context, AI agents started giving me answers catered to my requirements. This was big change. Saving Changes...
Uday GosainSr Director, Solution Train Engineer, Scaled Agile Specialist| Larsen & Toubro Infotech LtdAtlanta, Ga, United States
Has any one started using PromptCowboy? This is a Gen AI tool, to restructure prompts! My wife introduced me to it!
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Tejas BarotPhiladelphia Water DepartmentVADODARA, GJ, India
Jun 21, 2024 7:28 AM
Replying to Sergio Luis Conte
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There are framewoks to create prompt. This is part of the Prompt Desing discipline. Those that gave me and the initiatives where I was included are:R-T-F (Role-Task-Format), T-A-G (Task, action, goal), B-A-B (Before, after, bridge), C-A-R-E (context, action, result, example), R-I-S-E (role, input, steps, expectations).
Defining the context and outlining the interest will help to achieve specific result. Saving Changes...
Anonymous
The quality of the input is reflected in the output ! Saving Changes...
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