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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 14 | Issue 4 | Month- April 2026
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Paper Title
Prompt Engineering for improved AI Responsiveness: Methods and Case Studies
Authors
AYINALA LAKSHMI SATHVIKA, ANNAM PURNIMA, SADINENI HARSHITHA, PERAM ANUSHA, NAFISA SHAIK
Keywords
Prompt engineering, AI responsiveness, NLP, prompt optimization, artificial intelligence, AI interpretability, model bias
Abstract
This paper examines techniques in prompt engineering that can enhance the responsiveness of NLP-based AI models. As AI adoption is increasingly widespread across sectors, accuracy and context-aware responses become critical. We analyze various prompt design methods such as structured phrasing, keyword targeting, and contextual embedding that can enhance AI outputs in fields like customer service, healthcare, and education. Case studies show that well-crafted prompts make AI responses significantly better and prove prompt engineering as an essential skill to enhance the reliability of the model and minimize biases. This paper further emphasizes the role of prompt engineering in advancing the interpretability and trustworthiness of AI models for a wide range of applications.
IJCRT's Publication Details
Unique Identification Number - IJCRT2411056
Paper ID - 271560
Page Number(s) - a468-a471
Pubished in - Volume 12 | Issue 11 | November 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
AYINALA LAKSHMI SATHVIKA, ANNAM PURNIMA, SADINENI HARSHITHA, PERAM ANUSHA, NAFISA SHAIK, "Prompt Engineering for improved AI Responsiveness: Methods and Case Studies", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 11, pp.a468-a471, November 2024, Available at :http://www.ijcrt.org/papers/IJCRT2411056.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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