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Published : Apr 26, 2023
This blip is not on the current edition of the Radar. If it was on one of the last few editions, it is likely that it is still relevant. If the blip is older, it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar. Understand more
Apr 2023
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Prompt engineering refers to the process of designing and refining prompts for generative AI models to obtain high-quality responses from the model. This involves carefully crafting prompts that are specific, clear and relevant to the desired task or application in order to elicit useful outputs from the model. Prompt engineering aims to enhance large language model (LLM) capabilities in tasks like question answering and arithmetic reasoning or in domain-specific contexts. For software creation, you might use prompt engineering to get an LLM to write a story, an API or a test suite based on a brief conversation with a stakeholder or some notes. Developing effective prompting techniques is becoming a valuable skill in working with AI systems. There is debate over whether prompt engineering is an art or science, and potential security risks, such as “prompt injection attacks,” should be considered.

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