Prompt Engineering
Learn the fundamentals of prompt engineering that can help optimize AI model responses.
What is prompt engineering?
“The art and science of asking questions is the source of all knowledge.”—Thomas Berger
In generative AI, the art of asking the right questions is known as prompt engineering, and these carefully crafted questions are called prompts.
At its core, prompt engineering is the process of designing effective prompts for generative AI models. It involves providing the AI model with clear and specific instructions on what we want it to accomplish.
Key concepts in prompt engineering
Here are some important key concepts related to prompt engineering.
Context
Context in prompt engineering is crucial for the model to understand the task and generate meaningful responses. The context includes background information that helps the model frame the question or task correctly.
For example, if we ask a language model to write a short story, the context might include the genre, characters, and setting. If we need a technical explanation, the context should specify the domain or field of interest, such as software development, cloud computing, or healthcare.
Look at the difference between these two prompts, showcasing how context can make our prompt more effective:
Prompt without context: “Explain how machine learning works.”
Prompt with context: “Explain how machine learning algorithms are used in predictive analytics for financial forecasting.”
The second prompt provides more context, helping the model understand the specific application of machine learning, resulting in a more relevant and tailored response.
Instruction
An instruction is a clear and direct guideline that specifies what we want the model to do. It tells the model not just what to do, but often how to do it. Clear instructions ensure that the model doesn’t wander off-topic and stays focused on the user’s intent.
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