INTRODUCTION – Prompt Engineering: Techniques and Approaches
Enrollees in this module will discover the various adages about prompt construction and the techniques for directing generative AI toward a desirable result. The different approaches to prompt engineering will allow the participants to know how to optimize the capacity of generative models to provide more precise and contextual outputs.
Thus, they shall employ these tools into their entire repertoire, enabling them to maximize the use of generative AI.
Learning Objectives
- Apply various prompt engineering techniques for successful text prompts.
- Adapt prompt engineering techniques to improve generative AI models’ responsiveness.
PRACTICE QUIZ: WRITING EFFECTIVE PROMPTS
1. Which of the following techniques helps text prompts guide LLMs to generate responses within specific boundaries, ensuring that the output aligns with the desired requirements?
- Task specification
- Framing (CORRECT)
- Bias mitigation
- Domain expertise
Correct! Framing is a technique that is used to scope text prompts for LLMs so that it can be directed towards generating controlled outputs along specific dimensions, basically meeting a certain specification or condition with respect to the prompt.
2. Which of the following prompt engineering approaches involves breaking down complex tasks into easier ones through a sequence of simpler prompts to guide the model toward the intended outcome?
- Cognitive building
- Interview pattern
- Chain-of-Thought (CORRECT)
- Tree-of-Thoughts
Correct! In the Chain-of-Thought approach, breaking down a complex task into simpler, smaller, and prima facie longer prompts makes the model behave in a more efficient manner to achieve the intended outcome.
3. How does the interview pattern approach enhance the interaction with generative AI models?
- By hierarchically structuring a prompt or query
- By promoting a back-and-forth exchange of information with the model. (CORRECT)
- By providing a single static prompt to the model.
- By focusing on a conventional prompting approach
Correct! The interview pattern approach advances interrogation with generative AI models, whereby the system throws questions back and forth between users to iterate and refine the clarity of the answer pose rather than merely feeding back a known state.
GRADED QUIZ: PROMPT ENGINEERING: TECHNIQUES AND APPROACHES
1. Imagine you are planning a business trip, and you want to use the interview pattern approach to prompt an AI model to assist you in planning your itinerary. What would be the benefit of this approach in comparison to a traditional static prompt?
- The model will generate a random travel plan.
- The model will provide a single predetermined itinerary
- The model will ask for your preferences and adjust the itinerary accordingly (CORRECT)
- The model will minimize the need for any user interaction
Correct! The approach interview patterned with specific prompt instructions will bring relevant questions to the model from the user, leading to the grooming elaboration of a much more refined answer.
2. Jennifer wants to request some useful information about a complex medical condition using a large language model. Which among the following techniques should she employ on the text prompt to ensure that the generated content is relevant, accurate, and precise for this specialized field?
- Task specification
- Bias mitigation
- Framing
- Domain expertise (CORRECT)
Correct! Actually subject-matter knowledge constitutes a technique by which the credibility of the output of LLMs might be enhanced in the area of content-specialized generation through dependence on more accurate and precise output.
3. Imagine you are a content developer working with LLMs, and you must ensure that the responses generated are indiscriminatory and neutral. Which among the following techniques would you employ with your text prompts to instruct the model appropriately?
- Zero-shot prompting
- Bias mitigation (CORRECT)
- Few-shot prompting
- Contextual guidance
Correct! Bias mitigation happens when text prompts contain explicit instruction for the language model for which the response has been generated for an aim to be neutral and unbiased, thereby helping in mitigating the unintended bias that could come in the output.
4. Imagine you are using the Chain-of-Thought approach to teach a generative AI model how to solve a mathematical problem. What is the key component of a prompt in this approach?
- A prompt includes a series of related questions without the correct answer.
- A prompt includes a list of formulae to solve the question.
- A prompt consists of a question and a correct answer for context. (CORRECT)
- A prompt includes only a question without an answer.
Correct! Includes a prompt with a question and with a right answer for chain-of-thought to provide some background and steps to successfully guide the model in generating an appropriate response.
CONCLUSION – Prompt Engineering: Techniques and Approaches
This module, however, gives them a full understanding of prompt engineering techniques within the arena of generative AI.
Mastering the art of prompt construction as well as engineering techniques will prepare the participant to allow that generative AI model to accurately respond in context for almost any need. Even better, it would allow participants to learn how to employ the technology of generative AI for their innovative applications and drive progress in the discipline, which is the hallmark of their training.