Prompt Engineering for Testers – A Talk by Pricilla Billavendran

 

 

 

 

 

 

Here are my notes from Pricilla’s talk on Prompt Engineering for Testers. It is a beginner friendly simple and feel-good session where she discussed on

• Focusing on crafting efficient prompts to get better results from Generative AI and other Large Language Models (LLMs).
• The goal is to explore various techniques, tools, and best practices for effective prompt engineering.

Prompt Engineering Basics

• What is a Prompt?: A prompt is a group of texts, lines, or passages that instructs the AI or LLM to produce desired outputs. Effective prompts lead to better results.
• Prompt Engineering: The art of creating prompts that guide the AI to generate precise and accurate responses.

Prompt Techniques

• Instruction: Start prompts with verbs or action items to direct the AI. Examples include “summarize,” “condense,” or “draft.”
• Role Play: Instruct the AI to assume a specific role, such as a doctor or a superhero, to generate contextually appropriate responses.
• Examples: Provide examples to guide the AI towards the desired output.

Types of Short Prompting

• Zero-shot: No examples are provided, and the AI predicts the output based on its training.
• One-shot: One example is given, guiding the AI to produce the desired response.
• Few-shot: Multiple examples are provided, resulting in improved output quality.

Advanced Concepts in Prompting

• Chain of Thought: Involves breaking down a complex task into smaller steps, enabling AI to explain its reasoning and provide a more comprehensive answer.
• Self-Consistency: Providing diverse examples to encourage consistent and accurate responses.
• Tree of Thoughts: A recent framework that allows the AI to evaluate multiple paths, helping to find the most efficient or correct solution.

Tools for Prompt Engineering

• Prompts Royal: A tool for developing and generating prompts, especially helpful for beginners.
• OpenAI Playground: A platform for experimenting with different modes and models of OpenAI, allowing for prompt testing and refinement.

Best Practices for Prompt Engineering

• Be clear and specific, structuring prompts with examples.
• Avoid overload of information and be mindful of open-ended questions.
• Define constraints and output styles, such as word count and tone.
• Practice and refine your skills through continuous experimentation