AI Prompt Engineering: Streamlining Tasks and Empowering Efficiency
Introduction
Prompt Engineering is a transformative technique that not only enhances interactions with ChatGPT but also saves valuable time and effort. By crafting purposeful prompts, we can elicit specific types of outputs from ChatGPT that cater to various needs and situations. In this article, we will explore the practicality of prompt engineering through examples that showcase how it streamlines tasks and empowers efficiency. From summarising prompts that extract key points from books to transforming prompts that enable on-the-go translations, let's delve into the functions of each type of prompt and understand how they enhance convenience in our daily lives.
1. Summarising Prompts: Extracting Essential Insights
Function: Summarising prompts condense extensive information into concise summaries, extracting the key takeaways from a given source.
Example Prompt: "Summarise the key points from 'The Power of Habit' by Charles Duhigg."
Output: ChatGPT generates a summary that captures the main concepts, principles, and actionable insights from the book, providing users with valuable knowledge without the need for extensive reading. This function enables efficient information consumption, saving time and effort while still acquiring essential insights.
Other examples:
2. Transforming Prompts: Breaking Language Barriers
Function: Transforming prompts facilitate seamless communication by enabling quick translations between languages.
Example Prompt: "Translate 'Where is the nearest subway station?' into French."
Output: ChatGPT swiftly translates the provided phrase into French, empowering users to navigate foreign environments with ease. This function eliminates language barriers, enabling effective communication and saving users the time and frustration of language-related obstacles.
Other examples:
3. Inferring Prompts: Providing Contextual Recommendations
Function: Inferring prompts utilise implicit context to generate personalised recommendations based on user preferences and assumptions.
Example Prompt: "Based on my preferences, suggest the ideal vacation destination."
Output: ChatGPT uses inferred prompts to analyse the user's preferences, generating tailored recommendations for the perfect vacation spot. This function saves users time by providing curated suggestions aligned with their specific tastes, simplifying the decision-making process and enhancing the overall planning experience.
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Other examples:
4. Expanding Prompts: Stimulating Creativity and Ideation
Function: Expanding prompts foster creative thinking by generating detailed insights and imaginative ideas.
Example Prompt: "Expand on the concept of a futuristic sustainable city."
Output: ChatGPT responds with an expanded prompt, providing detailed insights and inspiring ideas about what a futuristic sustainable city might entail. This function sparks creativity and ideation, saving users time by offering fresh perspectives and stimulating innovative thinking.
Other examples:
Conclusion:
Prompt engineering in ChatGPT offers practical and time-saving benefits across various domains. Summarising prompts extract essential insights, transforming prompts break language barriers, inferring prompts provide personalised recommendations, and expanding prompts foster creativity and ideation. By leveraging these prompt engineering functions, users can streamline tasks, overcome obstacles, make informed decisions, and unlock their creative potential. As AI technology continues to advance, prompt engineering will play an increasingly significant role in empowering users, transforming how we interact with AI models like ChatGPT, and optimising various aspects of our daily lives.
Fun Facts about this article:
Who wrote this: It was 100% written by ChatGPT
What was the process: I provided ChatGPT with an initial prompt and brief notes for the functions I wanted to cover. The first output was unusable. It took six more attempts at prompt refinement to get the output that I wanted.
How long did this take: This process took about 20 minutes all up. Writing this as a traditional blog article without AI assistance would normally take 3+ hours.
Edits performed on content: I have tried asking ChatGPT to write using Australian English but it continues to deliver American English and ignores my request. As such I have edited some words to be Australian English e.g. summarise to summarise. It is only a little thing, but the grammar police in my mind insists I should fix it. I also fiddled with the formatting as all text generated is the same font type and size. I have also moved some content from one output and merged it with a previous output.
Fact Checking: In item 1 a book is referenced, I made sure I fact checked that this book actually exists as ChatGPT is known to make things up! True. Be careful!
The Verdict
As I already know a bit about ChatGPT I was able to provide very specific prompts to get meaningful output. Had I not known the output I was looking for, then the result would have been far inferior. So the verdict? ChatGPT did a good job, but I still have reservations about the quality of content if I was to research a topic I don’t know a lot about. I find you get better output if you provide some basic information that you want ChatGPT to include in your article. Ironically, this means doing a quick Google first!