Last Updated on January 8, 2024 by Showrooms Online
Prompt Engineering Thoughts
To effectively work with AI (Chat GPT) and get better results. (responses) Apply prompt engineering principles. Using AI and well crafted prompts, you can extract knowledge and derive insight from the data.
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The following video was created by AI using a story line from this blog.
NavigatingAIin2024 2 (youtube.com)
Data Analytics
Data analytics delivers more effective decision making.
There are four key types of data analytics
- Descriptive, which answers the question, “What happened?”
- Diagnostic, which answers the question, ”Why did this happen?”
- Predictive, which answers the question, “What might happen?”
- Prescriptive, which answers the question, “What should we do next?”
AI generates information from data. AI can also organize information so that it becomes usable knowledge.
The results are informed strategy formulation and decision-making.
The flow is data to information to knowledge combined with experience to wisdom.
AI Automates the Routine
AI can also automate the routine tasks to improve efficiency and productivity while freeing up the time and energy to do the creative work.
It all starts with developing the skills required to communicate with the AI model. This is achieved by applying the techniques and principles of prompt engineering.
Prompt Engineering
Crafting a well engineered AI prompt that will generate relevant and useful responses from Chat GPT. There is a lot you can do to ensure the best possible outcome.
Talk to the AI like you would talk to a person. Writing prompts have long been a part of the writing process before there was AI. Good practices are, in most ways, the same for a student as they are for talking to a LLM, (large language model).
A Prompt Outline, The Key Elements
There are key elements that comprise every well engineered prompt.
1. Provide Context: ( for example) I am a custom home builder interested in learning the basics of building science so I can design and build more energy efficient home. Provide a role for the Ai such as trainer, consultant, adviser, summarize, or fact check.
2. Be Specific: Define the task. Be specific, concise and provide essential instructions. Include relevant examples without overly constraining the response. Add key words by way of direction.
3. Include Format: Write an article, make a list, research a subject, write a blog with H2 headings, create an outline
4. Add Constraints: Specify word count, tone, anything not to be included. Exclude a response if no facts are available..
Alternate Approaches
1. Iterative Prompts: Modify the prompt and compare results. Just re prompt and learn as you go. This is the same as asking follow up questions.
2. Chain of Thought (CoT): Breakdown the task into simpler questions and use a coherent chain of thoughts. Get your responses in smaller bite sizes and build a total response in steps.
3. Ask the AI: Ask the AI model to draft a prompt for you. This may be part of the future using prompt apps. Some key elements are still needed in the ask.
4. Progressive Summarization: Long answers or large documents may be better understand by using a progressive summarization. Use the answer as the next prompt.
5, Chunking: Larger documents may require entering the text in the prompt in segments. Overlapping these segments may help keep the pieces in the right order.
In Summary
In summary, crafting a prompt is similar to coding a program, line by line in plain English.
Developing several standard templates for prompts and pretested sample prompts that have been proven to work is an efficient and effective approach.
Language skills are even more important than technical skills or coding skills.
We asked GPT to comment on this article. The response is provided here unedited.
GPT commented on the above article
The article on prompt engineering provides valuable insights into the effective utilization of AI, particularly Chat GPT, through well-crafted prompts. Here are some merits of the article:
Clarity on Data Analytics and AI:
- The article establishes a clear connection between data analytics and AI, highlighting the four key types of analytics (descriptive, diagnostic, predictive, and prescriptive). It emphasizes how AI can transform raw data into usable knowledge, contributing to informed decision-making.
Flow from Data to Wisdom:
- The article outlines the flow from data to information to knowledge, combined with experience leading to wisdom. This conceptualization provides a holistic understanding of how AI, through prompt-driven interactions, contributes to strategic decision-making and problem-solving.
Efficiency and Productivity Improvement:
- The article acknowledges the role of AI in automating routine tasks, enhancing efficiency, and freeing up time for more creative endeavors. This recognition of AI as a tool for optimization aligns with contemporary trends in leveraging technology for productivity gains.
Importance of Prompt Engineering:
- The article emphasizes the significance of prompt engineering as a fundamental skill in communicating with AI models. It provides a structured template for crafting effective prompts, offering practical advice on elements such as context, specificity, format, and constraints.
Diverse Prompting Approaches:
- The inclusion of alternate approaches to prompting, such as iterative prompts, chain of thought, asking the AI for prompt suggestions, progressive summarization, and chunking, reflects a nuanced understanding of the varied ways users can engage with AI models to extract relevant information.
User-Friendly Template:
- The article provides a user-friendly template for crafting AI prompts, encouraging users to approach the interaction as they would a conversation with a person. This helps demystify the process of communicating with AI, making it more accessible to a broader audience.
Recognition of Language Skills:
- The article underscores the importance of language skills in effectively communicating with AI. It suggests that language skills are even more critical than technical or coding skills, highlighting the human-like nature of interactions with language models.
Efficiency through Standard Templates:
- The suggestion of developing standard templates for prompts and pretested sample prompts adds a practical dimension, offering a systematic and efficient way for users to engage with AI.
In summary, the article provides a comprehensive guide on harnessing the potential of AI, specifically Chat GPT, through thoughtful prompt engineering. It bridges the gap between data analytics, AI utilization, and effective communication, catering to both technical and non-technical users.
Prompt: do you have any suggestions for how the article could be improved?
The ChatGPT response is presented here unedited
Certainly! While the article provides valuable information, here are some suggestions for potential improvements:
Concrete Examples:
- Provide concrete examples to illustrate the application of prompt engineering in real-world scenarios. This can help readers better understand how to implement the suggested principles and techniques.
Case Studies or Use Cases:
- Including case studies or use cases where prompt engineering led to successful outcomes could enhance the practicality of the article. Real examples can inspire readers and demonstrate the effectiveness of the recommended approaches.
Visual Aids:
- Consider incorporating visual aids such as diagrams or flowcharts to visually represent the process of prompt engineering. Visual elements can enhance comprehension, especially for readers who may be more visually oriented.
Further Exploration of AI Limitations:
- Address the limitations of AI, including potential biases, uncertainties, and situations where the model may not provide accurate or appropriate responses. This would help readers have a more nuanced understanding of AI capabilities and constraints.
Interactive Examples:
- Provide interactive examples or exercises that readers can try to reinforce their understanding of prompt engineering. This hands-on approach can make the article more engaging and applicable.
Updates on AI Advancements:
- Given the rapidly evolving nature of AI, consider adding a section or references to recent advancements or developments in prompt engineering techniques. This can keep the content more current and relevant.
Expanded Explanation of Alternatives:
- Expand on the explanations of alternate approaches to prompt engineering, providing more details on when each approach might be most effective. This can help readers choose the right strategy based on their specific needs.
User Feedback Section:
- Include a section on user feedback and experiences with prompt engineering. This could feature anecdotes or testimonials from individuals who have successfully applied the principles outlined in the article.
Integration of Ethical Considerations:
- Address ethical considerations related to AI, prompt engineering, and data usage. Discussing the responsible and ethical use of AI technologies can enhance the credibility and completeness of the article.
Cross-References and Hyperlinks:
- Provide cross-references within the article to related sections and include hyperlinks to external resources or tools that can assist readers in further exploring the topic.
Remember, these suggestions are aimed at further enriching the content and making it even more valuable for a diverse audience. Incorporating practical examples and addressing potential challenges will likely enhance the article’s effectiveness.
