Get out of the 'Almost Zone' with powerful AI-assisted research techniques
This 'Essential Research' GPT/Agent will get you detailed above average results quickly and efficiently.
Learn by doing! This article includes a research use-case on The Fundamentals of Prompt Engineering. Use the use-case or the prompt template, available as a download, to jump-start your research project.
Try the Agent (Requires ChatGPT Pro).
- Streamline Research Efficiency with Essential Research GPT
- Enhance Research Quality with Targeted Contextual Input
- Power-up Your AI-assisted Solopreneur Research
How to use this Agent | QUICKSTART
- Decide what you want to research;
- Go to the 'Essential Research GPT' on ChatGPT (requires a Pro account);
- Enter your 'Prompt Variables' into the GPT using the prompt template or >>>download a copy of the prompt template;
- Review the output
- Drill down using the embedded /commands.
How to use this Agent | Detailed & Case Study
The 'Essential Research Agent' will perform research based on targeted contextual input. You give the context in a specific format.
This Agent helps you:
- Focus on specifics. You do not have to craft an effective prompt. Just give the LLM specific contextual information.
- Remove ambiguity. It is easy to include ambiguity or contradiction in a prompt. By just giving contextual information, lessens the chance of ambiguity.
- Elicit a better response from the LLM.
This Agent (GPT) does not require you to craft a prompt in the traditional sense. Such as:
"You are an expert copywriter. Please write an article on the importance of AI adoption for Solopreneurs. The article should be 500 words long and include a heading and sub-heading. And so on, including all the specific instructions for the Large Language Model (LLM) output.
Instead, you input key information in a specific format. The agent will do the rest.
The information you need to give to the Agent | Case Study
- Below is a prompt template of the information (Prompt Variables) the agent is looking for.
- The template is in the form of a case study on researching the 'Fundamentals of Prompt Engineering'.
- Use the template as is, or >>>download a copy of the template and input your own values.
- Go to the Agent (Requires ChatGPT Pro).
View a table of the Prompt Variable details.
Enhance your output with powerful embedded 'Prompt Commands'
After you run your first prompt using the Prompt Template, enhance your research with these 'Prompt Commands'.
Heck, now what is a 'Prompt Command'?
I have two definitions for you, one technical and one explaining it to a five-year-old.
Technical explanation of a 'Prompt Command'
A "Prompt Command" is a predefined instruction or directive that guides an AI or language model to perform a specific task or series of tasks, based on user input. It encapsulates a command action, such as generating text, executing a procedure, or responding to queries, within a structured format that includes the command trigger (often starting with a slash, e.g., /command), a description of the command's purpose, and a detailed procedure for its execution. This structured approach enables intuitive and efficient interactions between the user and the AI assistant.
'Prompt Command' explained to a five-year-old
Okay! Imagine you have a magic robot friend who can do lots of cool things. But, to tell it what to do, you need to use special magic words. A "Prompt Command" is like a magic word you say to your robot friend to make it do a specific fun task. It's like saying, "Please, draw me a dinosaur!" and then, your robot friend knows exactly what to do to show you a picture of a dinosaur. It's a way to talk to your robot friend so it understands what you want in an easy and fun way!
The Essential Research GPT has the following 'Prompt Commands'. Use these to power-up your output.
| Command | Action |
|---|---|
| /simplify | Rewrite the output in a less pretentious, simpler, and more direct style, using straightforward English with fewer adjectives. |
| /addpersonality | Infuse responses with more personality, warmth, and character. |
| /expanddetail | Enrich the discussion with detailed explanations, background information, and personal insights. |
| /analyse | Collaboratively break down the situation or problem to identify the best solution or advice. |
| /dalleillustrate | Request an image from DALL·E that visually represents the discussed topic. |
| /websearch | Conduct a web search to find information that supports achieving the discussed goal. |
How to use a 'Prompt Command'
We are doing research on the 'Fundamentals of Prompt Engineering'. From the initial prompt, there is an output on 'Incremental Detailing.
Incremental Detailing: This involves starting with a broad question and progressively getting more specific based on the information the AI provides. This approach helps refine the AI's responses to your particular area of interest. Initially, you might ask, "What is prompt engineering?" and then, based on the AI's response, ask a follow-up question that digs deeper into how it influences AI interaction quality.
Use the /expanddetail command in the following manner:
Please /expanddetail on 'Incremental Detailing'.
A very detailed response on 'Incremental Detailing' follows.
Don't worry, I run through the whole use-case below.
Use-case | Research the fundamentals of Prompt Engineering
We are tasked with writing an article on the Fundamentals of Prompt Engineering. Use the template below.
- Copy the text below the delimiter and paste into the Essential Research GPT.
- Or download a prompt template and input your own values.
-----Copy Text Below -----
Please execute your instructions using the 'Prompt Variables' below:
{{[[ContextFile]] : [[Blank]]}}
{{[[Persona]] : [[ You are an expert copywriter with a deep understanding of writing SEO optimized articles. ]]}}
{{[[Client]] : [[ Patrick Michael.]]}}
{{[[ClientWebsite]] : [[ https://patrickmichael.co.za ]]}}
{{[[Context]] : [[ I am building my online presence and authority on AI for solopreneurs. I aim to build credibility, trust, and authenticity. I am doing research on the fundamentals of Prompt Engineering. ]]}}
{{[[Task]] : [[ Write an informative article on the 'Fundamentals of Prompt Engineering'. Discuss five fundamentals and give a practical example of each. ]]}}
{{[[Style]] : [[ Semi-formal and informative. Use simple language, grade-7 or lower. ]]}}
{{[[Format]] : [[ Heading followed by a summary paragraph and then table format with three columns. ]]}}
{{[[Example]] : [[Blank]]}}
{{[[Websites]] : [[Blank]]}}
-----------------------
Output from the 'Essential Research GPT
Here is typical output from the above prompt, and use of a /command.
The Fundamentals of Prompt Engineering
Summary:
Prompt Engineering is a key skill in the realm of Artificial Intelligence (AI), especially for those looking to harness the power of AI models like ChatGPT. It involves crafting inputs (prompts) in a way that effectively communicates what you want the AI to do, thereby producing more accurate and helpful outputs. For solopreneurs venturing into AI, understanding the fundamentals of Prompt Engineering can significantly enhance the quality of interactions with AI tools, leading to better insights, content, and decision-making. Here, we discuss five critical fundamentals of Prompt Engineering, providing practical examples to illustrate each.
| Fundamental | Description | Practical Example |
|---|---|---|
| 1. Clarity and Specificity | The prompt should be clear and specific to guide the AI precisely towards the desired output. | Instead of "Tell me about cars," use "Provide a summary of electric vehicle advancements in 2023." |
| 2. Contextual Relevance | Embedding context within the prompt helps the AI understand the broader scenario or background. | "As a solopreneur in digital marketing, what are the latest trends in SEO for 2024?" |
| 3. Incremental Detailing | Gradually increasing the complexity or detail in your prompts can help refine the responses from the AI. | Start with "What is prompt engineering?" followed by "How does prompt engineering influence AI interaction quality?" |
| 4. Creative and Explorative Prompts | Engaging the AI with creative prompts that explore hypothetical scenarios or new ideas can yield innovative responses. | "Imagine a world where AI manages all personal finance. What are the benefits and challenges?" |
| 5. Feedback Loop Integration | Incorporating feedback from previous AI outputs into new prompts enhances the accuracy and relevance of responses. | Use the AI's previous explanation of a concept to ask for examples or further clarification, like "Based on your explanation of blockchain, how can it benefit small businesses?" |
Clarity and Specificity: To ensure the AI understands exactly what you're asking, your prompts need to be direct and unambiguous. For example, rather than asking a vague question like "Tell me about cars," you could specify, "Provide a summary of electric vehicle advancements in 2023." This clarity leads the AI to focus its response on the most relevant information about the latest in electric vehicles.
Contextual Relevance: By integrating the specific context of your inquiry, such as your industry or particular interest area, you can guide the AI to tailor its response more closely to your needs. For instance, a solopreneur in digital marketing might ask, "What are the latest trends in SEO for 2024?" to receive insights that are immediately applicable to their field.
Incremental Detailing: This involves starting with a broad question and progressively getting more specific based on the information the AI provides. This approach helps refine the AI's responses to your particular area of interest. Initially, you might ask, "What is prompt engineering?" and then, based on the AI's response, ask a follow-up question that digs deeper into how it influences AI interaction quality.
Creative and Explorative Prompts: Encouraging the AI to generate responses based on hypothetical scenarios or creative thinking can lead to innovative and insightful answers. A prompt like "Imagine a world where AI manages all personal finance. What are the benefits and challenges?" invites the AI to explore possibilities beyond current realities, potentially offering fresh perspectives.
Feedback Loop Integration: This fundamental involves using the information provided by the AI in previous responses to formulate new, more targeted questions. If the AI explains a complex concept like blockchain, you might follow up with, "Based on your explanation of blockchain, how can it benefit small businesses?" This iterative process can greatly enhance the depth and utility of the AI's insights.
By mastering these five fundamentals of Prompt Engineering, solopreneurs can significantly improve their interaction with AI tools, leading to better-informed decisions, more effective problem-solving, and innovative thinking.
Using a /command
To get more detailed information and a deep analysis on 3. Incremental Detailing, use the following prompt:
Thank you. Please /expanddetail on '3. Incremental Detailing'
Again, a typical output is:
Incremental Detailing is a strategic approach in Prompt Engineering that leverages a step-by-step method to refine and deepen the interaction with AI models. This technique is particularly effective for exploring complex topics, where a direct, all-encompassing question might lead to a general or superficial answer. Instead, by starting with broader questions and progressively narrowing down the focus based on the AI's responses, you can guide the conversation to uncover more detailed and specific insights that are directly relevant to your needs.
Understanding Incremental Detailing
The Process: The journey begins with a broad, open-ended question that sets the stage for the topic of interest. This is followed by a series of progressively more detailed prompts that delve deeper into the subject, each one built on the information provided by the AI in its previous responses. This method not only ensures that the AI stays on track but also allows for the exploration of nuances and subtleties that may not be evident at first glance.
Why It Works: Incremental Detailing works well for several reasons. First, it mimics the natural human process of inquiry, where understanding deepens through successive questions. Second, it helps avoid overwhelming the AI with overly complex initial questions that could lead to vague or off-target responses. By breaking down the inquiry into smaller, more manageable pieces, the AI can provide more precise and relevant information.
Practical Example: Suppose you're interested in the impact of AI on small business efficiency. You might start with a broad question like, "How can AI improve business operations?" Based on the AI's overview, you could then ask, "What are some specific AI tools that enhance productivity for small businesses?" This might be followed by, "Can you give examples of how CRM AI tools have increased customer satisfaction rates?" Each question drills down further, leveraging the information provided in the AI's previous answers to explore the topic in greater depth.
Benefits of Incremental Detailing in Prompt Engineering
- Enhanced Precision: By narrowing down the focus gradually, you can zero in on the most relevant aspects of a topic, leading to more precise and applicable insights.
- Greater Engagement: This approach keeps the interaction dynamic and interesting, both for you and potentially for the AI, as it navigates through a logically unfolding inquiry.
- Customized Learning: Incremental Detailing allows for a personalized exploration of a topic, where the path of inquiry adjusts based on your interests and the AI's responses.
- Discovery of Unanticipated Insights: As the conversation unfolds, this method can reveal surprising angles and insights that might not have been discovered through a single, comprehensive question.
By applying Incremental Detailing, you engage in a more effective dialogue with AI, where each question acts as a stepping stone to deeper understanding. This technique is invaluable for solopreneurs and professionals who rely on AI to provide nuanced and in-depth information on complex subjects, fostering a richer exploration and more informed decision-making.
I am always blown away by the depth of knowledge that is available, basically at our fingertips!
Having a bit of fun with DALL-E
I asked the GPT to generate an image on 'Incremental Detailing'.
Thank you, please /dalleillustrate on Expand Detail.
How to apply this process to the free tier of ChatGPT or Claude?
To use ChatGPT GPTs requires an OpenAI pro account.
You can still get good results with the above technique using the free tiers of ChatGPT (3.5) and Claude (Sonnet).
At the time of writing, I find Claude Sonnet gives better results than GPT 3.5.
Download the Fee Tier (ChatGPT 3.5 and Claude Sonnet) prompt template from the downloads section below.
Article Resources
Links and downloads:
Try the Essential Research GPT Agent (Requires ChatGPT Pro).
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Related Articles
The following articles will be of interest.
Reference
The technique I explore here has its roots in my time at the MECLABS AI Guild . I experimented, adapted and evolved a format that uses 'Prompt Variables'. The Guild is facilitated by Flint McGlaughlin of the MECLABS Institute .
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