Do we need specialized prompts when using AI for genealogical research?

 Artificial Intelligence has generated its own jargon or special words or expressions that are used by a particular profession or group and are difficult for others to understand. Jargon is used to exclude outsiders from insiders and can evolve into almost a complete language such as the one used by medical doctors and lawyers. Here is a list generated by Google Gemini showing some of the jargon terms that are regularly used in conjunction with AI:

• AI (Artificial Intelligence) - The simulation of human intelligence processes by machines.

• Machine Learning (ML) - A subset of AI where systems "learn" from data and make decisions.

• Deep Learning (DL) - A subset of ML using deep Artificial Neural Networks to analyze complex data.

• Artificial Neural Network (ANN) - A computing system inspired by the human brain's interconnected neurons.

• Algorithm - A set of rules a computer follows to complete a task.

• Training Data - The dataset used to teach an AI model.

• Bias - Errors in AI output resulting from skewed training data.

• Alignment - Ensuring an AI model's goals and actions match human values.

• Generative AI (GenAI) - AI that creates new content (text, images, video).

• Large Language Model (LLM) - A deep learning model trained on massive text for understanding and generating language.

• Prompt - The user's text input to an AI system.

• Prompt Engineering - The skill of crafting effective prompts for desired AI output.

• Hallucination - When an AI confidently generates false information.

• Token - The smallest unit of text an LLM processes.

• Temperature - A parameter controlling the randomness or creativity of an AI's response.

• Transformer - A neural network architecture effective for language tasks, using self-attention.

• Multimodal Model - An AI capable of processing and generating multiple data types (text, images, audio).

• Retrieval-Augmented Generation (RAG) - A method connecting an LLM to external sources for improved accuracy.

• Artificial General Intelligence (AGI) - Theoretical AI with human-level intelligence across all tasks.

• Artificial Narrow Intelligence (ANI) - AI designed for a single, specific task (current AI).

• Natural Language Processing (NLP) - AI focusing on computers understanding and generating human language.

• Computer Vision - AI that enables computers to interpret visual information.

• Chatbot - A software application that mimics human conversation.

One of these jargon terms, prompt, is used extensively as the term for a way to communicate with chatbots.  There is a fast-growing industry of people "developing" and selling prompt systems. Some of these specialized prompts are being characterized as "secret"  or "perfect." There is already a huge number of YouTube.com videos promoting and selling different "prompt solutions" and yes, there are a number of videos touting genealogy ai prompts. Some of the suggested prompts run into multiple pages of text single spaced. 

So, I asked Google Gemini if specialized prompts get a better or more complete response.  The answer was yes. Here is what the summary said. 

While I can certainly answer simple questions, providing me with specific instructions, context, and constraints acts like giving me a focused searchlight instead of a floodlight, resulting in a more precise, detailed, and complete output tailored exactly to your needs.

The question at the end of the full response from Gemini, was this:

Is there a specific topic or type of information you are currently working on where I could help you formulate a more specialized prompt?

Here is one of Gemini's suggestions:

Components of an Effective Specialized Prompt

Component	Description	Example Phrase
Goal/Task	What you want me to do.	"Generate a summary..."
Context/Topic	The specific subject matter.	"...about the impact of the printing press on 16th-century literacy rates."
Audience	Who the information is for.	"Explain this as if you are talking to a middle school student."
Format/Length	How the answer should be structured.	"Use a bulleted list, starting with a strong topic sentence."
Tone	The desired feeling or style.	"Adopt a persuasive and optimistic tone."

The initial key word is "generate." Using prompts is almost second nature to me because I have been "talking" to computers for years using instructions, programming, queries, and search terms.  I guess my answer to my own question in the title of this post would be a qualified yes. Would any of the videos help you get better responses from a chatbot? I would suggest you might get better feedback from the chatbot itself by simply asking it if there is a better way to ask a question. I asked Gemini and it gave me a long free answer.

es, absolutely! Here is a versatile, high-detail prompt template designed to maximize the completeness and quality of my response, especially for complex or multi-step tasks.

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📝 High-Detail Prompt Template (The R-T-C-F Method)

This method breaks your request into four key areas: Role, Task, Context/Constraints, and Format.

Section	Purpose	Example Instructions
1. 🎭 Role (R)	Sets my persona and knowledge base.	"Act as a senior financial analyst specializing in emerging markets."
2. 🎯 Task (T)	Defines the core action required.	"Your task is to evaluate the risk profile of investing in lithium mining operations in South America."
3. 🛑 Constraints (C)	Imposes limitations or necessary details.	"Focus only on Chile and Argentina. Cite data from 2020-2024. Do not discuss regulatory risk."
4. 🛠️ Format (F)	Specifies the desired output structure.	"Present the analysis as a comparison table with three columns: Country, Production Volume, and Key Risk Factor. Conclude with a two-sentence summary."

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➡️ Template Structure for You to Copy and Fill In

Markdown

**[1. ROLE]** Act as a [Specific Role/Expertise].
**[2. TASK]** Your primary task is to [Specific Action Verb and Goal].
**[3. CONTEXT & CONSTRAINTS]**
* **Topic Focus:** [The exact subject matter.]
* **Scope Limits:** [What should be included and, crucially, what should be excluded.]
* **Depth/Timeframe:** [Level of detail required or historical period to cover.]
**[4. FORMAT]**
* **Structure:** [e.g., Use a numbered list, a table, a 5-paragraph essay.]
* **Tone/Style:** [e.g., Technical, persuasive, conversational, academic.]
* **Length:** [e.g., Limit to 400 words, provide exactly 5 steps.]

✨ Example of a Completed Specialized Prompt

[1. ROLE] Act as a university-level computer science professor.

[2. TASK] Your primary task is to explain the concept of time complexity in algorithms.

[3. CONTEXT & CONSTRAINTS]

• Topic Focus: Big O notation, specifically $O(n^2)$ and $O(\log n)$.

• Scope Limits: Do not discuss space complexity or linked lists. Use Python code examples.

• Depth/Timeframe: Explain the concepts using a simple, real-world analogy before presenting the code.

  [4. FORMAT]

• Structure: Use three distinct sections: Analogy, Code Example $O(n^2)$, and Code Example $O(\log n)$.

• Tone/Style: Educational and clear.

• Length: Keep the entire response under 500 words.

Do I thnk all this would improve my interaction with chatbots? Maybe, but I already get the answers I need and ask for just using my own computer-speak. Hmm, maybe I should have tried to sell all the information I got from asking Gemini?

The whole idea here is that if you have a question and you don't get the answer you expected, ask your chatbot to tell you how to ask the question. You don't really need to watch YouTube videos or pay for the information unless you are already paying for a chatbot.