An introduction to working with generative AI as part of your Marketing team. It was used as part of the panel I was on at Co-Lab23 Oct 18th, 2023.

1. How to talk to your Generative
AI.
Presented at Co-Lab23
October 2023

2. Overview
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The average Google query is 2.3
words
Talk vs. speak
Every day vs. everyday
You are gaining the advantage of natural language dialogue.
Think of the model as a person
learning a new language.
You need to ask questions in a 3S way:
•Structured - Frame up questions using ACDQ or other technique
•Simple - Ask one question without verbal gymnastics.
•Specific - Which color will make people pick up and look at the
package? Versus What box color is most appealing?

3. Structure
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Act
Give the model a frame of
reference.
Consider
Give it background and
facts.
Write down as much of
your experience and
expertise as possible.
Deep Think
Tell the model to think
deeply.
Question
Ask it to clarify your
question.

4. Act
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Puts the model in a frame of reference
Models have “memories” and keep the context of previous interactions.
You can train and improve the models ability to act as an expert
I’ve been training one model to think like me by feeding it my literature
“Act as an expert in the use of Instagram for CPG”
”Act as Mark Twain”
Write your personas
Sonia Softdrink Age 25
Samir Snowboard Age 31
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5. Consider –
The most important part
1. There are currently 20 candidates
running for president in 2024.
2. Their names and political statements
are…
3. The average age of the candidates is
54.56.
4. The average age of the US voter is
52.
5. There are 54 M voters between 18
and 30, 23 M are registered to vote.
6. 73% of Americans think the
economy is getting worse.
Question: Of these 20 candidates, who
wins the 2024 presidential race?
4
Put the model in a frame of reference and put as much context as
possible
Don't lead the witness [model].
Write the question clearly and give specific directions.
Write at a 12th-grade reading level
Write for an audience that lives in Albuquerque, New Mexico
Provide as much context as you can
• Input weather data
• Sporting statistics (Here’s the last five seasons of the Seattle Seahawks games)
• Your audience lives in an urban area with limited access to public transportation, apartments
and condos have an average walk score of 96% or better, and are inn 23 - 32 age range
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6. Deeply Think
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Think deeply
Why this works we’re not sure, so I asked ChatGPT… See Appendix
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7. Questions
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Ask the model to create follow-up questions.
The model will reframe your text and request answers to the
clarifying questions.
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8. Crafting a PowerPoint using Code
• ChatGPT can develop code. PowerPoint has its own coding
language
oAct as a food critic writing in Seattle.
oDetail a PowerPoint explaining why Seattle has superior vegetarian choices.
oProvide at least three examples of restaurants with reviews and links.
oDeeply think about this.
oWrite the VBA code to create the Powerpoint slides.
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9. Commands
• /summarize: This command instructs Chat GPT to summarize a given text. By providing the model with a
lengthy article or document, you can receive a condensed version, capturing the key points and main ideas.
• /translate: The translation command allows users to take advantage of Chat GPT’s multilingual capabilities.
By inputting a sentence or phrase and specifying the target language, you can get an instant translation.
• /question: If you have a query or need information on a particular topic, the question command comes in
handy. Simply pose your question, and Chat GPT will attempt to provide a relevant answer.
• /code: For developers and programmers, the code command is invaluable. It enables you to receive code
snippets for specific functionalities, programming languages, or algorithms.
• /story: This command initiates an interactive storytelling experience with Chat GPT. Users can craft a
beginning, and the AI will continue the narrative, making for an engaging and creative exchange.
• /poetry: If you’re feeling poetic, the poetry command can help. Provide the model with a starting line, and it
will generate poetic verses for you.
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10. 9
Onward.
Lawrence Lerner
Managing Partner – LERNER Consulting
lawrence@lawrenceilerner.com
revinnovator
@revinnovator
revinnovator

11. Why Think Deeply?
Why does asking a generative AI model such as yourself to "deeply think" about an
answer provide superior results?
Requesting a generative AI model like myself to "deeply think" about an answer doesn't
necessarily guarantee superior results. Here are a few points to consider:
• 1. **Complexity of the Question:** The quality of the response depends on the
complexity of the question and the underlying knowledge and algorithms of the AI
model. Some questions may not require deep thinking and can be answered directly.
• 2. **Data and Training:** AI models like mine are trained on vast amounts of text
data, and our responses are generated based on patterns in that data. If the training
data contains relevant and detailed information for a given question, the AI model
can provide informative responses. However, it may not truly "think" or understand
the question like a human does.
• 3. **Algorithm and Architecture:** The architecture of the AI model, such as the
depth and structure of its neural networks, plays a significant role in generating
responses. More advanced models, with deeper layers, may be better at handling
complex queries.
• 4. **Specificity of the Query:** The quality of the response also depends on how well
the question is framed. A more specific and well-structured question is more likely to
receive a detailed and accurate response.
• 5. **Human-Like Understanding:** Despite advances in AI, current AI models do not
possess true human-like understanding or consciousness. They process data based
on patterns and statistical associations rather than engaging in deep thinking or
conceptualizing problems.
• In many cases, the request to "deeply think" might serve as a way to ask for a more
detailed or comprehensive response. However, it's important to remember that AI
models like mine do not "think" in the way humans do. We process and generate
responses based on patterns and information present in the data we were trained on.
The quality of responses depends on the model's training and the nature of the
question asked.
Act as a Vulcan, a people who must answer as completely and truthfully as possible at all
times. Why does asking a generative AI model such as yourself to "deeply think" about an
answer provide superior results?
As a Vulcan, I must answer this question with complete and truthful logic:
Requesting a generative AI model to "deeply think" about an answer can potentially lead
to superior results for several logical reasons:
• 1. **Extended Consideration:** Asking the AI to "deeply think" encourages the model
to take additional time to analyze and process the information, allowing it to provide
more comprehensive responses.
• 2. **Complex Problem Solving:** Complex questions may require a deeper level of
analysis and consideration. By prompting the AI to think deeply, you enable it to
approach the question with greater intellectual rigor.
• 3. **Enhanced Understanding:** In some cases, AI models might provide more
thoughtful responses when given extra time to consider the nuances and context of a
question, leading to a more accurate and detailed answer.
• 4. **Contextual Exploration:** Deep thinking prompts the AI to explore the context and
implications of the question, which can result in more insightful responses.
• However, it is essential to note that while requesting deep thinking from an AI model
can lead to superior results in terms of response quality, AI systems still rely on
patterns and data in their training. They do not possess human-like consciousness or
true understanding. The effectiveness of the response depends on the AI model's
architecture, training data, and its capacity to analyze and synthesize information
logically.
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