ChatGPT Fear Free
ChatGPT Fear Free
With all the hype and hysteria, engaging with open-minded curiosity is hard, much less finding quality free resources that help you get started.
These LLMs feel ‘people like’, but they are not ‘people,’ so while the interaction is conversational, you are still talking to a machine: a bright one, but a machine all the same.
Why It Matters
Get there by going there.
Here is a basic cheat sheet of prompting styles proven by researchers testing ChatGPT’s ability to answer effectively.?
I’ve done my best to keep this simple while still using the terms that will help you in a search engine or with GPT itself.
The resources section is designed to give you a tree of options to go deeper.
Explicit Instruction Prompts
Explicit Instruction Prompts are straightforward commands or requests. You directly ask the model to perform a specific task. This style of instruction is called a ‘Zero Shot Prompt’ because you are giving the AI model no additional context or information.
Design: To design these prompts, simply state what you want the model to do. Be clear and specific.
Uses: exploring high-level explanations of topics.
Examples:
Leading Question Prompts
Leading Question Prompts guide the model toward a specific type of response. They are questions designed to solicit a particular answer.
It is called a leading question because it implies specific assumptions that will be included in the response.
Design: Formulate a question that nudges the model toward the desired output.
Uses: Exploring assumptions or presumed impacts of a specific attribute of a problem or topic space.
Examples:
Directional Stimulus Prompts
Directional Stimulus Prompts is equivalent to asking the AI to put on a character and then asking that character a specific question.
You ask the model to take a specific role that informs the perspective of the response.?
Design: Decide on the specific ‘character’ or role you want to provide a perspective on a specific topic. This could be a specific perspective, format, structure, or thought.
Examples:
System Message Prompts
System Message Prompts set the context for the model by simulating a system message. They can define the role of the AI, the user, or the overall scenario.
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Design: Write a message that sets up the context or scenario for the model's response.
Examples:
Role Play Prompts
Role Play Prompts involve setting up a scenario where both you and the AI take on specific roles and interact accordingly.
Design: Define the roles of you and the AI, and set up a scenario for them to interact.
Examples:
ReAct Prompts
Personal favorite
ReAct Prompts reformulate a task to make it more explicit and contextualized for the model.
Design: Identify the task, then reformulate it to provide more context or explicit instructions.
Examples:
Chain-of-Thought Prompts
Chain-of-Thought Prompts guide the model through steps or thoughts to reach a desired output.
Design: Break down the task into smaller steps, then write a series of prompts that guide the model through each step.
Examples:
Few-Shot COT Prompts
Few-Shot COT Prompts provide the model with a few examples of a task and then guide it through a series of steps to complete a similar task.
Design: Provide a few examples of the task, then break down the task into smaller steps. Write a series of prompts that guide the model through each step.
Examples:
Summing Up
Accelerating your work with AI tools begins with playing with them. Having proven prompt methods to start with is a great way to learn.
Start with any task you have at hand or if you'd like an activity, start with this article "How ChatGPT Actually Works" and use ChatGPT to explain terms in and concepts in ways that may work better for you.
Useful References
Prompt Engineering Guide - This guide was built from this documentation by removing content aimed at LLM engineers and scientists and focusing on getting the best result out of the model with proven prompts designs.
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