Setting Up AI for Success: The Most Popular Prompting Frameworks

What is prompt engineering?

Prompt engineering is carefully crafting the prompts or instructions fed into AI systems like ChatGPT. It involves strategically wording and structuring prompts to get the best output from the AI.

Here's a simple explanation of how it works:

Imagine ChatGPT is like a robot assistant to which you give tasks and commands. Prompt engineering is finding the best way to phrase those tasks and commands so the robot can understand and complete them properly. 

For example, telling the robot to "write a blog post" is very broad. The robot doesn't know what kind of blog post you want or the specifics you want included. But if you give the robot more details, like "write a 300 word blog post about the benefits of AI assistants, focus on how they can improve customer service," it can generate a much better result.

Prompt engineering is like learning to give the robot precise instructions to get the desired output. You have to experiment and tweak the wording, level of detail, formatting, and examples you provide.

The goal is to make your prompts easily understandable specific, and provide enough context and direction so ChatGPT can create high quality, targeted responses. It takes practice, but prompt engineering is key to using AI assistants effectively.

Different prompting frameworks:

Here are some of the most popular prompting frameworks for crafting effective AI prompts.

PAL (Prompt, Actions, Lessons)

Gives a clear prompt, outlines actions, and provides lessons/examples. 

"Prompt: Write a 300 word blog post about chatbot benefits. Actions: Focus on 3 key benefits, use statistics, and include one example. Lessons: See the attached introduction paragraph example."

BART (Background, Action, Result, Takeaway)

Provides background context, defines the task, describes the ideal result, and key takeaways.  

"Background: Chatbots are becoming popular for customer service. Action: Write a 300 word blog post highlighting the benefits of chatbots for customer service. Result: A draft post covering 3 benefits and an example case. Takeaway: Emphasize how chatbots increase efficiency."

FORD (Facts, Options, Resolution, Decision)  

Presents relevant facts, outlines possible options, states desired resolution, and specifies the decision needed.

"Facts: Chatbots can offer 24/7 support. They can handle common queries. But they lack human empathy. Options: Outsource support or use chatbots. Resolution: Hybrid model balancing chatbots and human agents. Decision: Should we invest in chatbot customer service?"

AID (Audience, Intent, Details)

Identifies target audience, states intent, and provides key details. 

"Audience: Small business owners. Intent: Persuade to use chatbots. Details: Focus on cost savings, 24/7 availability, and integration options."

STAR (Situation, Task, Action, Results)

Describes situation, defines task, actions to take, and expected results.

"Situation: Our client needs to improve customer service. Task: Recommend a chatbot solution. Action: Research options, analyze use cases, and create a proposal. Results: Client adopts chatbot solution."

CRISPE (Context, Requirements, Examples, Style, Purpose, Exclusions)

Provides context, outlines requirements, gives examples, specifies style, states purpose, and
notes exclusions.

"Context: There is an ongoing debate around regulating AI systems. Requirements: In a 450 word report, analyze key perspectives and provide recommendations. Examples: See attached report format. Style: Adopt a neutral, objective tone. Purpose: Offer balanced insights into AI regulation for policymakers. Exclusions: Avoid definitive stance for or against regulation."

Other tips:

Here are some tips for creating effective prompts when using GPT models like ChatGPT:

  • Be specific - Give the AI a clear context and goal for what you want it to generate. For a blog post, you could say, "Write a 300 word blog post explaining the benefits of using AI assistants for customer service." 
  • Provide examples - Give the AI 1-2 examples of the style, tone, or format you want. For a blog post, provide a sample intro paragraph.
  • Use plain language - Write prompts conversationally using simple words and grammar. Avoid overly complex or technical language.
  • Break down complex requests - For long or multi-part assignments, break them down into smaller, simpler prompts focused on one task at a time.
  • Limit scope - Narrow the topic and give the AI constraints to focus its response. For a blog post on AI assistants, specify the post should focus on ChatGPT and Claude.
  • Guide content - Use keywords related to the content you want generated. For example, "Write a post comparing the pros and cons of ChatGPT and Claude."  
  • Edit and iterate - View the initial AI response as a draft. Refine the prompt and ask for an improved version if needed.
  • Check accuracy - Fact check key points in the generated text. Provide corrections to inaccuracies to further improve the AI's knowledge.

The key is being strategic with your prompts' phrasing and level of detail. Experiment to see what prompts produce the best results for your use case.