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PROMPT ENGINEERING

AI - GETTING AI TO WORK WITH YOU

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LET'S GET SIGNED UP/IN

PROMPT ENGINEERING

  • Login to machine per instructions.

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  • Open an InPrivate/Incognito window on your chosen brower.
  • Go to ChatGPT.com
  • No account? Choose "Sign up for free"
      • Log into your preferred email for this tool, and click to verify.
  • Been here before? Choose "Sign in" and help a neighbor. :)
  • Now, let's get familiar.

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A little background to help us along the way.

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Who’s taken an algebra class?

x^3 graph

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Who’s taken an algebra class?

-5x^3 graph

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Who’s taken an algebra class?

x^3/5 graph

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Who’s taken an algebra class?

(x^3)+5 graph

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Who’s taken an algebra class?

(x^3)/5 graph

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Who’s taken an algebra class?

ALL functions graphed

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GEEKS FOR GEEKS ANSWER

HOW DOES THAT TRANSLATE TO AN AI?! (tl;dr: LLMs, GPTs)

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Whoa, that was a lot! Let’s discuss…

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Ethical Use

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  • Don’t share personal medical data
  • Don’t send your SSN, bank info, passwords
  • Be cautious with government benefits info
  • Avoid harmful stereotypes
  • Treat AI as a tool, not an authority

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Help me understand [something I find confusing online], and explain it in a way that works best for me.

In a new chat

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According to Coursera, "Prompt engineering is a technical term for a straightforward action: It means prompting (or requesting) a generative AI tool to perform a task."

WHAT IS PROMPT ENGINEERING?

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4 MAIN TYPES OF PROMPT ENGINEERING

  • Zero-shot prompting: This is the most direct and simplest method of prompt engineering in which a generative AI is simply given direct instruction or asked a question without being provided additional information. This is best used for relatively simple tasks rather than complex ones.

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  • Few-shot prompting: This method involves supplying the generative AI with some examples to help guide its output. This method is more suitable for complex tasks than zero-shot prompting.

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  • Prompt chaining: The prompter splits a complex task into smaller (and easier) subtasks, then uses the generative AI's outputs to accomplish the overarching task. This method can improve reliability and consistency for some of the most complicated tasks.

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  • Chain-of-thought (CoT) prompting: This method helps improve an LLM's output by breaking down complex reasoning into intermediate steps, which can help the model produce more accurate results.

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ZERO SHOT

PROMPT ENGINEERING

  • This is the most direct and simplest method of prompt engineering in which a generative AI is simply given direct instruction or asked a question without being provided additional information. This is best used for relatively simple tasks rather than complex ones.
  • An example.

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FEW SHOT PROMPTING

PROMPT ENGINEERING

  • This method involves supplying the generative AI with some examples to help guide its output. This method is more suitable for complex tasks than zero-shot prompting.
  • An example.

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PROMPT CHAINING

PROMPT ENGINEERING

  • The prompter splits a complex task into smaller (and easier) subtasks, then uses the generative AI's outputs to accomplish the overarching task. This method can improve reliability and consistency for some of the most complicated tasks.
  • An example.

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CHAIN OF THOUGHT PROMPTING

PROMPT ENGINEERING

  • This method helps improve an LLM's output by breaking down complex reasoning into intermediate steps, which can help the model produce more accurate results.
  • A quick video

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THE STAR METHOD

CHAIN OF THOUGHT CONTINUED

  • S = Situation Thinking step; What are we trying to get done or solve? What’s the end goal?
  • T = Task; Designing step; Decide how you want the results to returned from the GPT (table, PDF, etc.). Make sure to write this down!
  • A = Action; Get hands on with entering your S & T information; Tell the tool how you want it to give you results, in a table of links, a printable PDF, etc. BEFORE hitting enter, your last sentence/instruction will be “Reflect on the information provided and ask any clarifying questions before providing your results AND, if necessary, provide other suggestions not thought of here with reasonable explanations.”
  • R = Result; Review, refine, repeat until you get the results you’re after.

SITUATION

TASK

RESULT

ACTION

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a non-judgmental accountability partner to help us stick to a goal, track progress.

PROJECT: ACCOUNTABILITY BUDDY

Using the STAR Method, let’s build…

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a supportive companion for managing anxiety and tracking mood.

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Summary & Reflection

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  • AI is a collection of pretrained algorithms
  • Interacting with a GPT is called prompting
  • Your accountability buddy can grow over time

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NEXT SESSION: Context, Clarity & Control

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CHEAT SHEETS AND OTHER LEARNING RESOURCES

LEARN MORE ON YOUR OWN

  • Self-Guided learning via GitHub, heavily code based, lots of technical jargon, requires environment usage knowledge.
  • LinkedIn Articles and other learning resources, I like Alex Wang's approach.
  • ASU beginners course, paid course.
  • Use your new found skills and ask the GPT itself.

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RESOURCES

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