Cognilytica’s Prompt Engineering Best Practices Guide: Using Custom Instructions (Part 3 of 6)

This week we share part 3 of our 6 part newsletter on Prompt Engineering Best Practices. Make sure to check out the first part here and second part here if you haven’t already!

Prompting Best Practice #3: Use Custom Instructions

Getting the LLM to do your bidding is always the hardest part. Prompt engineering puts the “Art” in artificial intelligence. Perhaps writing effective prompts should be a standard course in middle school and high school English classes? That’s another topic for another day.

One of the ways of coaxing these LLM systems to providing the desired output is to provide greater context and information that can be applied to one or more prompts. Not only does this help the LLM system provide better focused output, but it can also help to avoid continuously repeating yourself in prompts around aspects of tone, format of output, etc.

OpenAI’s ChatGPT in particular allows you to provide settings that tailor the responses to match your tone and desired output goals as a “default” that can be applied to all future prompts. Many have reported that using custom instructions has resulted in much more accurate, precise, consistent, and predictable results.?

You can provide these custom instructions through the API, or find the Custom Instructions in the “Customize ChatGPT” settings:

In ChatGPT, Custom instructions are provided by answering two questions asked in settings that get sent along with your prompts:

• What would you like ChatGPT to know about you to provide better responses?
• How would you like ChatGPT to respond?

These custom instructions then will apply to all future chat prompt sessions (not previous or existing ones), allowing you to make somewhat permanent settings that don’t have to be constantly reset. Custom Prompt instructions are short and generally limited to about 1500 characters, so keep it precise and concise.

What would you like ChatGPT to know about you to provide better responses?

This section focuses on ensuring that responses match your personal style, tone, expertise level, and background that should be reflected in the prompt responses. The best way to use this is to craft a unique voice? and ensure that the system doesn’t forget your settings between different chat prompt sessions.?

For example, you can tell the LLM that “I’m a professional working with project managers and other business and technical implementers of AI, so assume that my audience will be somewhat knowledgeable on the topic of AI and generative AI, and very knowledgeable on topics of project management”

How would you like ChatGPT to respond?

With custom responses, you can ensure consistent results with custom prompt responses, and set expectations for the type of output, your goals, or even format of the output

For example, you can tell the LLM to “Ask clarifying questions that will help you generate a better response before starting. If the questions will not change your output, then respond with the output”.

You can also use Custom Prompt instructions to specify negative prompts: those things you never want to see in any LLM responses.

For example, “Never use any first-person pronouns in your responses. Always provide reference sources.”

? Stay subscribed for the part 4 in our series next week where we explore another best practice in prompt engineering:?

? NEXT UP IN PART FOUR: We’ll be discussing Using Plugins to enhance the LLM's capabilities beyond its base functions.

?? In Case you Missed it… Insights from Cognilytica Podcasts & Content

• ?? {Featured Forbes Article} What Are The Real Costs Of AI Projects? When you're trying to run and manage AI projects, there's a lot that needs to be considered in terms of determining project budgets and cost. What are the real costs of running AI projects?? [Read here]
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• ?? {Featured Podcast} AI’s impact in the practice of medicine: Interview with Dr. Jag Singh, Mass General Brigham? - AI’s impact is helping to reshape the practice of medicine both now, and in the future. In this episode of the AI Today podcast we interview Dr. Jag Singh. He is a Professor of Medicine at Harvard Medical School, focusing on the application of AI in the practice of medicine. He is also a practicing cardiologist at Mass General Brigham (MGB). [Listen here]
• ?? {Featured Podcast} How AI will Re-imagine Air Travel: Interview with Bernadette Berger, Alaska Airlines - AI is transforming the aviation industry and passenger experience in some profound ways. In this episode of the AI Today podcast we interview Bernadette Berger, who is Director of Innovation at Alaska Airlines as she shares with us how AI will reimagine air travel and the airport experience. [Listen here]

?? The Most Important AI Stories from the Past Week You Should Know:

• {AI Strategic Plans} - Canadian PM announces $2.4 billion for AI-related investments - Canadian Prime Minister Justin Trudeau announced Canada will be setting aside $2.4 billion in its upcoming budget to build capacity in AI. The investment will be divided between a number of measures aimed to advance job growth in the AI and tech industry, but it appears the majority (about $2B) is going into a fund that will provide access to computing capabilities and technical infrastructure. [Read More]
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• ??? {AI Regulation} -? Washington state judge blocks use of AI-enhanced video as evidence in possible first-of-its-kind ruling - A Washington state judge overseeing a triple murder case barred the use of video enhanced by AI as evidence in a ruling. The ruling comes as AI and its uses — including the proliferation of deepfakes on social media and in political campaigns — quickly evolve. Will we see the use (or banning) of AI continue to play out in the courts? [Read More]
• ?? {AI Applications} - Insurance companies rely on aerial images to ditch risky properties - Insurance companies are leveraging aerial images of homes to drop properties deemed too risky. AI models scrutinize the images looking for underwriting hazards, such as “damaged roof shingles, yard debris, overhanging tree branches or undeclared swimming pools or trampolines.” Have insurers gone too far with AI-powered surveillance? [Read More]
• ?? {Autonomous Pattern} - Apple Lays Off Workers After Canceling Car Project - The autonomous pattern of AI continues to be the hardest pattern to implement.? Apple had axed its decadelong plan to build a self-driving electric car and is laying off over 600 workers. Have we reached peak Autonomous Vehicle? [Read More]
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?? Events and Opportunities to Hear from Cognilytica

• April 17, 2024: PMI New York City Chapter “How to Run Successful AI Projects and Avoid Failure” Virtual / Online session, 6-7pm EST [Register here]
• April 18, 2024: FORUM: Women Making an IMPACT, Empowering Women in AI - virtual/ webinar, 1pm EST [Register here]
• April 23, 2024: PMI Tulsa, OK Chapter: “The Hidden Secret of AI Success: A PMI Approach” Virtual / Online session 12:00-1:00pm CST [Register here]
• April 29, 2024: PMI Saudi Arabia Chapter: “How to Run Successful AI Projects and Avoid Failure”, Virtual / Online session -? 7PM-8PM Saudi Time (10AM-11AM Eastern Time) [Register here]
• May 2, 2024: PMI Austin, TX Chapter: “The Future is Now:? Essential AI Skills Every Project Manager Must Have”, Professional Development Day 2024, In-person presentation, 7:30am - 16:00pm CT ?[Register here]
• May 7, 2024: PMI Delaware Valley Chapter: “How to Run Successful AI Projects and Avoid Failure”, Virtual / Online session -? 6:30PM-8PM Eastern Time [Registration opening soon]
• May 8, 2024: PMI Southwest Ohio Chapter: “How to Run Successful AI Projects and Avoid Failure”, Virtual / Online session, 6:30-7:30pm Eastern Time [Register here]
• May 15, 2024: Designing Maryland's AI Future Summit, 8:30am-4:30pm, Fort Washington, MD [Registration opening soon]
• May 21, 2024: PMI New Jersey Chapter: “What you need to know, today, to successfully run and manage AI projects”, Virtual / Online session -? 6:30PM-8PM Eastern Time [Registration opening soon]
• July 10, 2024: PMI Madrid, Spain Chapter: “Best Practice Methods for Successful AI Projects”, Virtual / Online session - 7:00 - 8:00 PM Spanish time? [Registration opening soon]
• July 10th, 2024: PMI San Francisco Chapter: “Successful approaches to running AI Projects - Avoiding the Top Reasons why AI Projects Fail”, Virtual / Online session -? 6-7:30 pm PST [Registration opening soon]
• July 17, 2024: PMI Northern Alberta Chapter: “The hidden secret of AI success: a PM approach” Virtual / Online session? 6-8pm MT [Registration opening soon]

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