Cognilytica Insights
This week we share the final part of our 6 part newsletter on Prompt Engineering Best Practices. Make sure to check out part 1, part 2, part 3, part 4, part 5 if you haven’t already!
Prompt Engineering Best Practice #6: “The Soft Skills of Prompt Engineering”
??? Generative AI is one of the most accessible forms of AI currently available. While in the past, you might have used AI without knowing it, you can use Generative AI purposefully in ways that have immediate and dramatic impact on your daily life.
The great thing about Generative AI, is that it doesn’t require “hard skills”: programming, math, analytics skills, database or data engineering skills, or anything else that requires specific education and years of training. You don’t need to be an expert in math skills such as Statistics & Probability, Calculus or Linear Algebra to get value from using Generative AI. You also don’t need to be skilled in using different Data Visualization tools. Nor do you need to have knowledge of different algorithms & modeling skills.?
The only time you need those skills is if you are building programs that interact with Generative AI systems through APIs. But you don’t need to do that to get value from Generative AI. This is what makes prompt engineering so approachable.?
??? Rather, we can use our existing “soft skills” of communication, planning, creativity, and interaction to get what we want out of Generative AI. No surprise, soft skills are incredibly important when it comes to effective prompting, since hard skills aren’t used at all when creating prompts that interact with Generative AI systems.?
What sort of soft skills are needed to become effective and excel at prompt engineering?
- ?? Creativity: Being able to think about the art of the possible when it comes to generative AI helps you seek advice from others, be influenced by others and how they have written prompts and used GenAI to help them with various tasks. Creativity and a curious mind are some of the most important aspects of prompt engineering, since the art of the possible with prompts is only limited by your imagination in how you interact with the LLM.
- ?Problem solving: Prompt outputs will likely not be exactly what you want the first time. Prompt iteration often requires identifying what is missing or ambiguous in AI responses and refining your prompt until you get your desired output. Problem solving skills are beneficial for creatively overcoming challenges such as unexpected AI behavior or hallucinations.
- ??Adaptability: The ability to quickly adapt prompts based on your organization’s changing needs, changing project conditions, or unexpected answers is vital. Being able to adapt helps in managing projects where AI integration is critical, ensuring that outputs remain relevant and useful despite shifting project parameters or data.
- ?? Critical Thinking: Using critical thinking to iteratively refine prompts helps in honing in on more effective questions or prompt patterns that lead to clearer, more accurate results. The ability to analyze complex situations and make informed decisions helps in designing effective prompts and assessing the quality of AI-generated responses.
- ?? Communication: Being an effective communicator is critical for crafting effective prompts. Providing the prompt with precise and unambiguous language helps ensure relevant and accurate outputs. Effective communication also involves interpreting AI responses and refining prompts based on those responses.
- ?? Collaboration: Don’t be afraid to ask for help and seek feedback from peers and colleagues. Getting perspectives from others can help you better refine your prompts, come up with new and innovative ideas, and ways to use and word prompts you never thought of. Collaboration can also help you stay up to date on the latest prompting best practices.
Embrace Continuous Experimentation and Learningnbsp;
When it comes to prompt engineering, there's no such thing as failure, there’s only experimenting, trial, and error. LLM-powered Generative AI solutions are tools that can enhance and expedite your tasks. Try various strategies without fear of repercussions. Don’t be afraid to come up with crazy ideas and test them out in the LLM. Most of the time, your prompts are private unless you share them, so you have the freedom to experiment and try without fear of ridicule or failure.?
You should also develop expertise in prompt engineering through continuous practice and sharing what you have learned with others. Keep practicing and pushing your boundaries to get out of your comfort zone. Utilize your soft skills to continuously refine and hone your prompt engineering skills so you can really use LLMs as an augmented intelligence tool.?
Putting the Best Practices of Prompt Engineering into Practice
Throughout this prompt engineering best practices newsletter series you’ve learned a number of key skills, best practices and techniques for prompt engineering. You are well on your way to prompt engineering success. There is really no penalty for failure, just rewards for success. So keep practicing prompting.
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?? In Case you Missed it… Insights from Cognilytica Podcasts amp; Content
- ?? {Featured Forbes Article} Understanding The Layers Of Trustworthy AI- In the push to make AI systems more ethical and trustworthy, organizations are realizing the broad scope of things to consider under the umbrella of Trustworthy AI. [Read here]
- ?? {Featured Forbes Article} What Are The ROI Metrics For AI Projects? - For AI projects to be successful, there needs to be a combination of a larger vision for AI and quick projects that allow organizations to ensure real-world value. [Read here]
- ?? {Featured Podcast} - Prompt Engineering Best Practices: Using Plugins - Plugins for Large Language Models (LLMs) are additional tools or extensions that enhance the LLM’s capabilities beyond its base functions. In this episode hosts Kathleen Walch and Ron Schmelzer discuss this topic in greater detail.? [Listen here]
- ?? {Featured Podcast} ?Prompt Engineering Best Practices: Hack and Track- Experimenting, testing, and refining your prompts are essential. A best practice is to constantly experiment, practice, and try new things using an approach called “hack and track”. This is where you use a spreadsheet or other method to track what prompts work well as you experiment. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss hack and track in detail.? [Listen here]
?? The Most Important AI Stories from the Past Week You Should Know:
- ?? {AI Investments} - SoftBank will reportedly invest nearly $1 billion in AI push, tapping Nvidia’s chips - Japanese tech conglomerate SoftBank is looking to develop a “world-class” Japanese-language-specific generative artificial intelligence model, and plans to invest $960 million in the next two years to bolster its computing facilities. [Read More]
- ??? {AI in Medicine} - AI Links Gut Microbiome to Alzheimer’s : Researchers are pioneering the use of artificial intelligence to explore how the gut microbiome influences Alzheimer’s disease. Their latest study employs AI to analyze how metabolites produced by gut bacteria interact with cellular receptors, potentially contributing to Alzheimer’s development. [Read More]
- ??? {AI Chatbots} - Meet Sunny: Denver’s AI-powered chatbot - Sunny is an AI-powered virtual assistant that can be reached through text messages or online. While some other AI-powered chatbots can have conversations related to any topic, Sunny is strictly business. Will this chatbot turn out to be as “helpful” as the bot NYC recently rolled out? [Read More]
- ?? {AI Adoption} - AI shakes up corporate boards -? The world's largest companies are increasingly obsessed with AI — mentioning it repeatedly in 2024 earnings calls — but most boards lack the expertise to effectively guide AI strategies. The pace of AI innovation is pushing executives to develop AI strategies quicker than they have for previous new technologies.? [Read More]
?? Events and Opportunities to Hear from Cognilytica
- THIS WEEK 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]
- THIS WEEK 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 [Register here]
- 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 9, 2024: Air Force Research Laboratory (AFRL): “Digital Dialogue on AI Best Practices”, Virtual / Online Private session, 12pm-1pm
- May 15, 2024: Designing Maryland's AI Future Summit, Prince George's County OIT AI Workshop, 8:30am-4:30pm, Fort Washington, MD [Register here]
- May 21, 2024: PMI New Jersey Chapter: “Successful Approaches to Running AI Projects - Avoiding the Top reasons why AI projects Fail”, Virtual / Online session -? 7PM-9PM Eastern Time [Register here]
- 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 10, 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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?? Move Forward with AI Best Practices - Training amp; Certification
Cognilytica’s AI best practices & Trustworthy training and certification continues to be in high demand. Haven’t yet enrolled in a certification or training? What’s holding you back?
- ?? CPMAI v7 - Get Certified with comprehensive AI & ML Project Management Training. Includes: AI Fundamentals, AI Applications, Managing Data for AI, Data Preparation for AI, ML Algorithms, Generative AI, CPMAI Methodology, and Trustworthy AI. [Enroll now]
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