About This Website
Welcome, Fellow Prompt Crafters!
Let's craft the perfect prompt! I'm Polly, your feathered guide
through this course, and I'm thrilled you're here! You'll see me
pop up throughout the chapters — I'll welcome you to new topics,
share tips I've picked up along the way, help you think through
tricky concepts, warn you about common misunderstandings before
they trip you up, encourage you when things get tough, and
celebrate your successes when it all clicks. Think of me as
the friend who's already taken the course and saved you a seat.
Let's do this, word wizards!
I have always been fascinated with language. I got my first exposure to language tools when I discovered WordNet in the late 1990s. It was amazing to see a formal database representations of words I used every day. Leveraging WordNet for writing and search was opened a new door for me. This helped me formalize my ability to visualize how to represent concepts in a graph.
I first started using generative AI seriously when OpenAI release their first tools in 2020. I had been using BERT to analize clinical documents, and now there was another model that would not only fill in a single word, but it would continually guess a set of next words.
Back then it was just GPT-2.
But it still had potential. I started blogging about
GPT-3 in September of 2020
as a way to Generate Detailed Lesson Plans for my STEM students.
Although my peer group of graph and NLP researchers were interested in using these models for task automation, we found that by adding detiled examples of what we wanted we could dramatically increase the quality of prompts. So I started teaching informal one-hour sessions on how to us GPT to perform various tasks that we had formally done by builing custom BERT models.
The more we worked with GPT-3 the more we realized the incredible number of tasks that this single model could do. The demmand for the class continued and I launched both a half-day and eventually a full-day of training for developers. These were often the most popular classes that were offerend by our training group.
Since those early days, the power of generative AI has continued to expand. But the role of writing good prompts is still critical for you to get the most out of your models.
Why a Parrot?
You might have heard that LLMs are called "stochastic parrots" — they
just predict the next word based on patterns, without truly understanding
meaning. So naturally, who better to teach you prompt engineering than
an actual parrot? The difference is, I choose to repeat myself.
The LLMs can't help it.
I hope that you find this course useful and I would appreciate any feedback you have to help me make the course better.
About Dan McCreary
Dan McCreary is a semi-retired AI researcher, solution architect, and educator who has spent more than three decades helping Fortune 100 organizations reason over massive datasets. At Optum he founded the Generative AI Center of Excellence and led the team that built one of the world's largest healthcare knowledge graphs — spanning over 25 billion vertices — to unify member, provider, and patient insights. During his tenure at Optum Dan taught over 3,000 engineers how to model healthcare data using graph databases. Dan's deep background in knowledge representation and systems thinking underpins the precise learning graphs and intelligent textbook workflows used throughout this course.
He is the co-author of Making Sense of NoSQL (Manning Publications), the founding chair of the NoSQL Now! conference, and a frequent keynote speaker on semantic search, ontology strategy, and AI hardware. Beyond industry, Dan has mentored students as a STEM volunteer since 2014 and now applies the same rigor to building open educational resources. You can visit the Intelligent Textbooks Case Studies to see over 70 textbooks that Dan has created or co-created with other authors.
Selected Credentials
- B.A. in Physics and Computer Science from Carleton College
- M.S.E.E. from the University of Minnesota
- MBA coursework at the University of St. Thomas (33 of 36 credits complete)
- Patent holder in semantic search and ontology management techniques
- Advocate for large-scale Enterprise Knowledge Graph adoption across healthcare and education
- Long-time promoter of accessible, low-cost AI-powered learning experiences
How to Cite This Book
If you reference this course in academic work, presentations, or other publications, please use the following citation:
McCreary, D. (2026). Prompt Engineering: A Hands-On Course for Writing Effective AI Prompts. Retrieved from https://dmccreary.github.io/prompt-class
BibTeX:
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