This course introduces students to prompt engineering — the practice of effectively communicating with generative AI systems such as ChatGPT, Claude, and Gemini. Students will learn how large language models function, how to design structured prompts, and how to apply AI tools to business, marketing, and research contexts.
The course emphasizes hands-on experimentation, critical evaluation of AI outputs, and ethical AI use. Students will leave with practical skills for integrating AI into workflows while maintaining human judgment and accountability.
By the end of the course, students will be able to:
This course includes lectures, live demonstrations, hands-on exercises, and applied projects. Students are expected to actively engage with AI tools during and outside of class.
| Assignment | Weight |
|---|---|
| Prompt Experiment Log | 20% |
| Reverse Engineering Assignment | 10% |
| AI Output Evaluation | 15% |
| Midterm Applied Project | 20% |
| AI Workflow Assignment | 10% |
| Final Project Portfolio | 25% |
| Participation | 10% |
Students will maintain a weekly log documenting their prompt experiments. Each entry must include the prompt used, the intended goal, the AI output, an evaluation of effectiveness, and a revised prompt.
Submission: Weekly entries + final compiled portfolio
Students will analyze high-quality AI outputs and infer the prompts that likely generated them — reconstructing the original prompt, identifying techniques used (role, constraints, examples), and improving the prompt.
Submission: 2–3 page analysis
Students will generate AI content and critically evaluate it for accuracy (fact-checking required), bias, missing information, and hallucinations. Students will revise their prompt to improve results.
Submission: 3–4 page report with original and improved outputs
Students will apply prompt engineering to a real-world task such as marketing campaign development, research synthesis, or customer analysis. Students must document prompt iterations and evaluate results.
Submission: 5–7 page report + prompts
Students will design a multi-step prompt workflow (e.g., idea generation → filtering → expansion → final output).
Submission: Workflow diagram + prompts + 2-page reflection
Students will create a portfolio demonstrating mastery of prompt engineering, including at least 5 applications, iterative prompt development, evaluation of outputs, and a real-world use case.
Submission: Portfolio + optional presentation
Includes in-class exercises, peer feedback, and discussion participation.
Ten sessions over two weeks. Each 75-minute session: 20 min lecture, 35 min live lab, 20 min debrief.
| Session | Topic | Focus |
|---|---|---|
| D1 | What Is This Thing, Actually? | Demystify LLMs without the math. Compare AI vs. search vs. intelligence. |
| D2 | Anatomy of a Prompt | The four elements every effective prompt contains: Role, Task, Context, Format. |
| D3 | Role Prompting & Persona Assignment | Put AI in the right seat before asking it to drive. The panel of advisors technique. |
| D4 | Few-Shot Prompting | Show AI what you want instead of just telling it. Zero-shot vs. few-shot. |
| D5 | Iteration — The Most Important Skill | The CRISP framework. Chain-of-thought prompting. Making AI show its work. |
| Session | Topic | Focus |
|---|---|---|
| D6 | Prompting for Research & Analysis | AI as research partner, not source. Synthesis, comparison, hallucination detection. |
| D7 | Prompting for Writing & Communication | AI as editor vs. ghostwriter. Voice injection. Emails, memos, pitches. |
| D8 | Prompting for Decision Support | SWOT, risk analysis, pre-mortem. Use AI to think better, not instead of you. |
| D9 | Ethics, Limits & Responsibility | What AI cannot do. Hallucinations, bias, academic and professional integrity. |
| D10 | Capstone — Prompt Portfolio | 5 prompts for 5 real business scenarios. Peer review. Portfolio presentations. |
Use of AI is required in this course. However:
All work must comply with WSU academic integrity policies. Misuse of AI (e.g., submitting unverified or deceptive work) will be treated as academic misconduct.
Students requiring accommodations should contact the Access Center at accesscenter.wsu.edu and inform the instructor as early as possible.