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Course Description

In an era where artificial intelligence is reshaping industries at breakneck speed, the ability to effectively partner with AI tools is becoming an indispensable skill. This course, designed for the modern professional, aims to demystify AI collaboration and equip students with practical, hands-on experience in leveraging large language models like GPT for various professional tasks.

Course Philosophy: Beyond the Hype

This is not a technical class. Instead, the focus is on developing a way of thinking—a mindset that allows professionals to harness AI's potential without getting bogged down in technical minutiae. The course is built on the premise that AI collaboration can make you "100 times better" at certain tasks, a leap that's simply not achievable through traditional means alone. 

Course Themes

• Building community, developing community commitments
• Defining and exploring the differences between facilitation and teaching 
• Rethinking your teaching practice and incorporating new skills 
• Designing a facilitative activity/lesson/unit to implement with your students 
• Implement and reflect on your facilitative teaching skills and revised activity/lesson
• Practice facilitative teaching skills in a supportive community where you can give and receive feedback 

Core Concepts & Learning Outcomes

• The AI Interview Technique: Learn to extract and structure information from various sources, including your own thoughts, using AI.
• Iterative Refinement: Develop the crucial skill of giving feedback to AI and refining outputs.
• AI as a Teammate: Shift your perspective to view AI as a collaborative partner. The course explores how to "treat it like a teammate" and simulate "an entire team of agents" for complex tasks.
• Transference and Rapid Learning: Discover techniques to quickly grasp new concepts by associating them with familiar ideas.

Practical Workflows & Real-World Application

The course is structured around five "generative AI workflows," each building on the last. These practical exercises cover a range of professional scenarios, from developing marketing strategies to establishing foundational business plans.

Tools of the Trade

While the course primarily uses OpenAI's GPT models, particularly through their Playground interface, students are encouraged to explore other platforms like Google's Gemini or Anthropic's Claude. The focus is on understanding the underlying principles rather than mastering any single tool.

Ethical Considerations & Responsible Use

The course doesn't shy away from the ethical implications of AI use. Students are encouraged to think critically about issues like data privacy, bias in AI models, and the potential impact on various industries.

Assessment & Project Work

The course employs a multi-faceted assessment approach:

1. Generative AI Workflows: Practical exercises that form the backbone of the course.
2. Culminating Case Study: A culminating assignment where students apply their skills to develop an AI-assisted business concept and explore creating positioning, segmentation, messaging, and supporting materials to bring the hypothetical concept to market.

Looking to the Future

By the end of this course, students should feel confident in their ability to leverage AI as a powerful professional tool. Whether you aim to optimize your job search, streamline your workflow, or innovate within your industry, the skills learned here provide a significant edge in an AI-augmented professional landscape.

About the Instructor

Daniel Englebretson
Adjunct Instructor, Management

Daniel Englebretson is an instructor in management, teaching courses at the crossroads of AI and business in Elon University's Martha and Spencer Love School of Business. A serial entreprenuer, Daniel has founded three companies centered on AI technology and works to empower and enable individuals with the skills and mindset shifts needed to open their own door of opportunity through mastering collaboration with artificial intelligence.