Prompt Engineering for Non-Developers

The Challenge

Prompt engineering is quickly becoming an important skill for non-technical professionals, but much of the existing documentation is overly technical, informal, or inconsistent.

My challenge was to create clear, practical guidance that helps non-technical users improve AI output by writing more effective prompts.

My Role

This was an individual project that I researched, wrote, edited, and designed.

Audience

The primary audience for this guide was non-developer knowledge workers who use generative AI tools but lack experience in programming or machine learning. The audience analysis identified several common needs and concerns.

• Limited or no understanding of how LLMs work
• A desire for immediate, practical guidance rather than technical explanations
• Frustration with inconsistent or low-quality AI outputs
• Concerns about using AI responsibly and appropriately in professional contexts

Approach

Using a writer-centered analysis worksheet, I identified the professional roles of my primary, secondary, tertiary, and gatekeeper readers. I then used a reader analysis worksheet to document each group’s needs, values, attitudes, and the contexts in which they would use the deliverable. I defined the content scope by outlining the desired outcomes of the guide for primary readers.

Result

The final deliverable provides jargon-free, practical instruction rather than technical theory. It includes clear, step-by-step techniques that can be applied immediately, a simple framework for constructing effective prompts, and examples that mirror real workplace tasks.