Article
5 Prompt Engineering Patterns Every Beginner Should Know
By Dr. Adaeze Nwosu
Getting consistently useful output from a language model is less about luck and more about structure. These five patterns cover the majority of everyday prompting situations, from quick one-off questions to multi-step research tasks.
1. Role Prompting
Assigning the model a specific role or persona focuses its tone, vocabulary and level of detail, which is especially useful for technical or professional writing tasks.
2. Few-Shot Examples
Providing two or three examples of the input/output pattern you want dramatically improves consistency, particularly for structured or repetitive tasks.
3. Chain-of-Thought
Asking the model to reason step by step before giving a final answer tends to improve accuracy on tasks involving logic, math or multi-part decisions.
4. Constraint Stacking
Explicit constraints on length, format and tone reduce back-and-forth revisions and get you closer to a usable first draft.
5. Iterative Refinement
Treat your first prompt as a draft. Refining based on the model's output is often faster than trying to write the perfect prompt up front.
These patterns are covered in much greater depth, with 40+ worked examples, in Prompt Engineering for Beginners.