Prompting Principles
Prompting is an interface contract. The model has no access to your hidden requirements, your domain context, or your acceptance criteria. If the prompt leaves degrees of freedom, the model will fill them implicitly.
These principles make that contract explicit by tightening objectives, supplying material information, prescribing method, validating quality, and standardizing representation. They are designed for reliable use in production workflows.
Objective Framing Principle
Specify the objective and remove degrees of freedom so the model does not resolve ambiguity or underspecification by default.
Information Supply Principle
Supply the information that materially shapes the outcome and avoid information that mainly adds noise.
Method Prescription Principle
Prescribe how the model should proceed — steps, checkpoints, comparisons, intermediate artifacts — so the path to the result is shaped deliberately.
Quality Validation Principle
Make uncertainty visible, expose assumptions, and validate output against correctness and constraints before relying on it.
Output Representation Principle
Make the intended use of the response explicit so the output is an artifact with stable structure and predictable fields, not free-form prose.
Iterative Alignment Principle
Use each response as feedback; adjust objective, information, method, validation, or representation across turns until the result is fit for use.
These principles are general rules, similar in spirit to SOLID in software design. They describe forces in human model interaction, not fixed prompt templates. The patterns in the book are the concrete, reusable prompt designs that apply these principles across tasks and contexts.