PrinciplesPrompt

Principlesprompt is a design approach in prompt engineering that involves embedding explicit guiding principles within prompts to influence the behavior of language models. It supplements task-specific instructions with a concise set of norms or rules intended to steer outputs toward desirable properties, such as accuracy, safety, privacy, fairness, transparency, and accountability.

A typical PrinciplesPrompt comprises two elements: a principle set and a task instruction. The principle set enumerates the aims and constraints the model should follow, often with priority or conditional guidance. The task instruction then directs the model to perform the requested operation while adhering to those principles. This structure aims to improve alignment between model output and organizational values or regulatory requirements.

Applications and use cases include high-stakes domains such as healthcare, finance, education, and content moderation, where adherence to ethical and legal norms is important. PrinciplesPrompt can support auditability by making the governing rules explicit in the prompt and, in some implementations, in prompt logs or workflow metadata.

Evaluation typically involves assessing fidelity to the stated principles, using human judgments, automated checks, or specialized red-teaming. Important considerations include versioning of principle sets, handling conflicts among principles, and ensuring the approach generalizes across domains without overly constraining creativity or performance.

Relationship to related concepts includes alignment, policy prompts, and rule-based prompting. Principlesprompt is distinguished by the explicit, enumerated principle framework it imposes on the model’s outputs.