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Prompt structure

Prompt structure is the organization of a prompt’s content and instructions to guide a model’s response or generation.

How 2 Manning books explain it

Grokking AI Applications

The organization of a prompt into clearly distinguishable parts that a language model can parse.

How it is used
Structures prompts so language models can distinguish roles, tasks, features, examples, and input.
How deep it goes
Explains a four-part template and the rationale for specifying a role, with examples supporting practical use.
Examples
Uses translation formatting, a marketing-manager role, and a four-part standard template.
What you can do after
Apply prompt structure by composing requests with explicit roles, tasks, features, examples, and recognizable inputs.

Read how Grokking AI Applications explains prompt structure →

Data Storytelling with Altair and AI

Prompt structure is the organization of descriptive instructions that specify the intended content and visual characteristics of a generated image.

How it is used
Structures instructions for directing ChatGPT responses and generated images toward a defined purpose or visual result.
How deep it goes
Defines reusable prompt parts, demonstrates style variation, and recommends iterative refinement without pursuing advanced prompt-engineering detail.
Examples
Uses examiner prompts, scenario questions, and contrasting digital-art and black-and-white-photograph image descriptions.
What you can do after
Apply it via ChatGPT or DALL-E by specifying structure, testing outputs, and refining prompts.

Read how Data Storytelling with Altair and AI explains prompt structure →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.