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Adaptive prompting

As explained in Introduction to Generative AI, Second Edition

Adaptive prompting is a technique in which a model dynamically modifies or expands its prompts as task information changes.

Adaptive prompting is a technique in which a model modifies or expands its prompts as task information changes. Instead of relying on one fixed instruction, the system asks clarifying questions, refines its goals, and creates subquestions during a multistep interaction. section 7.6

Travel planning

A travel-planning agent may begin with “Where would you like to go?” After a vague answer such as “somewhere warm,” it can ask about budget, activities, and travel constraints before producing tailored results. section 7.6

The technique makes prompting an evolving interaction rather than a one-time input. It helps the model construct relevant context, although the description remains conceptual and does not specify implementation details or guarantees of reliability. section 7.6

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Defines dynamic prompt modification and illustrates it with travel planning, but stops short of implementation details.
Examples
Uses a travel-planning agent that asks about destination, budget, activities, and travel constraints.
What it assumes
Builds on basic prompt-engineering practice while avoiding any stated requirement for deep technical expertise.
What you can do after
Apply adaptive prompting to structure interactions that clarify vague requests and produce tailored subquestions.
How it connects
Connects prompt engineering with multistep tasks, clarifying questions, and evolving goals.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Introduction to Generative AI, Second Edition. The section links point to the parts of the book it draws on.