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Intention

As explained in The Art of AI Product Development

A user’s underlying goal or requested task expressed through an interaction.

Intention is the goal behind a user’s request. For an AI product, recognizing user intent means responding to the task in context—not merely producing fluent language. Defining supported intents helps align model behavior and the interface with actual user needs. section 1.1 section 5.1.3

Intent boundaries shape both the product and its safeguards:

  • Gather real user questions and test whether the model handles the tasks it is meant to support. section 1.1
  • Guide users toward supported requests with prompt templates, suggestions, or fixed question types; expect some requests to be complex, off topic, or misleading. section 1.1
  • Set guardrails for requests the product should not fulfill, such as unauthorized investment advice. section 1.1

A request with a clear intent

“Shorten the product description and make it more playful” asks for a specific transformation. A later request to turn it into a formal press release changes the intended output and style. section 5.1.3

How The Art of AI Product Development covers it

How deep it goes
Explains intent through product decisions and examples, but does not detail technical intent-detection methods.
Examples
Uses chatbot question guidance, unauthorized investment-advice requests, and product-description rewrites.
What it assumes
Distinguishes broad pretrained language knowledge from understanding intent and context, without requiring technical background.
What you can do after
Apply intent boundaries by testing real user questions and steering requests toward supported tasks.
How it connects
Connects user intent to language models, pretraining, fine-tuning, and guardrails.

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Related concepts

This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.