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Product sense

As explained in The Art of AI Product Development

Product sense is the ability to recognize valuable product opportunities and make sound product decisions based on user, market, and product understanding.

Product sense is the ability to spot valuable opportunities through experience, user and domain understanding, market dynamics, and informed intuition—not customer requests alone. section 2.1.2

Use product sense to:

  • Generate hypotheses without requiring a prior data-driven argument for every idea. section 2.1.2
  • Invite domain experts and internal contributors to reveal promising directions and broaden ideation. section 2.1.2
  • Turn promising ideas into small changes that can be implemented, deployed, and tested quickly. section 2.1.2

From chatbot to better questions

A financial analytics product can test prompt suggestions and other interface nudges to help users formulate questions correctly, then validate which changes improve use. section 2.1.2

How The Art of AI Product Development covers it

How deep it goes
Combines experience, market dynamics, domain expertise, hypotheses, and rapid validation; stops short of a formal scoring method.
Examples
Uses chatbot prompt suggestions, interface changes, and predictive personalization as experimental opportunity examples.
What it assumes
Builds on experience and knowledge of users and domains while relaxing the need for prior data for every idea.
What you can do after
Apply it via small, testable prompt or interface changes, then validate hypotheses with experiments.
How it connects
Connects AI opportunities with customer research, domain expertise, product-led growth, experimentation, personalization, and conversion.

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.