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Technology-first thinking

As explained in The Art of AI Product Development

Technology-first thinking is an opportunity-discovery approach that begins by considering what newly available technologies make possible.

Technology-first thinking discovers opportunities by asking what newly available technologies make possible, rather than relying only on customers to articulate their needs. It broadens ideation through product sense, domain expertise, internal crowdsourcing, and fast validation. section 2.1.2

Use the approach to:

  • Generate hypotheses from experience, market dynamics, and emerging capabilities. section 2.1.2
  • Invite domain experts and colleagues to suggest opportunities beyond the immediate product team. section 2.1.2
  • Test promising ideas directly instead of demanding complete data or certainty before experimentation. section 2.1.2

From capability to experiment

After adding a chatbot to financial analytics software, a UX team can test prompt suggestions and other interface changes that help users formulate better questions. section 2.1.2

How The Art of AI Product Development covers it

How deep it goes
Defines the approach and outlines idea sources and rapid validation, but stops short of a detailed discovery workflow.
Examples
Uses a financial analytics chatbot, prompt suggestions, UX changes, and predictive personalization as opportunity-discovery examples.
What you can do after
Apply it via small, testable product hypotheses without waiting for complete up-front data.
How it connects
Connects opportunity discovery with product sense, domain expertise, internal crowdsourcing, 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.