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Minimal product

As explained in The Art of AI Product Development

A minimum viable product is a product version containing enough functionality to deliver value and test assumptions with real users.

A minimal product, or MVP, contains enough functionality to deliver value and test assumptions with real users. It creates a focused starting point rather than trying to solve every need at once. section 2.1.2

Use the MVP as a learning boundary:

  • Start with a real need you understand directly, but do not dogfood indefinitely; personal use can bias the product toward your own needs. section 2.1.2
  • Show the initial product to external users so it can become more scalable and representative. section 2.1.2
  • Compare customer requests with behavior data, because stated intentions may differ from actual usage. section 2.1.2

From personal need to external validation

Alex, a blogger, builds an AI app for his own content-generation needs, then works with design partners to identify problems with the initial MVP. section 2.1.2

How The Art of AI Product Development covers it

How deep it goes
Explains scope, timing, and bias risks, but stops short of implementation details or a formal prioritization framework.
Examples
Uses an AI content-generation app, blogger Alex, design partners, and an AI-assisted language-learning app.
What you can do after
Apply it via building an initial product, testing it with external users, and iterating from feedback and observed behavior.
How it connects
Connects dogfooding with external users, customer feedback, design partners, and behavior data.

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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.