Minimum Viable Product
The simplest version of a product that can be released to test a core hypothesis with real users. An MVP delivers just enough functionality to gather validated learning while minimizing development time and cost.
A Minimum Viable Product is not a half-built product. It is a deliberate experiment designed to answer the riskiest question about your idea with the least effort possible. The goal is learning, not launching a polished experience. Teams that misunderstand this often over-build, delaying the feedback they need to make informed decisions.
For AI products, the MVP concept is critical because training models and building ML pipelines can be expensive. Before investing in custom models, teams should test whether the core value proposition resonates using simpler approaches: rule-based systems, manual processes behind an interface, or off-the-shelf APIs. If users engage with a Wizard-of-Oz prototype where humans simulate AI responses, that validates demand before any model work begins. Growth teams benefit from shipping MVPs quickly because they generate real usage data that informs both product direction and model training priorities.
Related Terms
Product-Market Fit
The degree to which a product satisfies strong market demand. Achieving product-market fit means customers are actively seeking, using, and recommending your product because it solves a real and pressing problem for them.
Jobs to Be Done
A framework that defines customer needs as functional, emotional, and social jobs people hire products to accomplish. It shifts focus from demographic segments to the underlying progress customers are trying to make in specific circumstances.
Minimum Lovable Product
An evolution of the MVP concept that emphasizes delivering enough quality and delight that early users genuinely love the product. It balances speed-to-market with the emotional engagement needed to drive organic word-of-mouth growth.
Design Sprint
A five-day structured process for rapidly prototyping and testing ideas with real users. Developed at Google Ventures, it compresses months of debate into a focused week of mapping, sketching, deciding, prototyping, and testing.
Lean Startup
A methodology for developing businesses and products through validated learning, rapid experimentation, and iterative releases. It emphasizes reducing waste by testing assumptions before building fully-featured solutions.
Build-Measure-Learn
The core feedback loop of the Lean Startup methodology. Teams build a small experiment, measure how users respond with quantitative and qualitative data, then learn whether to iterate, pivot, or scale the approach.