Discovery Prototype Selectionv1.0.0

A team wants to add a recommendation engine to their e-commerce app but is unsure if the data pipeline can support real-time inference. They use a feasibility spike to prototype the ML model and data flow, confirming technical viability before committing to full development.

A SaaS product team has designed a simplified onboarding flow and needs to validate that users can complete key tasks. They build a high-fidelity clickable prototype (user prototype) to observe 15 users interacting with the interface and identify friction points.

A fintech startup wants to build a real-time spending analytics dashboard but is unsure about the performance of their existing data infrastructure. They create a live-data prototype using a subset of customers to test query speed and data accuracy before building the full product.

A healthcare company is exploring an AI-powered symptom checker. They simulate the AI by having a human behind the scenes respond to user inputs (Wizard of Oz prototype) to gauge user trust and willingness to share health data before investing in the actual NLP model.

A product manager needs to get buy-in from executives on a new mobile app feature. They create a low-fidelity paper prototype and walk stakeholders through the flow during a review meeting, using shared understanding to align on priorities without costly implementation.

A software company uses prototypes to validate new features before adding them to the product roadmap. By testing feasibility and usability early, they reduce development waste and accelerate time-to-market for features that drive subscription renewals.

An online marketplace uses live-data prototypes to test new search algorithms and recommendation systems. Early validation ensures that only technically feasible and user-accepted changes go into production, improving conversion rates and average order value.

A B2B platform leverages Wizard of Oz and high-fidelity prototypes during enterprise sales to demonstrate a product vision that doesn't yet exist. This simulates the value proposition, secures early commitments, and de-risks custom development investments.