MVP vs. Prototype vs. Proof of Concept: Understanding the Differences

When developing new products or features, teams often use different approaches to test ideas and validate assumptions. Three common methods—MVPs, prototypes, and proofs of concept—are frequently confused despite serving distinct purposes. Understanding these differences is crucial for choosing the right approach for your project.

Proof of Concept (POC)

A proof of concept is primarily a technical experiment designed to verify that a specific concept or theory can be implemented in practice. It answers the fundamental question: “Can this actually be built?” Unlike prototypes or MVPs, POCs are usually created for internal development teams and stakeholders rather than end users. The focus is strictly on demonstrating technical feasibility, not usability or market appeal.

For example, before investing resources into developing a complex AI recommendation engine, a team might create a POC to demonstrate that their algorithm can effectively analyze user behavior and deliver relevant suggestions with the data available. The POC might not have a user interface at all—instead, it would focus on proving that the core algorithmic challenge can be solved.

You should consider using a POC when exploring cutting-edge technology with uncertain feasibility or when validating that a technical approach can meet specific performance requirements. POCs are particularly valuable before making significant resource commitments to development, especially when stakeholders need evidence that a technical challenge can be overcome.

Common pitfalls with POCs include allowing scope to expand beyond the core technical question, mistaking a successful POC for a production-ready solution, and failing to document learnings and technical constraints discovered during the process. A POC should have a clear, narrow focus on answering specific technical questions.

Prototype

A prototype is a preliminary model of a product used to explore design concepts and test user experience. It answers the question: “How will this work for users?” Unlike POCs, prototypes are specifically designed to be tested with users, focusing on interaction patterns, visual design, and user flows rather than technical implementation details.

For a mobile banking app, a prototype might showcase the user flows for common tasks like transferring money or checking balances, allowing designers to test whether users can intuitively navigate these processes. The prototype might not connect to actual banking systems—it simulates these interactions to gather feedback on the experience.

Prototypes come in various fidelities. Low-fidelity prototypes include paper sketches, wireframes, or simple clickable mockups that focus on layout and information architecture. Medium-fidelity prototypes offer more detailed representations with some visual design elements and basic interactions. High-fidelity prototypes present near-final visual designs with comprehensive interactions that closely resemble the final product.

Several prototyping methods exist to suit different needs. Wizard of Oz prototyping involves human operators simulating complex functionality behind a user interface. Role-playing prototypes have team members act out interactions to simulate product experiences. Concierge prototyping manually delivers a service that will eventually be automated. Digital prototyping tools like Figma, Adobe XD, or InVision help create interactive digital experiences.

The key value of prototyping lies in its ability to generate user feedback early, before significant development resources are committed. This feedback can drastically reshape a product concept, potentially saving months of misguided development work.

Minimum Viable Product (MVP)

An MVP is a functional product with just enough features to satisfy early customers and provide feedback for future development. It answers the question: “Will people use and value this product?” Unlike POCs and prototypes, an MVP is a complete, usable product that is released to actual customers and generates real usage data and metrics.

The first version of Dropbox serves as a classic MVP example. It offered basic file storage and syncing capabilities, lacking many features now considered standard but delivering on its core promise of seamless file synchronization across devices. By focusing solely on this core value proposition, Dropbox could validate market demand before investing in additional features.

Several misconceptions exist about MVPs. Some believe an MVP should include minimal functionality, but the reality is that an MVP should include minimal, but complete, functionality to deliver value. Another myth suggests an MVP can be low quality, but while feature-lean, an MVP should be production-quality for the features it does include.

Teams approach MVPs in various ways. A concierge MVP involves manually providing a service to understand user needs before automating. A piecemeal MVP combines existing tools and services to deliver value before building custom solutions. Single-feature MVPs focus on delivering one core feature exceptionally well. Wizard of Oz MVPs use human operators behind the scenes while presenting an automated interface to users.

The primary purpose of an MVP is to start the build-measure-learn feedback loop as quickly as possible. By getting a real product into users’ hands, teams can gather authentic feedback about what works, what doesn’t, and what should be prioritized next.

The Development Continuum

These approaches often exist on a continuum in the product development lifecycle. Many successful products evolve through all three stages: starting with initial concept exploration using a POC to validate technical feasibility, moving through user experience design with multiple iterations of prototypes, then proceeding to market testing with an MVP launch, and finally scaling the product with incremental feature additions based on user feedback.

Each approach addresses different types of risk. POCs reduce technical risk by validating feasibility. Prototypes reduce usability risk by validating design concepts. MVPs reduce market risk by validating demand with real users. By understanding which risk is most pressing at each stage of development, teams can choose the appropriate tool.

Measuring Success

Success metrics differ for each approach. For POCs, success means demonstrating technical feasibility, identifying constraints and limitations, and providing clear data on performance metrics. For prototypes, success is measured by whether users understand how to use the interface, if it effectively communicates the value proposition, and if it generates actionable design insights. For MVPs, success depends on user adoption and retention, the quality of feedback for future iterations, and validation of key business model assumptions.

Industry Examples

Airbnb’s journey illustrates these distinctions well. Their POC tested if people would book stays in strangers’ homes, investigating the technical and logistical feasibility. Their prototype included early website mockups showing listings and booking flows, focusing on the user experience. Their MVP was a basic platform allowing hosts to list spaces and travelers to book them—a complete but minimal product that validated market demand.

Spotify followed a similar path. Their POC validated streaming technology and licensing frameworks, solving technical challenges. Their prototype developed user interface designs for browsing and playing music, focusing on experience. Their MVP was a desktop-only application with basic streaming functionality that proved market value.

Tesla’s Model S development also reflects this progression. Their POC validated battery and electric motor technology, overcoming technical hurdles. Their prototypes included design concepts and drivable concept cars, refining the experience. Their MVP was the first production model with limited features compared to later versions but demonstrating the core value proposition.

By clearly understanding these distinctions, product teams can choose the right tool for each stage of development, communicate more effectively about goals and expectations, and maximize learning while minimizing wasted resources. Recognizing when to use each approach—and when to transition from one to the next—is a crucial skill for successful product development.