Somewhere right now a team is polishing error handling on a thing no user has seen, and another team is onboarding paying customers onto a demo held together with hardcoded data. Both teams made the same mistake in opposite directions: they confused a prototype with an MVP.
The words get used interchangeably, and they should not be. They describe artifacts with different purposes, different audiences, and different definitions of success.
What a prototype is
A prototype is a question wearing the costume of a product. You build it to learn something specific: will users understand this navigation, does the pricing page make sense, is the core interaction pleasant enough that anyone would come back. It only needs to be real enough for the question to get an honest answer.
That gives prototypes a useful property: they are allowed to cheat. Fake data, one happy path, no accounts, no edge cases. Anything that does not serve the question is waste. Our guide to rapid prototyping goes deeper on how to keep that loop fast.
What an MVP is
A minimum viable product is the smallest version of your product that delivers real value to real users. The word doing the work is product. People rely on it. It stores their data, charges their cards, sends their emails. It can be narrow, even embarrassingly narrow, but within its narrow scope it has to actually work, keep working, and be something you can build on next month.
An MVP is not a rough draft of the product. It is the product, at its smallest honest size.
And a proof of concept?
The third term in the pile. A proof of concept answers "can this be done at all": will the API return what we need, can the model run fast enough, does the integration exist. It often has no interface worth showing anyone. Settle feasibility there, settle desirability with a prototype, then ship the MVP.
Side by side
| Prototype | MVP | |
|---|---|---|
| Purpose | Answer a question | Deliver value |
| Audience | Your team, test users | Real users |
| Lifespan | Days to weeks, then discard or graduate | The first version of something permanent |
| Success metric | Did we learn what we needed? | Do people use it and come back? |
What goes wrong when you confuse them
Shipping a prototype as an MVP. The demo impresses, someone says "just launch it," and now real users live on scaffolding. The hardcoded data becomes a database migration nobody planned. The single happy path meets a thousand unhappy ones. Every week of runway after that goes to stabilizing code that was never meant to hold weight, which is usually slower than building the real thing would have been.
Treating an MVP as a prototype. The opposite failure is quieter. The team decides the first release must be "real," so they build authentication, billing, admin tools, and a settings page before a single user has confirmed the core idea matters. Months pass. The launch finally answers the question a prototype could have answered in a week, and the answer is sometimes no.
How to decide which you need
Ask two questions. First: what are you trying to find out? If there is a genuine open question about what to build or whether anyone wants it, you need a prototype, and you should build the cheapest one that answers it. If the question is answered and the risk left is execution, you are ready for an MVP.
Second: who touches it? If the people using it are colleagues and test participants, prototype rules apply: cut every corner that does not serve the question. The moment strangers depend on it, MVP rules apply: it has to work, all the way through, every time.
The agent-built wrinkle
Here is the honest complication. When an agent builds your prototype, it writes real code. An afternoon with an AI prototyping tool can produce a working checkout flow, not a clickable picture of one. The artifact gap between prototype and MVP has nearly closed.
The commitment gap has not. "Built to learn" and "built to serve" remain different promises, even when the code looks similar. A prototype makes no promises about tomorrow. An MVP promises that tomorrow exists: someone will fix bugs, migrate data, and answer support email. That promise, not the code quality, is the real line between them.
Making the transition
When a prototype earns promotion, resist the urge to ship it untouched. Keep the decisions: the flow that tested well, the copy people understood, the layout that made the demo land. Rebuild the load-bearing parts: data models, authentication, payments, anything that must survive contact with strangers. Agent-built prototypes make this cheaper than it used to be, because the same brief that produced the prototype can produce the sturdier version, informed by everything the prototype taught you.
For the fuller picture of how prototypes fit into shipping real software, start at the prototyping pillar or see how teams take the step after the prototype in our AI app development guides.