PoC or MVP?
A proof of concept, or PoC, proves something can be built technically – does the API handle the load, does the algorithm work, does the integration hold up? An MVP proves someone actually wants to use and pay for it. The PoC answers whether it can be built, the MVP whether it should. Biggest risk decides which comes first.
PoC and MVP sound like the same kind of early experiment, but they answer completely different questions. A proof of concept proves that something can be built technically. A minimum viable product proves that someone wants to use and pay for it. One takes the edge off technology risk, the other off market risk – and knowing which one you’re facing determines where to start. The question comes up especially often in AI and integration projects, where the technology is more often an open question.
Can it be built versus does anyone want to use it
A PoC asks the question can this even be built? Can the API handle the load? Does the AI model reach sufficient accuracy? Can it be integrated with the old business system? A PoC is therefore often narrow and technical, built to answer a single such question – and it usually lacks a finished interface, since it’s not meant for users but to prove something to the team.
An MVP instead asks the question does anyone actually want to use this? It’s a real, stripped-down product that meets real users in production, and what it measures is behavior: do people come back, do they complete the flow, do they pay?
The core distinction: the PoC addresses technology risk, the MVP market risk. Use the wrong tool and you’ll confidently answer the wrong question.
Typical sequences: where does the risk sit?
Which order is right gets decided by where the biggest uncertainty lies.
- Technology-risk projects: PoC first, then MVP. When the big question is whether the solution is even possible to build – a new algorithm, an untested integration, a tough performance requirement – start with a PoC. If it fails, you’ve saved an entire product investment. If it holds up, build the MVP on that insight and test the business.
- Market-risk projects: go straight to MVP. When the technology is well-proven but it’s uncertain whether anyone wants the product, a PoC is wasted time. Go directly to an MVP and put the effort into testing demand.
- Both: a PoC on the critical technical piece, then an MVP around it. Sometimes there’s both a technical make-or-break question and a market question. Then the PoC gets scoped to exactly the uncertain technology, and once that’s solved, the MVP gets built to test the whole.
Most projects land in one of these. Putting into words which risk weighs heaviest is often the single most valuable decision in the entire start of a project.
The common mistake: the PoC that quietly becomes production
This is where many stumble. A PoC gets built quickly to prove a point, it works, and someone says, “it already works – can’t we just build on it?” And the makeshift version imperceptibly slides into production.
The problem is that a PoC deliberately skips what makes a product sustainable: error handling, security, tests, structure. It was built to answer a question, not to live in production. When it gets put into production anyway, technical debt gets built into the very foundation, and the bill arrives later – in the form of bugs, security holes, and a codebase that’s hard to build on.
The remedy is a decision made in advance: the PoC will be thrown away. It’s the lesson that carries forward, not the code. The MVP then gets built on the right foundation, with the knowledge that the technology holds up.
A concrete scenario
A company wanted to build a service that automatically interprets scanned invoices with AI. The big uncertainty was technical: would accuracy get good enough to be useful? They built a PoC over a couple of weeks, ran it against hundreds of real invoices, and found it reached a usable level – with clear exceptions for handwritten fields.
Instead of putting the PoC into production, it was used as decision-making input and discarded. The MVP was then built for real, with error handling and a flow for cases where the AI was uncertain and a human had to step in. The PoC answered can it be built; the MVP moved on to does anyone want to use it – in the right order, without the makeshift version becoming the foundation for the product.
How to choose the right starting point
Ask which risk would sink the venture: that it can’t be built, or that nobody wants it? If the heavy uncertainty lies in the technology, start with a PoC. If it lies in the market, go straight to an MVP. At Weapp we often sort out exactly that question first in AI and integration projects, as part of our services.
Not sure where your heaviest risk sits? Get in touch and we’ll help you place it – and choose the right first step.
Frequently asked questions
What's the most important difference between PoC and MVP?
Which question they answer. A PoC answers can this be built – a technical question, often without a user interface. An MVP answers does anyone want to use it – a business question that requires real users. One addresses technology risk, the other market risk. Mix them up and you test the wrong thing.
Does every project need a PoC?
No. A PoC is only justified when there's real technical uncertainty – a new algorithm, a questionable integration, a performance requirement nobody knows will hold up. If you're building something technically well-proven, the PoC is wasted time; go straight to the MVP. A PoC belongs where the answer to can this be built isn't an obvious yes.
Can a PoC be developed further into an MVP?
Rarely directly, and that's a common trap. A PoC gets built to quickly prove a point and often lacks the error handling, security, and structure to hold up in production. Building further on it means stacking production on top of something makeshift. It's usually smarter to take the lesson from the PoC and build the MVP on the right foundation.
Why does PoC come up more often in AI and integration projects?
Because the technology risk is tangible there. Whether an AI model can reach sufficient accuracy, or whether an integration with an old system is even possible, are open questions that are cheaper to answer with a PoC before building a whole product. In projects using well-established technology, that kind of uncertainty is uncommon.
What's the risk of letting a PoC become production?
That technical debt gets built into the foundation from the start. A PoC that quietly ends up in production lacks what makes a product sustainable – error handling, security, tests – and the problems surface later, when they're more expensive to fix. Decide in advance that the PoC will be thrown away, so the lesson carries forward but not the code.