Insights · 12 min read
Founders confuse proofs of concept, prototypes, and MVPs, and the confusion costs real money. Here is what each one actually tests and when to build it.
By GGP Editorial
Most software projects waste their first budget on the wrong first step. A founder has an idea, gets excited, and either builds a full product nobody asked for or a polished demo that cannot actually run. The fix is knowing the difference between a proof of concept, a prototype, and an MVP. The three terms get used interchangeably, but they answer three different questions and cost very different amounts. Get the order wrong and you spend real money testing the wrong thing. Get it right and you spend the smallest amount possible to find out whether the project is worth continuing.
A proof of concept answers "can this technically work?" A prototype answers "how should this look and feel?" An MVP answers "will anyone pay for it?" The three are not the same thing with increasing polish. They are different tools for different unknowns, and most projects only need one or two of them, not all three.
| Proof of concept | Prototype | MVP | |
|---|---|---|---|
| Question it answers | Can this be built? | How should it work? | Will people pay? |
| What you build | A narrow technical test | A clickable design or shell | A small working product |
| Who sees it | Your team | Stakeholders, investors, test users | Real users |
| Typical time | Days to a few weeks | One to four weeks | Two to six months |
| What you learn | Whether the risky part is feasible | Whether the flow makes sense | Whether there is real demand |
Keep that table in mind as you read. The mistake is rarely choosing the wrong one entirely. It is usually skipping the step that would have caught the problem early.
A proof of concept, or PoC, tests a specific technical risk in isolation. It is not a product, not a demo, and not meant to be shown to customers. It is a small, throwaway piece of work that answers one question: does the risky part of the idea actually work?
The risky part is different for every project. It might be whether a payment provider's API supports the exact flow you need. Whether a machine learning model can hit a useful accuracy on your data. Whether a third-party system you plan to build on gives you the access you need. Whether a real-time feature holds up under the load you expect.
The point of a PoC is to fail cheap. If the model cannot reach the accuracy you need, better to learn that in a two-week spike than after six months of building a product around it. We see this pattern often in AI projects. A business wants an AI feature, the idea is sound, but the model on the actual data does not perform well enough to ship. A PoC surfaces that before anyone has committed to a full build. If you are planning an AI product, our guide on AI development cost explains where that early technical validation fits into the budget.
A PoC usually lives on a developer's machine or a staging server. It can be ugly, incomplete, and missing every feature except the one being tested. That is the point. Its output is knowledge: either the approach works, or you need a different one.
A prototype tests the shape of the product, not the engineering. It is a clickable representation of the screens and flows, built in a design tool or as a lightweight front end with fake data behind it. You show it to stakeholders, investors, and a handful of test users to see whether people understand the product and can move through it.
Prototypes answer questions a PoC cannot. Is the flow confusing? Do users know what to tap first? Does the design communicate what the product does? These matter because a product people cannot understand will fail even if the code is perfect.
There is a trap here worth naming. A prototype can feel finished. It is interactive, it looks polished, and everyone in the room nods. But there is no backend, no real data, and no real user paying for it. A prototype that gets mistaken for a working product is how teams get a false green light. The nod in the demo does not tell you whether someone will pull out a card.
A prototype is cheap relative to a build, and it is the right step when the biggest unknown is usability or stakeholder buy-in rather than engineering. For many internal tools and client-facing redesigns, a prototype is all you need before committing.
An MVP is a real, working product with the smallest set of features that lets you test demand with real users. It has a backend, real data, and a path to payment if the product is paid. This is the version you put in front of actual customers to find out whether the market wants it.
Where a PoC tests engineering and a prototype tests design, the MVP tests the business. That is why it is the step that matters most for most founders, and why it costs more than the other two. It has to actually work.
We have written at length about MVP scope and pricing, so I will keep this section short and point you there. The cost depends almost entirely on what kind of product it is: a simple SaaS tool sits in the low tens of thousands, while a compliance-heavy FinTech MVP can run into six figures. The full breakdown is in how much MVP development costs. The key idea for this article is simpler: an MVP validates demand, and you should not build one until the technical and design risks are already settled. Otherwise you are running a demand test on a product that might not even work.
The rule is straightforward. Match the step to the unknown.
If the biggest risk is technical, do a PoC. You are unsure whether the integration, the model, or the performance target is achievable. Prove it in isolation first.
If the biggest risk is usability or buy-in, build a prototype. You are confident it can be built, but you need people to understand it or investors to fund it.
If the biggest risk is demand, build an MVP. You are confident on the tech and the design, and the open question is whether the market will pay.
Most projects do not need all three. A founder building a straightforward SaaS tool on well-understood technology can often skip the PoC and go from a quick prototype to an MVP. A FinTech founder integrating with a bank's API on a tight compliance budget may need a PoC first. An AI product almost always needs a PoC, because model performance is the one thing that can sink the whole idea.
The PoC is the step people skip most often, and it is usually the cheapest one to run. The reasoning goes: we are confident, let's just build it. Then the team spends months building the full product around an assumption that turns out to be false.
The classic version in payments: the team assumes a provider supports a specific flow, builds the whole product around that assumption, and discovers at the end that the provider's API does not allow it. The fix would have been a one-week PoC. Instead it is a rewrite.
The classic version in AI: the team assumes a model will perform well enough, builds the product around it, and discovers the accuracy is not good enough to ship. A PoC on a sample of the real data would have answered that in two weeks.
The pattern is the same. The most expensive thing in software is finding out late that the foundation does not hold. A PoC moves that discovery to the cheapest possible moment. If you are unsure how much of this early validation to plan for, how to estimate a custom software project walks through scoping it properly.
Here are rough bands, in the same spirit as the MVP cost figures we have published before: ranges to think with, not quotes.
| Step | Typical range | Typical time |
|---|---|---|
| Proof of concept | Roughly $5k to $25k | Days to a few weeks |
| Prototype | Roughly $5k to $30k | One to four weeks |
| MVP | $20k to $200k+, by product type | Two to six months |
The PoC and prototype ranges overlap because both depend on how deep you go. A one-page prototype costs less than a clickable prototype of every screen. A PoC that tests one API call costs less than one that trains and evaluates a model.
The MVP range is wide because product type dominates, as the MVP cost article explains. A simple SaaS MVP can sit in the low tens of thousands, while a FinTech MVP with compliance runs much higher.
One useful relationship: the MVP is usually a fraction of the full product, often 20% to 40%, because the full product adds everything you deliberately deferred. We cover that trade-off in MVP vs full product.
When a client comes to us with an idea, we try to avoid letting them pick a deliverable before they have picked a question. The first thing we ask is: what does this project need to prove, and what is the cheapest thing that proves it?
Sometimes the answer is a PoC. A client building a trading or financial platform, for example, usually has a technical or integration risk that should be settled before anything else. We have built systems for brokers trading across Hong Kong, US, and A-shares markets, and the risky parts there are rarely the buttons on screen. They are the feeds, the order routing, and the settlement logic, and those are exactly what a PoC is for.
Other times the answer is a prototype, when the client needs to show something to investors or to an internal stakeholder before the budget opens up. And plenty of projects go straight to an MVP because the tech and the design are already settled and the only open question is demand.
The deliverable follows the risk. That is the whole approach, and it is why we can tell you honestly when a PoC is a waste of your money and when skipping one is dangerous.
There are three mistakes we see repeat, and all of them cost money.
First, calling a prototype an MVP. A clickable design with no backend cannot test demand, because there is nothing real to buy or use. It can only test whether people understand the flow. If you need demand data, you need a working product.
Second, building the full product and calling it an MVP. If you build every feature you can think of, you are no longer running a cheap demand test. You are betting the whole budget before you have any signal. Scope discipline is what makes an MVP cheap; the guide on defining an MVP before hiring developers covers how to hold that line.
Third, skipping the PoC on unproven technology because the team is confident. Confidence is not evidence. When the risky part is technical, test it first and test it cheap.
What is the difference between a proof of concept and a prototype?
A proof of concept tests whether something can technically be built, usually in isolation and behind the scenes. A prototype tests how the product should look and feel, usually as a clickable design with fake data. One is about engineering, the other about design and usability.
Do I need all three before launching?
No. Most projects need one or two. Skip the PoC if the technology is well understood. Skip the prototype if the design risk is low. You need an MVP whenever the open question is whether the market will pay.
How long does a proof of concept take?
Days to a few weeks for most projects. The length depends on the risk being tested. A single API integration can be validated in days; training and evaluating a model can take a few weeks.
Can an MVP be a website instead of an app?
Yes. A responsive web app is often the cheapest way to test demand before committing to native mobile apps. We cover the trade-off in how to build an MVP mobile app without overbuilding.
How do I pay for this work?
A PoC or prototype with a clear goal suits a fixed price. An MVP where the scope will shift as you learn usually suits time and materials or a dedicated team. The difference is explained in fixed price vs time and materials.
The terms get confused because the words all sound like "an early version of my product." But they buy different things. A proof of concept buys confidence that the hard part is possible. A prototype buys confidence that people will understand it. An MVP buys evidence that they will pay. Spend each one only when the corresponding question is actually open, and you will spend the smallest amount of money to find out whether your project is worth building.
GlobeSoft has shipped more than 300 projects across SaaS, mobile, FinTech, AI, and business systems, and we start every one the same way: figure out what must be proven, then build the smallest thing that proves it. If you have an idea and are not sure what to build first, describe the product and the risk you are most worried about. We will help you decide whether you need a proof of concept, a prototype, or an MVP, and give you a realistic budget for it.
Tell us what you are building and where you are today. We typically reply within 24 hours.
