MVP vs Prototype vs PoC: What's the Real Difference?

You're ready to build. But should you create a prototype? An MVP? A proof of concept?

These terms get thrown around interchangeably in startup conversations, pitch decks, and dev agency proposals. But they're not the same thing. Using the wrong approach at the wrong time can cost you months of work and thousands of dollars.

Let's clear this up once and for all.

The Quick Answer

Here's the difference in one sentence each:

• Proof of Concept (PoC): Can this idea even work technically?
• Prototype: What will this look and feel like?
• MVP: Will real users pay for or use this?

Same product journey. Different questions. Different outputs.

Proof of Concept (PoC): Testing Feasibility

A proof of concept answers one question: Is this technically possible?

You build a PoC when you're not sure your idea can actually work. Maybe you're integrating with a complex API. Maybe you need to process data in a way that's never been done. Maybe your GenAI model needs to perform a specific task and you're unsure if current technology can handle it.

A PoC is rough. It's internal. It's often ugly code that only developers see. The goal isn't to impress anyone—it's to prove that the core technical challenge is solvable.

PoC characteristics:

• Internal only (not shown to users)
• Focuses on one specific technical risk
• Quick and dirty—days to a couple weeks
• Answers: "Can we build this?"
• Output: Working technical demo or clear "no, this won't work"

Example: You want to build an AI that analyzes legal contracts. Before building anything user-facing, you create a PoC to test whether GPT-4 can accurately extract key clauses from various contract formats. If it can't, you've saved yourself from building an entire product around a flawed assumption.

Prototype: Testing Design and Experience

A prototype answers: What will this look and feel like?

Prototypes are about the user experience. They visualize the product before you write production code. They can be clickable Figma mockups, paper sketches, or interactive wireframes.

The key: prototypes aren't functional. The buttons might be clickable, but they don't actually do anything. There's no real backend, no real data processing. It's a simulation of the experience.

Prototype characteristics:

• Visual and interactive (but not functional)
• Tests user flows and interface design
• Can be low-fidelity (sketches) or high-fidelity (pixel-perfect mockups)
• Answers: "Is this intuitive? Does the flow make sense?"
• Output: Clickable mockup, user feedback on design

Example: Before building your contract analysis AI, you create a Figma prototype showing how users would upload documents, view extracted clauses, and export reports. You test this with 10 potential users to see if the workflow makes sense—before writing a single line of backend code.

MVP: Testing Market Demand

An MVP answers the most important question: Will people actually use and pay for this? (If you need a deeper dive, check our guide on what an MVP really is.)

Unlike a PoC or prototype, an MVP is a real product. It works. Users can actually accomplish something with it. But it's stripped to the absolute minimum functionality needed to deliver value and learn from real usage.

The MVP isn't about testing tech (that's PoC) or testing design (that's prototype). It's about testing the market. Do people want this enough to sign up, engage, and potentially pay?

MVP characteristics:

• Fully functional (real users, real data, real value)
• Minimum features—only what's needed to test the core value proposition
• Released to actual users (not just internal testing)
• Answers: "Is there demand for this? Will people use it?"
• Output: User engagement data, feedback, early revenue

Example: Your contract analysis AI is now a working product. Users can upload real contracts, get real extracted clauses, and export real reports. It's missing advanced features like batch processing or CRM integrations—but it solves the core problem. You launch to 50 beta users and measure if they keep coming back.

When to Use Each Approach

Start with a PoC when:

• You're using new or unproven technology
• The technical feasibility is genuinely uncertain
• Failure would mean the entire product idea is dead
• You need to convince stakeholders the tech works before investing more

Start with a Prototype when:

• The tech is proven, but the UX is complex
• You need stakeholder or investor buy-in on the vision
• User flows are complicated and need validation
• You want to test multiple design approaches cheaply

Start with an MVP when:

• Tech is feasible and UX is reasonably clear
• You need real market validation, not just opinions
• You're ready to learn from actual user behavior
• You want to start generating revenue or traction

The Expensive Mistake: Skipping Steps

Here's where startups burn money:

Skipping PoC → Building an MVP on impossible tech
You spend 3 months building a product, only to discover the core AI/integration/algorithm doesn't work reliably. A 2-week PoC would have revealed this.

Skipping Prototype → Building an MVP nobody can use
The product works, but the UX is so confusing that users bounce immediately. A week of prototype testing would have caught these issues.

Skipping MVP → Building a full product nobody wants
You perfect every feature, every edge case, every integration. 12 months later, you launch to crickets. An MVP would have revealed the market wasn't there—or helped you find the right market.

The smartest founders validate in stages: PoC (if needed) → Prototype (if needed) → MVP → iterate.

Can You Combine Them?

Yes—and often you should.

A typical GenAI MVP project might look like:

• Week 1: PoC to validate the AI model can perform the core task
• Week 2: Rapid prototype to test user flows
• Weeks 3-4: MVP development with real functionality

This is how we approach projects at t3c.ai. We've seen too many teams skip validation and pay for it later. A quick PoC or prototype can save months of wasted development.

For example, when we built an HR analytics platform, we validated the core data processing approach first, prototyped the dashboard experience, then built the MVP. The entire process took weeks, not months.

Real-World Decision Framework

Ask yourself these questions:

1. Is the technology proven?

• No → Start with PoC
• Yes → Move to question 2

2. Is the user experience complex or unclear?

• Yes → Build a prototype first
• No → Move to question 3

3. Do you need real market validation?

• Yes → Build an MVP
• No (just exploring) → Maybe a prototype is enough for now

Most software products today use proven tech stacks, so you'll often skip the PoC. But if you're building with GenAI, custom ML models, or complex integrations, don't skip that feasibility check.

The Cost Comparison

Here's what each typically costs and takes:

Proof of Concept:

• Timeline: 1-2 weeks
• Cost: $2K-10K
• Output: Technical validation

Prototype:

• Timeline: 1-2 weeks
• Cost: $3K-15K
• Output: Clickable design mockup

MVP:

• Timeline: 2-8 weeks
• Cost: $15K-75K
• Output: Working product with real users

Compare that to building a full product without validation: 6-12 months, $100K-500K, and a high risk it doesn't find a market.

The math is clear: validate early, validate cheap.

Common Confusion: "We Built a Prototype" (But It's Actually an MVP)

Many founders say "prototype" when they mean MVP—and vice versa.

If users can actually use it to accomplish something real, it's an MVP, not a prototype. If it's clickable but doesn't actually process data or perform functions, it's a prototype.

The distinction matters because it changes what you're learning:

• Prototype feedback: "I'd click here, this is confusing, I like this layout"
• MVP feedback: "I used this daily for a week, here's what I actually needed"

Real usage data beats hypothetical preferences every time.

Ready to Build the Right Thing?

The best approach depends on your specific situation:

• Unproven tech? Start with a PoC.
• Complex UX? Build a prototype.
• Need market validation? Go straight to MVP.

Not sure which path makes sense for your idea? The t3c.ai team can help you figure out the fastest route from idea to validated product—whether that's a quick PoC, a prototype sprint, or a full MVP build.

We're a GenAI development agency that ships MVPs in 2-4 weeks. We'll tell you honestly if you need a PoC first—or if you're ready to build.

Let's talk about your project →

Frequently Asked Questions

What comes first: prototype or MVP?
Usually prototype, then MVP. The prototype validates your design and user flows without coding a real product. Once you're confident in the UX, you build the MVP with real functionality. However, if your UX is simple, you can skip straight to MVP.

Is a proof of concept the same as a prototype?
No. A PoC tests technical feasibility (can we build this?), while a prototype tests user experience (is this intuitive?). A PoC is typically internal and code-focused. A prototype is user-facing and design-focused.

Can an MVP be a prototype?
No. An MVP is functional—users can actually accomplish tasks with it. A prototype simulates functionality but doesn't actually work. They test different things: prototypes test design, MVPs test market demand.

How long should an MVP take to build?
A focused MVP typically takes 2-6 weeks with an experienced team. If your "MVP" is taking 3-6 months, you're probably building too much. Strip features until you reach the minimum needed to test your core hypothesis.

Do I always need all three (PoC, prototype, MVP)?
No. If your technology is proven, skip the PoC. If your UX is straightforward, skip the prototype. Many products go directly to MVP. The key is knowing which validation you actually need.