# Prototyping

> Building an interactive, clickable model of a product so a flow can be experienced and tested before it is engineered.

- Category: Process & Methods
- Canonical: https://www.themasterly.com/glossary/prototyping

A prototype simulates how a product behaves, with screens linked together so a person can click through a real task, and without the cost of building it for real. Fidelity ranges from tapping through grayscale wireframes to near-production screens with working transitions and live data.

The purpose is to learn early. A prototype turns an argument into a test: put it in front of users, watch them attempt the flow, and fix what breaks while fixing is still cheap. It sits between [wireframing](https://www.themasterly.com/glossary/wireframing) and engineering, and it is the raw material for [usability testing](https://www.themasterly.com/glossary/usability-testing).

## Prototype the uncertainty, not the feature

The most common waste in prototyping is building the whole thing. A prototype exists to answer a question, and most features contain one or two genuine unknowns surrounded by screens nobody is worried about.

Before you start, write down the question. "Can a new admin invite their team without our help?" is a question. "Let's prototype the settings area" is a scope. The first tells you which three screens to build and what to leave as a dead end; the second produces a faithful replica that costs a sprint and proves nothing in particular.

Dead ends are fine. A prototype where four buttons do nothing and one works is a prototype that tests one thing properly.

## Choosing fidelity

| Fidelity | Built from | Answers | Cannot answer |
|---|---|---|---|
| **Paper or grayscale** | [Wireframes](https://www.themasterly.com/glossary/wireframing) linked together | Is the sequence right? How many steps? | Anything about comprehension or trust |
| **Linked mockups** | Finished visuals with real copy | Can people find things? Do the words work? | How it behaves under real data |
| **Interactive, styled** | Component library, transitions, states | Does it feel fast? Are states legible? | Performance, edge cases at scale |
| **Coded prototype** | Real front end, sometimes real data | What happens at ten thousand rows? | Nothing much, but it costs the most to change |

The rule that keeps this cheap: raise fidelity only where the question demands it. A prototype can be pixel-perfect on the two screens under test and grayscale everywhere else, and nobody testing it will mind.

## Prototyping when the code is cheap

For most of the last decade the calculation was simple. Figma prototypes were cheap and coded prototypes were expensive, so almost everything got prototyped in a design tool and the questions that needed real data went untested until the build.

AI coding tools have moved that line. A working front end against fake data is now a short exercise rather than a week of engineering, which makes a class of question testable that used to be deferred: what a dense table feels like when it is really dense, whether a search returns fast enough to be usable, how a layout holds when a customer name runs to sixty characters.

The line has not disappeared. A design-tool prototype still changes in minutes, and a coded one still accumulates decisions that are awkward to unmake. The practical split is by question type: flow, layout and comprehension in the design tool; data, latency and volume in code. What has changed is that the second half of that list is now worth prototyping at all.

## Testing with it

A prototype is only worth what you learn from it, and most of that comes down to how the session is run.

**Give a task, not a tour.** "Pick the plan that fits your team" produces behaviour. "What do you think of this page?" produces opinions, and opinions from five people are worth less than the behaviour of one.

**Stay quiet.** The instinct to explain is strong and it destroys the data. If a participant cannot proceed without help, that is the finding.

**Watch where they hesitate.** People rarely say "this label confused me". They pause, then guess. The pause is the signal.

**Five per group.** Nielsen's rule of thumb puts five participants at roughly 85% of the usability problems, on the assumption that participants are comparable. B2B products with admins, members and approvers have three groups, not one. See [usability testing](https://www.themasterly.com/glossary/usability-testing).

## What a prototype cannot tell you

A prototype is a simulation, and four kinds of question fall outside it.

**Whether people would pay.** A participant clicking a plan in a test has spent nothing. Stated intent and card details are different measurements, which is [concept testing](https://www.themasterly.com/glossary/concept-testing)'s problem rather than a prototype's.

**Whether they would keep using it.** A prototype shows the first five minutes. Most B2B products are judged on the fiftieth hour, when the novelty is gone and the data has piled up.

**How it performs.** Transitions in a design tool run at whatever speed you set. Real ones run at whatever the server allows.

**What happens at the edges.** The account with one record and the account with ninety thousand behave differently, and a prototype usually contains a tidy middle case that exists nowhere in production.

Each of these has its own instrument: pricing tests, cohort [retention](https://www.themasterly.com/glossary/retention) data, load testing, and a look at the real data distribution before design starts.

## Prototypes and the design system

Once a [design system](https://www.themasterly.com/glossary/design-system) exists, prototyping changes character. Screens assemble from real components in minutes, so the cost of a second and third option drops close to zero, and the prototype inherits behaviour that has already been decided elsewhere.

That speed carries one risk worth naming. A prototype built from existing components can only propose arrangements of things that already exist, which is efficient for the ninety per cent of work that should reuse, and quietly limiting for the ten per cent that needs something new. When the question is genuinely novel, start outside the library and bring the result back into it afterwards.

## In practice

Before committing a sprint to a new pricing flow, a designer links twelve screens into a clickable prototype and gives five prospects one task: pick the plan that fits your team.

Two cannot find annual billing. One reads the middle tier as a per-company price when it is per seat, and says so only when asked at the end why they chose it. Nobody struggles with the parts of the flow the team had argued about for a week.

The fixes take a day in the design tool. The same lessons arriving after launch would have cost engineering time plus a run of support tickets from customers who had already misread the price, which is the more expensive half. The prototype also settled the internal argument, since the screens the team had debated turned out not to be where anyone got stuck.

## Prototyping inside a design sprint

A [design sprint](https://www.themasterly.com/glossary/design-sprint) compresses the whole loop into five days, and the prototype is the reason the format works. Thursday is spent building one, Friday is spent testing it, and the deadline forces every fidelity decision to be made in favour of speed.

The sprint version has a useful discipline built in: the prototype only has to survive a single day of testing with five people. It can be held together with hard-coded values and screens that lead nowhere, because nobody will open it again on Monday. Teams that prototype outside a sprint often build to a higher standard than the question requires, simply because no deadline is telling them not to.

## Where teams get it wrong

- **Prototyping the whole feature.** The cost approaches building it, and the test loses its focus.
- **Placeholder content.** Lorem ipsum and three-character customer names hide the problems worth finding.
- **Demoing instead of testing.** Walking a participant through the flow while narrating produces agreement, not evidence.
- **Testing colleagues.** People who know the product cannot be surprised by it.
- **Treating the prototype as the spec.** It is a question, and once it is answered, its job is finished. Engineering needs the decision, not the file.

## Related terms

- [Wireframing](https://www.themasterly.com/glossary/wireframing)
- [Usability Testing](https://www.themasterly.com/glossary/usability-testing)
- [Mockup](https://www.themasterly.com/glossary/mockup)
- [Design Sprint](https://www.themasterly.com/glossary/design-sprint)

## Learn more

- [UI/UX design for B2B SaaS](https://www.themasterly.com/services/ui-ux-design)

## FAQ

**What is the difference between a prototype, a mockup and a wireframe?**

Fidelity and interactivity. A wireframe is a structural sketch in grayscale. A mockup is the finished visual, and it is static. A prototype links screens so a person can attempt a real task, which is why only a prototype reveals problems in the flow rather than in the picture.

**How high-fidelity should a prototype be?**

Only as high as the question requires. Testing whether people can find their way through a flow needs linked screens and little else. Testing whether people understand a pricing table needs the real numbers and the real words, because placeholder content hides exactly the problem you are looking for.

**What should you prototype?**

The uncertainty, not the feature. Prototype the two screens where you genuinely do not know what will happen, and leave the rest as dead ends. A faithful prototype of a whole feature costs almost as much as building it and tests nothing in particular.

**How many people should test a prototype?**

Five per distinct user group is the working rule, from Jakob Nielsen's model. In B2B that usually means more than five in total, because admins, end users and approvers behave differently enough to count as separate groups.

**Should we prototype in Figma or in code?**

Figma when the question is about flow, layout or comprehension, because changes take minutes. Code when the question involves real data, real latency or real volume, since a Figma prototype cannot show what a table does with ten thousand rows. AI coding tools have made the second option far cheaper than it used to be, which moves the line but does not erase it.

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