Prototype development
with pace and focus

The essence of working with prototypes is simple: surface uncertainties when they are still cheap. You combine vision with evidence, design with data, and make trade-offs visible. This not only creates buy-in but also a clear roadmap that aligns with reality.

What you really want to achieve

• Clear decisions based on behaviour, not assumptions

• A clickable story that investors and teams understand

• A practical bridge to realisation, without lock-in

Evidence over assumptions

The best feedback comes from behaviour: clicking, swiping, scrolling. That is why we test realistic journeys, not loose screens. Subtle copy, micro-animations, empty states — it all adds up.

Where teams often get stuck

Too much scope in one go. Too little real data. Slick demos that hide edge cases. In practice “too perfect” is misleading — better an honest prototype that shows friction than a shiny tale that hides errors.

The pragmatic route forward

We start small, make scenarios concrete and reveal choices with variants. Next we test purposefully, measure friction points and translate insights into a feasible first release.

• Small workshop as jump-starter

• Prototype live within one day to a week

• AI-supported flows for speed and consistency

• Testing with real tasks, not vague questions

• Clear next steps towards MVP and TRL level

Those who try to prove everything at once often prove nothing. Prototype development is about naming uncertainties and eliminating them systematically — sometimes with a rough flow, sometimes with pixel-perfect screens. It is like chess: not every piece must move at once, but every move must be deliberate.

Why you should experience first and build later

• Experience reveals friction that documents hide

• Real interaction sharpens copy and order

• Buy-in grows faster around something tangible than around a memo

Proof of concept versus prototype

A proof of concept (PoC) demonstrates technical feasibility: can it be done, does the technology work, is the integration possible. A prototype simulates the user experience: this is how it feels, how you navigate, these are the states. Both are valuable but answer different questions. In TRL terms a PoC is usually around TRL 3, while prototypes move towards TRL 4-6 — first in lab scale, then in relevant and test environments.

The power of variants

What happens if you shorten the call to action? What if you place filter options below the search bar rather than above it? By prototyping and testing two variants, you see the effect without endless debate.

Realistic data, realistic reactions

A prototype with domain-specific language and believable datasets (synthetic if necessary) triggers better feedback.

The pitfall is well-known: too slick, too polished, not real enough. A working prototype feels authentic, edge cases included.

Practical guidelines for immediate results

Limit scope without being naïve

Choose two primary tasks and work them out in depth, including entry and exit.

Make interaction tangible

Clickable means more than linking screens; add micro-interactions.

Let AI boost speed and quality

• Generate component variants to accelerate design choices

• Use AI for first drafts of micro-copy

• Synthetic test data that mimics patterns

• Rapid flow sketches from user stories

Test like a researcher, not a presenter

Observe, note, time. Behaviour beats opinions.

The line between design and build is blurring. AI, design systems and TRL-driven development paths mean prototypes are not only created faster but also predict more accurately how the final solution will perform.

Generative flows based on goals

From goal to automatically suggested screen flows.

Synthetic everything

Synthetic data and scenarios let you safely simulate complex behaviour.

Bridge to implementation without lock-in

Prototypes remain code-free yet generate artefacts that support your build team.