AI can build a high-fidelity prototype in minutes — but a prototype is not a brief. It looks finished while missing the requirements, rules, states, edge cases and validation logic developers need. HyperSemantic is the one-file template that turns it into a clear, build-ready specification.
Between the two is where meaning usually leaks. The template closes that gap — in three steps.
A high-fidelity, clickable prototype — the kind you can now generate with AI in minutes.
Every screen, state, rule and edge case is read from the prototype — and tagged for how sure we are.
A clear specification for designers, product owners, developers and QA — ready to estimate and build.
Built for designers, product owners, developers and QA — so everyone works from the same source of truth.
Every requirement is tagged by confidence and priority. The team can see what is confirmed, what is a recommendation, and what still needs a decision — before any code is written.
Screens, states and rules are documented up front, so development can understand scope early and estimate with fewer surprises.
Acceptance criteria are written in Given / When / Then format, so QA can test against intended behaviour from day one.
These are the real building blocks of the document. No unverified assumptions, no guesswork.
Every requirement traces back to a real prototype interaction or an agreed decision. Where information does not exist, the template says so — and asks the owner. Nothing is guessed.
“Missing information” is a feature. Unknowns are surfaced and owned, never quietly guessed — so nobody builds on a false assumption.
Priority sits beside confidence, so scope conversations start from facts rather than opinions.
Use it to document screens, states, requirements, rules, edge cases and acceptance criteria before handing work to development.