Build a great product

Point your AI at Facet. Ship something real.

Facet is a design library an AI can actually read — and this page is the method that turns that into a product. You copy one prompt into your assistant. It reads the library, interviews you about who the product is for and what job it does, agrees a plan with you, builds with real components, and checks its own work like a user before showing you. Nothing here is hidden: the exact prompts are below, and your AI reads the same rules at /build.txt.

How it works

1. 1

   Copy one prompt

   Pick your tier below and paste it into Claude, ChatGPT, Cursor — anything that writes files. Then describe your idea in a sentence.

2. 2

   It interviews you

   Before any code: who is it for, the one job it does, what done looks like, how it should feel. A few questions at a time, in your words.

3. 3

   You agree the plan

   A short v1 list — the screens, what is in, what is deliberately out, which theme and shell — and it waits for your yes.

4. 4

   It builds and verifies

   Plain HTML on Facet's components — no installs, no build step — then it walks every screen like a user, on a phone size, in light and dark, before handing over.

The prompts

Two tiers, same method. The difference is who makes the technical calls: Prompt 1 keeps every decision with the AI and speaks plain language only; Prompt 2 keeps you in the decisions and teaches as it builds — including when a real backend is worth it.

You are going to build me a complete product using the Facet design
library, and I am not a developer — so you make the technical
decisions and you never hand them to me.

First, read https://facet-kappa.vercel.app/build.txt and follow its
method exactly. Read https://facet-kappa.vercel.app/llms.txt to learn
every component, theme and behaviour Facet ships.

Then interview me in plain language, a few questions at a time — who
the product is for, what one job it must do, what done looks like.
No jargon: never ask me about frameworks, hosting, databases or file
formats. When you know enough, show me a short plan — the screens,
what is in v1, what is not — and wait for my yes.

Build it as plain HTML pages that use Facet from its URL: one link
tag, one CSS file, one JS file, nothing to install. Keep everything
front-end and static; if some part truly cannot work without a
server, park that part, say so in one sentence, and build the rest.
Pick a Facet theme that fits the product's mood and tell me why in
one line. Keep every screen reachable by a link I can share.

When you finish, check your own work like a user would — every
screen, every button, on a phone size and in dark mode — then show
me the result and tell me: what shipped, what you left out, and the
one improvement you would make next. Then stop and wait.

You are going to build me a complete product using the Facet design
library. I understand technology — a PM/founder level, not a daily
coder — so teach me as you build and keep me in the real decisions.

First, read https://facet-kappa.vercel.app/build.txt and follow its
method exactly. Read https://facet-kappa.vercel.app/llms.txt to learn
every component, theme and behaviour Facet ships.

Interview me before building: users, the one job, success, feel.
Then propose a v1 plan — screens, features in and out, which Facet
shell and theme and why — and wait for my yes.

Build with plain semantic HTML plus Facet's classes and data
attributes, consumed from its URL with no build step. As you build,
teach in passing: when you pick a shell, a component or a pattern,
say in a sentence or two what it is and why it is right here — I
want to understand what ships. Keep state in the URL so every screen
and configuration is shareable and testable.

If the product genuinely needs a backend — accounts, shared data,
anything that must persist beyond one browser — stop and explain:
what a backend is in this context, the smallest option that works,
what it costs to run, and what stays impossible without it. Build
the front end fully either way; wire the backend only after I agree.
Follow the backend rules in build.txt's addendum.

When you finish, verify like a user — every screen, every action,
phone size, light and dark — then walk me through what shipped, how
it works, what you left out, and what you would do next. Then stop.

Why this works

Most AI-built products fail one of two ways: the AI builds the wrong thing because nobody asked what the right thing was, or it builds on a framework stack neither of you can read afterwards. This method removes both. The interview comes before the code, and the material is Facet: semantic HTML an AI gets right in one pass and a person can open and follow, with taste — the themes, the spacing, the motion — already built in.

And it is all in the open: build.txt is the same contract your AI reads — the method, the interview question bank, the backend rules, and the quality bar it must pass before calling anything done.