The scope chat extracts a structured ScopeSpec from your brief, then the pricing engine returns a fixed quote with no invented prices.
By Lab Twelve, founder-engineer at Lab Twelve.

The AI scope chat is a structured interview, not a creative writing session. You describe what you want to build at /start. The system asks follow-up questions until it can fill a ScopeSpec: screens, auth needs, integrations, data model complexity, and delivery tier. When the checklist is complete, a deterministic pricing engine maps that spec to a fixed quote from our published offers. The model does not invent prices. It classifies scope.
Most discovery calls wander. Someone takes notes. Those notes become a proposal three days later with numbers that reflect memory and optimism more than scope.
The scope chat inverts that. Each answer updates a structured object. Missing fields trigger specific questions. "Do users log in?" is not small talk. It changes auth wiring, admin views, and which offer tier fits.
The stages are roughly:
If your scope exceeds a tier, the chat says so. You either descope or move up a package. No silent scope creep baked into a low anchor price.
The model handles language and follow-ups. It extracts intent into fields the pricing engine understands. It does not choose arbitrary dollar amounts. Every price comes from the same canonical offer list shown on the pricing page.
Humans stay in the loop on taste, edge cases, and QA after you pay. The chat's job ends at a locked quote you can compare against market ranges before you commit.
A structured chat feels slower than "just send me a ballpark." It is slower for five minutes and faster for the next five weeks. Founders who want a number without answering questions about auth and payments are not ready for fixed-price delivery. That is fine. The chat is a filter, not a sales trick.
Read how fixed-price development only works when scope is written down. When you are ready, start the scope chat.
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