You don't need a team of ML engineers to ship an AI product. You need a clear use case, a model API, and a way to wrap it in a usable interface with auth and storage. SiteFast handles the wrapping so you can focus on the use case.
Start with the job, not the model
The best AI apps solve a specific, repeated job: summarizing meeting notes, drafting product descriptions, classifying support tickets. Pick one job a real person does today and would happily hand off.
Write the job down as input → output. That single sentence becomes your system prompt and your product spec at the same time.
Wire the AI layer
Connect a model provider and define a system prompt with identity, instructions, and examples. Keep the first version stateless — one input, one output — before adding memory or chat history.
Validate the model's output before showing it. Structured outputs and schema validation turn an unpredictable model into a dependable feature.
Build and ship with SiteFast
Describe the app: "A tool where users paste raw notes and get a clean summary with action items." SiteFast builds the interface, connects Supabase for accounts and history, and wires the model call.
Add login, save every generation per user, and publish to a live URL. Add Stripe when you're ready to charge for it.
FAQ
Do I need to train my own model?
Almost never for an MVP. Calling a hosted model with a well-designed prompt covers the vast majority of use cases.
How do I keep AI costs predictable?
Cap context size, cache repeated calls, and meter usage per user so cost scales with revenue.
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