How Does Puck Let You Control AI-Generated Interfaces With Your Own Rules?

Puck is a visual editor for React that lets your users generate, review, and refine production-ready interfaces inside your application. Its control model is aimed at teams that want AI-assisted interface generation but don't want to hand over the design system, component set, or editing permissions to the model. You define the rules; Puck enforces them at the point where users generate and edit.

The core idea: your rules, applied at AI scale

Puck's own framing is "The scale of AI, with your rules" and "The level of control you need." The practical meaning is that AI output is constrained by the same configuration that governs manual editing. Instead of letting a model emit arbitrary markup, you register the components and props that are allowed to exist, and everything users generate or refine stays inside that boundary.

This matters because unconstrained generation tends to produce interfaces that look plausible but break your design system, use components you don't ship, or accept props your components can't handle.

Where the control actually lives

Component allowlist

You decide which React components are available to the editor. If a component isn't registered, it can't appear in a generated or hand-edited interface. This is the primary lever: the surface area AI can touch is exactly the surface area you exposed.

Prop-level constraints

For each registered component you define which props exist and what values they accept. A generated interface can only set props you declared, which keeps output compatible with your actual component implementations rather than a model's guess at them.

Generate, review, refine as a loop

Puck describes the workflow as letting users "generate, review, and refine production-ready interfaces inside your application." The review step is not decorative — it's where a person inspects what the model produced against your rules before it moves toward production. Refinement happens through the same constrained editor, so corrections can't drift outside the allowlist either.

What this looks like in practice

A concrete scenario: a marketing team wants to assemble landing pages without filing tickets. You register your heading, button, image, and layout components in Puck, with only the props your design system supports. A user prompts for a hero section. The model can only compose from those components and props, so the result uses your real button variants and spacing tokens rather than invented ones. The user reviews it, swaps a component, adjusts copy, and the page is ready — still inside your rules.

The same pattern applies to internal tools, dashboards, or any interface where you want generation speed without losing consistency.

Who this fits, and who it doesn't

Checking the details before you commit

The specifics that determine fit — exact configuration APIs, how generation is wired into your app, and what the pricing tiers include — are not covered in the material summarized here. Puck's site has a dedicated pricing page at puckeditor.com/pricing, and the comparison and "How teams use Puck" sections on the homepage are the right places to verify how the control model maps to your stack. Confirm the component and prop configuration surface against your own design system before assuming a given constraint is expressible.