Learn how generative UI turns AI responses into useful, interactive interfaces and how HeroUI Agent renders them safely in React.
Generative UI, short for generative user interface, is an interface assembled at runtime by an AI model for the task in front of the user. The model does not stop at writing an answer. It decides whether that answer is easier to understand as a chart, table, comparison, form, approval step, or a combination of components.
That distinction matters. Ask a normal chatbot, “Which products lost the most revenue this quarter?” and you get a paragraph. Ask a product with generative UI and you can get KPIs, a ranked table, a trend chart, and an action to inspect the underlying orders in one response.
Traditional software starts with fixed screens. Designers and developers decide which information appears, where it goes, and how people interact with it. AI chat changed the content inside the screen, but the response was still mostly text.
Generative UI makes the interface part of the response.
| A user asks for… | A text response gives them… | Generative UI can give them… |
|---|---|---|
| Sales performance by region | A written summary | Metrics, a bar chart, and a sortable table |
| A comparison between several plans | A list of differences | A side-by-side comparison with the tradeoffs highlighted |
| Help updating an account configuration | Step-by-step instructions | A prefilled form and an approval step |
| The cause of a failed workflow | An explanation | A timeline, error details, and the relevant next action |
The goal is not to make every response visual. It is to choose the format that removes the most work for the user.
Generative UI does not require an AI model to write arbitrary HTML, CSS, and JavaScript. That is one approach, but it gives the model control over the same things your product team normally owns: accessibility, security, layout, responsive behavior, and visual consistency.
Production systems usually give the model a smaller vocabulary. The AI can choose and compose approved components, while the application keeps control of their implementation. A chart is still your chart. A button still follows your interaction rules. The generated part is the structure and data, not an unchecked bundle of code.
| Approach | How it works | Best fit |
|---|---|---|
| Static | The model selects one of a few hand-built response components. | Narrow workflows where predictability wins |
| Declarative | The model composes approved components through a typed schema. | Production agents and data-rich applications |
| Open-ended | The model generates complete markup or application code. | Experiments and highly bespoke interfaces |
HeroUI Agent takes the declarative approach. It gives the model enough freedom to choose the right interface without giving up the component contracts, permissions, and design system that make the rest of your product reliable.
Most generative UI systems follow the same path:
This is why generative UI and agents fit together. The agent handles intent and tools; the interface makes the result understandable and actionable.
A useful generated interface should feel like part of the product, not content pasted into it. That requires a few guardrails:
Keep core navigation, authentication, and critical settings conventional. Generative UI is strongest where the right presentation depends on the request or the data. It is not the right fit when consistency is the task.
HeroUI Agent turns tool results into validated Agent UI components. The hosted runtime chooses the presentation, then the embed streams metrics, charts, tables, comparisons, records, forms, and actions using your theme.
Client tools continue to run in the user's browser with the user's existing session and permissions. Generated actions remain declarative, so your application decides what each action is allowed to do.
