Generative UI with A2UI: From Google to TYPO3

A2UI revolutionises the interaction between AI agents and users. The open-source protocol from Google enables secure, cross-platform UI generation in real-time – including practical integration into TYPO3 13/14.

Overview

  • Text-based LLM dialogues fail in complex UX tasks due to inefficient ping-pong conversations.
  • The Google A2UI protocol defines how AI agents generate UI in real-time via JSON – with a Component Registry and security architecture.
  • Generative UI creates personalised interfaces per user and context instead of a static UI for everyone.
  • A TYPO3 extension integrates A2UI into TYPO3 13/14 for enterprise CMS applications.

From Static Designs to Dynamic Experiences  

The way we design user interfaces is facing a fundamental shift. Traditional UI patterns – identical for all users, statically defined, and manually optimised – are reaching their limits. Generative UI marks the transition from designing for the many to dynamic generation for the individual.

The Nielsen Norman Group defines GenUI precisely: AI creates personalised interfaces in real time for user-specific experiences. Instead of developers coding a fixed UI for all use cases, an AI agent composes the optimal interface for the respective task at the moment of interaction.


Table of Contents  


Video Introduction: Understanding GenUI  

Before we dive into the technical details, these two videos offer an excellent introduction to the topic.

Nielsen Norman Group: GenUI Explained  

The UX experts at the Nielsen Norman Group explain the concept of Generative UI and why it represents a paradigm shift in interface design.

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Video Content

Kate Moran and Sarah Gibbons discuss how AI generates personalised interfaces in real-time. The video explains the differences between traditional UI design and the GenUI approach – essential knowledge for UX designers and developers.

Google A2UI: Technical Deep Dive  

This tutorial shows Google's A2UI protocol in action. From the JSON structure to concrete implementation examples.

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Recommendation

The video demonstrates the integration of A2UI into various frameworks. Particularly relevant are the sections on security architecture and the component registry pattern, which we will revisit later in the TYPO3 integration.


The Efficiency Problem: Text-Based Agents Fail  

Text-based LLM dialogues are suitable for simple requests. In more complex scenarios – structured data entry, visualisation of multidimensional information – inefficient ping-pong dialogues emerge, which significantly increase the cognitive load on users.

The Restaurant Booking Dilemma  

UX Failure on Multiple Levels

Multiple slow round trips: Every question-and-answer round costs time and increases the likelihood of abandonment.

Cognitive overload: Users have to mentally cross-reference a text list with their availability – a classic failure that visual interfaces have long since solved.

Susceptibility to errors: Typos, misunderstandings regarding time formats, missing context information.

The solution does not lie in better text, but in richer communication methods: a graphical calendar with available time slots, interactive sliders for the number of people, a map with table positions. This is where A2UI comes in.


A2UI: The technical foundation for intelligent interfaces  

Agent-to-User Interface (A2UI) is an open-source protocol by Google that empowers AI agents to "speak UI". Instead of just sending text, agents generate rich, interactive user interfaces that are rendered natively within the host application.

Four core principles  

Security First

Agents send data, not code. The client app maintains a catalogue of trusted, pre-approved UI components. LLM-generated code is never executed – critical attack surfaces are eliminated.

LLM-Friendly

UI as a flat list with IDs. Easy for LLMs to generate and incrementally update. Progressive rendering as the conversation develops.

Framework-Agnostic

A JSON payload, native rendering everywhere: Web, Flutter, React, SwiftUI. The abstract UI structure is separated from the concrete implementation.

Open & Flexible

Open Registry Pattern: Developers integrate any of their own components, encapsulate their design system, and retain full control over sandboxing.

Architecture: From generation to rendering  

A2UI data flow: From agent to native user interface

The maxim: A2UI is "as secure as data, but as expressive as code" – a crucial advantage for enterprise adoption.

JSON payload example  

The agent describes intent, not implementation. The client decides what a date-picker concretely looks like – perfect brand consistency guaranteed.


Use Cases: From Concept to Practice  

Restaurant Finder with Interactive Map  

User Request

User asks: "Italian restaurants near me"

Agent Analyses

LLM understands context, determines location, searches for restaurants

UI Generation

Agent sends A2UI payload: Map component + filter list + detail cards

Native Interaction

User filters in real-time, opens Google Maps directly, makes a reservation

Instead of a long text list, the user receives a dynamically generated, interactive results map. Each result offers direct integration with Google Maps. The entire process feels like a seamless, purpose-built app.

Three Key Categories  

An agent generates a tailor-made form with exactly matching input elements based on the context:

  • Service Booking: Date selection, slider for budget, dropdown for service type
  • Onboarding Process: Conditional fields that only appear after specific answers
  • Feedback Collection: Star ratings, text areas, multiple-choice – context-dependent

The form adapts to the conversation, not the other way around.

Agent-Client Communication in Detail  

Workflow of an A2UI-based interaction


A2UI in the Developer Ecosystem  

A2UI is not an isolated project, but a specialised protocol in the rapidly evolving landscape of agent frameworks.

Technology Synergies  

Technology/ProtocolRole relative to A2UI
AG UI / CopilotKitFull-stack framework for agent apps. Provides infrastructure for state synchronisation and communication, integrating A2UI as a message format.
A2A ProtocolTransport protocol for communication between agents across trust boundaries. A2UI messages can be transported via A2A.
GenUI SDK for FlutterSDK for generative UI experiences in Flutter apps. Uses A2UI as a format for UI declaration when communicating with server-side agents.
REST / HTTPFuture planned support for additional transport protocols for increased interoperability and easy integration into existing systems.

A2A: The Sister Protocol for Agent-to-Agent Communication  

While A2UI governs the communication between agent and human, Google's second protocol – Agent2Agent (A2A) – addresses the communication between agents themselves. Together, they form the foundation for a fully agent-driven architecture.

A2UI – Agent-to-User

Direction of communication: Agent → Human

Enables AI agents to generate dynamic, native UI components that are displayed to users in host applications. Focuses on user experience and secure UI generation.

A2A – Agent-to-Agent

Direction of communication: Agent ↔ Agent

Enables various AI agents, regardless of framework or provider, to communicate with each other, exchange information, and coordinate tasks.

A2A was introduced in April 2025 with the support of over 50 technology partners such as Atlassian, PayPal, Salesforce, SAP, ServiceNow, and Workday. The protocol is based on established standards like HTTP, SSE, and JSON-RPC.

Interaction of A2A and A2UI in the agent ecosystem

A2A Design Principles

PrincipleDescription
Agentic CapabilitiesTrue multi-agent scenarios – agents collaborate in their natural, unstructured modalities, even without shared memory, tools, or context.
Existing StandardsBuilt on HTTP, SSE (Server-Sent Events), and JSON-RPC. Integration into existing IT stacks is thereby significantly simplified.
Enterprise SecurityEnterprise authentication and authorisation with parity to OpenAPI authentication schemes.
Long-Running TasksSupport for everything from quick tasks to in-depth research over hours or days – with real-time feedback.
Modality AgnosticNot limited to text – supports various modalities including audio and video streaming.

Practical Example: Recruiting Workflow

A typical A2A scenario: A manager tasks their agent with finding candidates for a developer position:

  1. Main Agent receives the task and identifies specialised agents
  2. Sourcing Agent searches candidate databases
  3. Screening Agent evaluates qualifications
  4. Calendar Agent schedules interviews
  5. Background Check Agent conducts background checks

All agents communicate via A2A, whilst the UI output for the manager is handled via A2UI – seamless orchestration across system boundaries.

Positioning: A2UI vs. Alternatives  

FeatureA2UIMCP AppsOpenAI ChatKit
Native UI Integration
Cross-platformLimited
Multi-agent transparentN/A
Full design controlLimited
Security modelWhitelistSandboxed iFrameVendor-controlled
Open Source

Crucial difference from MCP Apps: MCP treats UI as a resource (typically HTML in a sandboxed iframe). A2UI follows a "native-first" approach – the UI blends seamlessly into the styling of the host app. In multi-agent systems, an orchestrator effortlessly understands the lightweight A2UI message content of a sub-agent.

Industry Voices  

These statements demonstrate how leading technology companies are already using A2UI in production:


Roadmap & Community Involvement  

A2UI was deliberately released early (Version 0.8) to foster open collaboration. The project invites you to shape the future of agent-driven UI together.

Official Roadmap to v1.0  

Spec Stabilization

Achieving a stable v1.0 specification for reliable production deployments

Additional Renderers

Official support for React, Jetpack Compose (Android), iOS (SwiftUI)

Additional Transports

REST, WebSocket, and other protocols for increased integration flexibility

Agent Framework Integration

Native integrations with Genkit, LangGraph, AutoGPT, and other frameworks

Open Source Repository  

Contribute now

As an Apache 2.0 project, the success of A2UI relies on the community. Contributions are welcome in:

  • Specification Refinement: Format extensions, edge case handling
  • Client Libraries: Renderers for new frameworks (Vue, Solid, Svelte)
  • Tooling: Dev tools, debugging utilities, component validators
  • Examples: Real-world implementations, best practice guides

To the GitHub repository


TYPO3 Integration: A2UI in the Enterprise CMS  

The integration of A2UI into TYPO3 opens up new possibilities for intelligent, context-aware backend interfaces: editors receive dynamically generated forms based on the content type, AI assistants support SEO optimisation, and workflows adapt to the current task.

Vision: AI-Powered TYPO3 Workflows  

Context-Sensitive Forms

The AI agent analyses the content type and generates an optimised input form featuring exactly the fields relevant to this context.

Intelligent Dashboards

Dynamic admin dashboards that adapt to the user's role and current tasks. Relevant metrics, shortcuts, and actions available on demand.

SEO Assistant

An AI agent analyses page content in real-time and generates an interactive UI with concrete optimisation suggestions and direct editing options.

Architecture Overview  

TYPO3 A2UI Integration Architecture

Test Extension: a2ui_integration  

I present a complete TYPO3 extension that demonstrates A2UI concepts in TYPO3 13/14.

Extension Structure

1. Extension Configuration

2. Backend Module Registration

3. Core Domain Models

4. Service Layer

5. Controller

6. Fluid Templates

7. JavaScript Renderer

Step-by-Step: Creating an Extension from Scratch  

Follow this guide to implement the A2UI extension yourself. Each step builds upon the previous one.

Step 1: Create the Extension Skeleton

First, create the directory structure and the base files:

TYPO3 13 vs. 14

TYPO3 13 supports both typo3conf/ext/ and packages/. TYPO3 14 exclusively recommends packages/ for local extensions. We are using the future-proof variant here.

Step 2: Base Configuration

Create the two essential configuration files:

Step 3: Creating the Domain Model

The A2UIComponent model represents the JSON structure of the A2UI protocol:

Important Concepts:

  • Immutability: All properties are readonly for thread safety
  • Constructor Promotion: PHP 8.2+ feature for compact code
  • Recursive Children: Supports nested components

Step 4: Component Registry (Security Layer)

The registry implements the whitelist principle – only registered components are allowed:

Security Note

Never accept dynamic template paths from LLM output! The registry ensures that only pre-defined templates can be used.

Step 5: Agent Service (LLM Simulation)

The AgentService simulates the LLM logic. In production, this is replaced by real API calls:

Step 6: Renderer Service

The renderer converts A2UI components into TYPO3 Fluid HTML:

Step 7: Backend Controller

The controller connects everything together and exposes the functionality as a backend module:

Step 8: Creating Fluid Templates

Create the component templates:

Step 9: Register the backend module

Step 10: Activate & test the extension

Done!

After these 10 steps, you will have a working A2UI integration in TYPO3. The backend module can be accessed under Web > A2UI Agent Interface.

Extension Download  

Would you like to use the extension directly without rebuilding every step manually? Download the complete, production-ready extension:

a2ui_integration v1.0.0 (TYPO3 Extension)(15 KB)

Complete A2UI integration for TYPO3 13/14. Includes AgentService, RendererService, ComponentRegistry, 7 UI components, backend module and JavaScript client.

Contents of the extension

  • 5 PHP classes (Controller, Services, Models)
  • 7 Fluid templates for UI components
  • JavaScript client-side renderer
  • Backend module with dashboard
  • Complete README documentation

Compatibility

  • TYPO3 13.0 - 14.x
  • PHP 8.2+
  • Composer support
  • Apache 2.0 Licence (like A2UI itself)

Live Demo: Intent to UI  

Here is an example of how a user intent is converted into a generated UI:

Flow: From user request to generated UI

Installation & Usage  

Install extension

Install via Composer: composer require webconsulting/a2ui-integration

Activate extension

In the Extension Manager or via CLI: typo3 extension:activate a2ui_integration

Open backend module

Open the new module in the TYPO3 backend under "Web > A2UI Agent Interface"

Try the demo

Test various intent examples: "Create page", "Edit content", "Schedule", "SEO"

API Endpoints  

EndpointMethodDescription
/typo3/module/web/a2ui/dashboardGETMain dashboard with example intents
/typo3/module/web/a2ui/generateGETGenerate UI: ?intent=create+page&format=json
/typo3/module/web/a2ui/demoGETShow all component examples

Extension Options  

Production Checklist  

Important considerations before go-live

Security Hardening:

  • Implement rate limiting for API calls
  • Input sanitisation for all user intents
  • Strictly maintain the component whitelist
  • Securely store LLM API keys in the extension configuration

Performance:

  • Caching for frequently generated UI patterns
  • Lazy loading for JavaScript modules
  • Optimise component rendering via AJAX

Testing:

  • Unit tests for AgentService and RendererService
  • Integration tests for controller actions
  • Security tests for component validation

Conclusion: Strategic Importance for Modern Applications  

Generative UI with A2UI marks a fundamental step towards truly intelligent, adaptive assistants. The strategic advantages can be summarised in four dimensions:

Increased Security

By avoiding the direct execution of LLM-generated code, a critical attack surface is eliminated. The declarative approach gives the host application full control over permitted components.

Seamless User Experience

Native UI components of the host application guarantee perfect design integration. No out-of-place iframes, but consistent brand experiences across all touchpoints.

Cross-Platform Interoperability

One JSON payload, native rendering everywhere. Agents generate interfaces for web, mobile, and desktop without platform-specific knowledge.

Accelerated Development

Agents dynamically create context-specific UIs. Reduced development effort for complex, stateful interfaces. Faster prototyping cycles.

The Paradigm Shift  

GenUI represents the transition from designing interfaces for the many, to dynamically generating experiences for the individual. It is not just a new technology, but a decisive step towards personalised, context-aware digital assistants.

For businesses, this means:

  • Higher conversion rates through optimised, task-specific UIs
  • Reduced development costs through reusable, agent-driven components
  • Better scalability with the growing complexity of use cases

Would you like to use A2UI in your project or evaluate generative UI patterns? We support you with strategic assessment, architecture design, and implementation. Contact us for a no-obligation consultation.

Let's talk about your project

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Parts of this content were created with the assistance of AI.