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Blazor’s new AI components are designed to help developers build agent experiences that do more than display a chat transcript. They can stream content, surface tool requests and progress, pause for approval, and share typed application state with a workspace-style interface. The components are experimental throughout the .NET 11 release line, so they are building blocks to evaluate—not a finished, automatic agent UI.
What “agentic UI” means in Blazor
A chat box shows what an AI says. An agentic interface can also show what it is doing and let a person guide consequential steps. In a travel planner, for example, a conversation could sit beside a structured itinerary that updates as the agent works. The page might show progress, present an action for the user to handle, or ask for confirmation before proceeding.
That is the direction of the experimental Blazor AI components. Daniel Roth, Principal Product Manager at Microsoft, describes them as “building blocks for these experiences, which we call Agentic UI” in the September 28, 2026 .NET Blog announcement. The distinction is important: the components do not make Blazor itself an agent or automatically generate a complete application UI. Developers provide the AI client, decide what tools and content to expose, and implement the relevant interaction and state handling.
What the experimental components provide
Microsoft’s ASP.NET Core .NET 11 release notes describe the Microsoft.AspNetCore.Components.AI package as prerelease and experimental throughout .NET 11. The release notes document version 0.1.0-preview.1.26459.102 for .NET 11 RC1; that is a preview-specific version, not a general stable release. Check the latest release notes before using version-specific setup instructions.
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ChatPageprovides a complete chat shell, combiningAgentBoundary,MessageListandMessageInput. Developers can also compose or customize the lower-level components.UIAgentwraps an application-providedIChatClientand turns streaming updates into observable content blocks.- Rich-text and tool-rendering support includes client-side handling through
UIActionBlock. ActivityContentBlockand related handlers can map provider- or application-specific progress updates into visible activity.UIAgent<TState>provides typed, observable application state shared between the agent and a workspace-style UI.- Approval flows let an application present a consequential requested action for a user to review or confirm.
These pieces let an interface represent more than plain conversational text, but the application still determines how blocks, actions, approvals and state appear to its users.
How an agent can update the page, not just reply in chat
Conversation history and application state serve different purposes. The transcript records the exchange; typed shared state represents the structured information a page needs to render, such as the current itinerary in a travel planner. Keeping those concerns separate makes it possible to show both the agent’s explanation and a workspace view without treating every interface change as another chat message.
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With UIAgent<TState>, the application defines the state shape and how the UI observes and displays it. In an AG-UI integration, server-side agent code can map selected tool results to STATE_SNAPSHOT or STATE_DELTA events. The Blazor client can deserialize those updates and set the agent’s state. The application remains responsible for deciding which results become state and what the resulting UI means.
Tool calls, progress and user approval
A tool request is not necessarily an instruction to execute something silently. Frontend tools run in the Blazor client, where they can interact with UI state, local preferences or request user input. When an agent asks for such a tool, UIAgent can represent the request as a UIActionBlock for the application to handle. That gives the app a place to show the requested action and, where appropriate, involve the user.
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Backend tools are different: they run on the agent server. The interface can use activity blocks to expose progress, while approval flows can put a user review or confirmation step into the interaction. A developer must decide which tools are available, how requests are handled, and what confirmation experience is appropriate; the components are UI building blocks, not a guarantee of security or a substitute for application-specific safeguards.
Do you need AG-UI?
No—not for basic chat with these components. They accept any IChatClient from Microsoft.Extensions.AI, Microsoft’s set of abstractions for working with different AI service implementations through common exchange types and middleware patterns. Its facilities include tool invocation, telemetry and caching.
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Microsoft recommends AG-UI when a remote client and agent server need to exchange richer events, such as frontend tool declarations, backend tool events, approval interrupts, shared-state updates or AG-UI conversation identifiers. The AGUI.Client package supplies AGUIChatClient, which streams AG-UI events as ChatResponseUpdate values. Microsoft describes the protocol as supporting real-time streaming, session context, approvals, state synchronization and custom UI rendering; see its AG-UI integration documentation.
| Need | Documented fit |
|---|---|
| Basic chat interaction | Any IChatClient supported by the Blazor components |
| Richer remote-agent events across client and server | AG-UI, including tool events, approval interrupts and shared-state events |
Those are integration choices, not a requirement to adopt one fixed stack. Microsoft names Microsoft.Extensions.AI, the AG-UI .NET SDK, Microsoft Agent Framework (MAF), ASP.NET Core, Microsoft Foundry and Aspire as building blocks in the broader agent application ecosystem. Which ones belong in a project depends on its architecture and service needs; the cited documentation does not establish that all are necessary together.
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How this differs from existing Blazor AI chat
Blazor already has patterns for AI chat. Microsoft’s AI app template documentation describes an Interactive Server Blazor sample using Microsoft.Extensions.AI packages, an IChatClient, an embedding generator and a chat UI that supports response citations.
The newer experimental components focus on richer interactions around an agent: observable content blocks, tool and activity presentation, approval flows, and typed shared state alongside the conversation. That is an expansion of the interface patterns available to Blazor developers, not evidence that ordinary chat is obsolete or that the new components are already a stable production platform. Microsoft’s launch and documentation do not establish comparative benchmarks or production outcomes for these components.
What to keep in mind before building with them
- Expect preview APIs: the .NET 11 release notes label the package experimental throughout the release line.
- Design the interaction yourself: decide how to render content blocks, show progress, handle tool requests and present approvals.
- Keep client and server responsibilities clear: frontend tools execute in the client; backend tools execute on the agent server.
- Model state deliberately: the application defines the typed state and selects which agent results update it.
- Choose the connection for the job: an
IChatClientis enough for basic chat; AG-UI addresses richer remote-agent event exchange.
For broader Blazor background, the publisher lists Chris Sainty’s Blazor in Action as a book about reusable Blazor UI components and web frontends. It is general background, not documentation for these newly introduced experimental AI APIs.
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