Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Create dynamic and interactive Agent UI experiences in the Gemini Enterprise app. With support for the Agent-to-UI protocol (A2UI), custom agents can dynamically generate rich, native UI components directly within the Gemini Enterprise app.

googlecloud's profile picture

Google Cloud

568,461 subscribers

19,318,491 Aufrufe • vor 2 Monaten •via X (Twitter)

BildungNachrichten & PolitikWissenschaft & Technologie
LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

First look at Gemini Enterprise and UI walkthrough! Some key points: - You can also build Agent workflows via Chat UI - Gemini can create files - Model selector has Auto mode - Gemini Business comes with 15 seats at $21 per month 15 seats! 🔥
0:46

First look at Gemini Enterprise and UI walkthrough! Some key points: - You can also build Agent workflows via Chat UI - Gemini can create files - Model selector has Auto mode - Gemini Business comes with 15 seats at $21 per month 15 seats! 🔥

🚨 AI News | TestingCatalog

47,272 Aufrufe • vor 10 Monaten

🎨 Design freely with Agent 4. - Design while the agent builds. - Explore multiple UI variants on an infinite canvas. - Make precise UI edits that you can apply directly to your app.
0:30

🎨 Design freely with Agent 4. - Design while the agent builds. - Explore multiple UI variants on an infinite canvas. - Make precise UI edits that you can apply directly to your app.

Replit ⠕

184,057 Aufrufe • vor 5 Monaten

We are witnessing a fundamental shift in how software is built. Over the decades, UI was static and predictable. But AI is changing the fundamental nature of the interface. We are moving away from fixed UI and toward a new standard: Generative UI. Generative UI lets agents participate in the UI, not just the conversation. It’s a dynamic participant in the user experience. Depending on the complexity of your app, Generative UI generally falls into three categories: 1. Static (AG-UI): UI is chosen from a fixed set of hand-built components 2. Open-Ended (MCP Apps): agent sends arbitrary content like raw HTML or iframes for total flexibility. 3. Declarative (A2UI): agent and frontend communicate via a structured UI spec for dynamic widgets and forms. The AG-UI Protocol by CopilotKit is the real breakthrough. AG-UI acts as the universal transport layer. It provides the integrations and middleware for every Gen-UI spec, making it trivial to bring dynamic components into your existing app. CopilotKit provides the go-to ecosystem for building agentic applications and is the React client of AG-UI. It is designed to be deeply integrated, allowing developers to bring their own frameworks or protocols to the table. Play around with different types of Generative UI here → Check out the video attached to see Generative UI in action. Appreciate the CopilotKit team for collaborating with me on this deep dive.
0:33

We are witnessing a fundamental shift in how software is built. Over the decades, UI was static and predictable. But AI is changing the fundamental nature of the interface. We are moving away from fixed UI and toward a new standard: Generative UI. Generative UI lets agents participate in the UI, not just the conversation. It’s a dynamic participant in the user experience. Depending on the complexity of your app, Generative UI generally falls into three categories: 1. Static (AG-UI): UI is chosen from a fixed set of hand-built components 2. Open-Ended (MCP Apps): agent sends arbitrary content like raw HTML or iframes for total flexibility. 3. Declarative (A2UI): agent and frontend communicate via a structured UI spec for dynamic widgets and forms. The AG-UI Protocol by CopilotKit is the real breakthrough. AG-UI acts as the universal transport layer. It provides the integrations and middleware for every Gen-UI spec, making it trivial to bring dynamic components into your existing app. CopilotKit provides the go-to ecosystem for building agentic applications and is the React client of AG-UI. It is designed to be deeply integrated, allowing developers to bring their own frameworks or protocols to the table. Play around with different types of Generative UI here → Check out the video attached to see Generative UI in action. Appreciate the CopilotKit team for collaborating with me on this deep dive.

Pratham

33,920 Aufrufe • vor 6 Monaten

Introducing MCP UI, the SDK that wires UI components directly into the MCP protocol🤯 Watch the video to see the new phase in AI interaction! Why browse when you can have universal apps that deliver the right UI to consume any data and perform any action? Replace cumbersome walls of text with slick interactive components, bringing rich web experiences to MCP-enabled agents such as Claude and Cursor. Let’s build Jarvis so Kent C. Dodds 🏹 doesn’t have to! 🧵>>
0:41

Introducing MCP UI, the SDK that wires UI components directly into the MCP protocol🤯 Watch the video to see the new phase in AI interaction! Why browse when you can have universal apps that deliver the right UI to consume any data and perform any action? Replace cumbersome walls of text with slick interactive components, bringing rich web experiences to MCP-enabled agents such as Claude and Cursor. Let’s build Jarvis so Kent C. Dodds 🏹 doesn’t have to! 🧵>>

Ido Salomon

79,457 Aufrufe • vor 1 Jahr

Big release here! AG-UI 🤝 Google A2A Embed A2A multi-agent meshes in your frontend, and build fullstack multi-agent apps with A2A and AG-UI. 🔍How it works: Simply drop-in A2A agent endpoints, and an A2A AG-UI orchestrator agent will bi-directionally stream events between your Agents & application. Includes: - UI for A2A Interactions - Generative UI for Agent Tool Calls - Human-in-the Loop Approvals - State Synchronization (agent mesh application state) - Frontend Tool Calls for A2A Agents Watch the demo below > LangGraph & Google ADK agents working together simultaneously inside an app Demo GitHub, docs, and more 👇
0:25

Big release here! AG-UI 🤝 Google A2A Embed A2A multi-agent meshes in your frontend, and build fullstack multi-agent apps with A2A and AG-UI. 🔍How it works: Simply drop-in A2A agent endpoints, and an A2A AG-UI orchestrator agent will bi-directionally stream events between your Agents & application. Includes: - UI for A2A Interactions - Generative UI for Agent Tool Calls - Human-in-the Loop Approvals - State Synchronization (agent mesh application state) - Frontend Tool Calls for A2A Agents Watch the demo below > LangGraph & Google ADK agents working together simultaneously inside an app Demo GitHub, docs, and more 👇

CopilotKit🪁

31,845 Aufrufe • vor 10 Monaten

During the #MicrosoftBuild keynote, Cassidy took the stage to demo the new GitHub Copilot app, showing how agents, multi-model reviews, custom UI canvases, and enterprise-ready deployment through Rayfin come together in one workflow.
5:27

During the #MicrosoftBuild keynote, Cassidy took the stage to demo the new GitHub Copilot app, showing how agents, multi-model reviews, custom UI canvases, and enterprise-ready deployment through Rayfin come together in one workflow.

Microsoft Developer

40,017 Aufrufe • vor 2 Monaten

The UI lesson hidden in the AI Self-Agent Pika App Breakdown 67 Pika
15:50

The UI lesson hidden in the AI Self-Agent Pika App Breakdown 67 Pika

𝙅𝙊𝙎𝙀

30,898 Aufrufe • vor 3 Monaten

Introducing the A2UI Widget Builder ⚙️ An interactive demo and template to build A2UI Widgets and bring them into your application. Powered by CopilotKit & Google's new A2UI spec Includes... - Widget Gallery: premade UI widgets you can use & modify - Material Icons: 100 of the most commonly used icons - UI Components: common components preview, usage and props - Source code and data on any widget/icon/component - Built with CopilotKit- so you get chat UI, generative UI, etc. Try it out: Tutorial of how to get started: Repo:
0:30

Introducing the A2UI Widget Builder ⚙️ An interactive demo and template to build A2UI Widgets and bring them into your application. Powered by CopilotKit & Google's new A2UI spec Includes... - Widget Gallery: premade UI widgets you can use & modify - Material Icons: 100 of the most commonly used icons - UI Components: common components preview, usage and props - Source code and data on any widget/icon/component - Built with CopilotKit- so you get chat UI, generative UI, etc. Try it out: Tutorial of how to get started: Repo:

CopilotKit🪁

18,510 Aufrufe • vor 8 Monaten

Introducing 21st Agent Elements Diffed edits. Plan approvals. Clarifying questions. Sub-agents. Tool cards. The pieces every "agent UI" lib skips. 25 shadcn /ui components built for the new generation of agents that use your computer. Open-source. Link in thread 🧵
0:28

Introducing 21st Agent Elements Diffed edits. Plan approvals. Clarifying questions. Sub-agents. Tool cards. The pieces every "agent UI" lib skips. 25 shadcn /ui components built for the new generation of agents that use your computer. Open-source. Link in thread 🧵

serafim

44,036 Aufrufe • vor 3 Monaten

Introducing the Generative UI Research Canvas ✨ Every agent needs a powerful UI Combine LangChain, Tavily, Tako and CopilotKit🪁 and you get a LangChain-based research agent with a Generative UI-driven frontend. When agents can explore the underlying data, research becomes more trustworthy and useful. How does this work? - LangChain manages the agent workflow and tool orchestration. - Tako converts retrieved data into structured, visual components - Tavily provides agentic search - CopilotKit renders those components in the UI and keeps the user in the loop while the agent is working So instead of a boring and static report, the output is an interactive research canvas that evolves as the agent runs. 2026 is the year where users want to see the output, not read it... Generative UI makes this possible for agentic applications. Tutorial: Open-Source Repo: Docs:
0:36

Introducing the Generative UI Research Canvas ✨ Every agent needs a powerful UI Combine LangChain, Tavily, Tako and CopilotKit🪁 and you get a LangChain-based research agent with a Generative UI-driven frontend. When agents can explore the underlying data, research becomes more trustworthy and useful. How does this work? - LangChain manages the agent workflow and tool orchestration. - Tako converts retrieved data into structured, visual components - Tavily provides agentic search - CopilotKit renders those components in the UI and keeps the user in the loop while the agent is working So instead of a boring and static report, the output is an interactive research canvas that evolves as the agent runs. 2026 is the year where users want to see the output, not read it... Generative UI makes this possible for agentic applications. Tutorial: Open-Source Repo: Docs:

Atai Barkai

11,997 Aufrufe • vor 6 Monaten

This entire mobile app UI was generated using new AI Agent tool with just one prompt and 3 button clicks and they have got free tier too. It’s built specifically for mobile app development and can generate entire UI screens, write code, and even publish apps on the App Store! More details below 👇
0:22

This entire mobile app UI was generated using new AI Agent tool with just one prompt and 3 button clicks and they have got free tier too. It’s built specifically for mobile app development and can generate entire UI screens, write code, and even publish apps on the App Store! More details below 👇

AshutoshShrivastava

17,720 Aufrufe • vor 1 Jahr

Finally, MCP servers can now deliver UI-rich experiences! MCP servers in Claude/Cursor don't offer UI any experience yet, like charts. It's just text/JSON. mcp-ui lets you add interactive web components to its output that can be rendered by the MCP client. 100% open-source!
0:41

Finally, MCP servers can now deliver UI-rich experiences! MCP servers in Claude/Cursor don't offer UI any experience yet, like charts. It's just text/JSON. mcp-ui lets you add interactive web components to its output that can be rendered by the MCP client. 100% open-source!

Avi Chawla

123,784 Aufrufe • vor 11 Monaten

Gemini 2.5 Flash-Lite for instant UI! 🚀 Just vibe coded a chat app that only responds in dynamically generated UI to your prompts. No generation time was sped up. Enjoy five quick components in a matter of seconds, fun to see what fast models will enable. Demo + code below!
1:06

Gemini 2.5 Flash-Lite for instant UI! 🚀 Just vibe coded a chat app that only responds in dynamically generated UI to your prompts. No generation time was sped up. Enjoy five quick components in a matter of seconds, fun to see what fast models will enable. Demo + code below!

Ammaar Reshi

122,691 Aufrufe • vor 1 Jahr

Modern AI agents have evolved beyond a simple state graph and a few tool calls. Google Developer Expert Sam Witteveen shares 5 components you need to build world-class agents. Join Gemini Enterprise Agent Ready (GEAR) for the latest agent resources →
1:23

Modern AI agents have evolved beyond a simple state graph and a few tool calls. Google Developer Expert Sam Witteveen shares 5 components you need to build world-class agents. Join Gemini Enterprise Agent Ready (GEAR) for the latest agent resources →

Google Cloud Tech

11,360 Aufrufe • vor 2 Monaten

your agent has left the chat. > generate your user interface > interact with the generated interface all the benefits of interactive visual interfaces with all the power of ai agents. build an agent that can speak your ui. it's open source. link 👇
0:50

your agent has left the chat. > generate your user interface > interact with the generated interface all the benefits of interactive visual interfaces with all the power of ai agents. build an agent that can speak your ui. it's open source. link 👇

Michael Magán

10,737 Aufrufe • vor 5 Monaten

To help you create rich, reliable experiences while reducing regeneration time and costs, we’re adding two new models to Gemini Enterprise Agent Platform: #1 - Nano Banana 2 Lite is GA #2 - Gemini Omni Flash is in public preview Learn more →
1:14

To help you create rich, reliable experiences while reducing regeneration time and costs, we’re adding two new models to Gemini Enterprise Agent Platform: #1 - Nano Banana 2 Lite is GA #2 - Gemini Omni Flash is in public preview Learn more →

Google Cloud Tech

14,028 Aufrufe • vor 1 Monat

AG-UI makes building agentic applications dramatically easier. Here's how it works. This is a model for a simple chatbot: User → LLM → Response But interactive agents that render UI, pause for approvals, and ask users for input need a much more complex model. When building these agents, a response from the LLM will include a series of state changes as the agent runs: • Agent started a task • Agent called a tool • Agent updated its state • Agent streams these tokens • Agent is waiting on a human • Agent is resuming the task The Agent-User Interaction Protocol (AG-UI) treats the LLM response as a stream of events rather than a text endpoint. In practice, here is what you get as an agent runs: 1. Lifecycle events so your UI knows where the agent is. 2. Text messages that stream tokens. 3. Tool calls so your UI can prefill a form with any required arguments. 4. State updates that keep your UI in sync with the agent. 5. Special events for human approvals, rich media, and custom needs. All of these events travel over standard transports (SSE, WebSockets, or plain HTTP) as JSON. As a result, you can build a frontend that stays in sync with the agent's progress without having to invent a custom process to make this happen. For example, building a human-in-the-loop workflow becomes an off-the-shelf component you can integrate rather than build from scratch. CopilotKit🪁 is the creator of AG-UI, and you can use it when building frontend applications pretty much anywhere: • React • Angular • Vue • React Native • Slack • Teams • Discord • WhatsApp • Telegram Here is the link for you to check it out: Thanks to the CopilotKit team for partnering with me on this post.
0:22

AG-UI makes building agentic applications dramatically easier. Here's how it works. This is a model for a simple chatbot: User → LLM → Response But interactive agents that render UI, pause for approvals, and ask users for input need a much more complex model. When building these agents, a response from the LLM will include a series of state changes as the agent runs: • Agent started a task • Agent called a tool • Agent updated its state • Agent streams these tokens • Agent is waiting on a human • Agent is resuming the task The Agent-User Interaction Protocol (AG-UI) treats the LLM response as a stream of events rather than a text endpoint. In practice, here is what you get as an agent runs: 1. Lifecycle events so your UI knows where the agent is. 2. Text messages that stream tokens. 3. Tool calls so your UI can prefill a form with any required arguments. 4. State updates that keep your UI in sync with the agent. 5. Special events for human approvals, rich media, and custom needs. All of these events travel over standard transports (SSE, WebSockets, or plain HTTP) as JSON. As a result, you can build a frontend that stays in sync with the agent's progress without having to invent a custom process to make this happen. For example, building a human-in-the-loop workflow becomes an off-the-shelf component you can integrate rather than build from scratch. CopilotKit🪁 is the creator of AG-UI, and you can use it when building frontend applications pretty much anywhere: • React • Angular • Vue • React Native • Slack • Teams • Discord • WhatsApp • Telegram Here is the link for you to check it out: Thanks to the CopilotKit team for partnering with me on this post.

Santiago

17,438 Aufrufe • vor 1 Monat

Microsoft Teams just got Generative UI But this is just the tip of the iceberg. AG-UI is the protocol connecting any agent to any user on any app, topped with Generative UI. That means your agent can render: - forms - buttons - charts - approval flows Right inside the chat, on the fly. But it's not limited to in-app copilots. What's special is that you can work with any agent using the same system and bring them into any surface, including Slack, WhatsApp, Discord and more. This is exactly why Hermes and OpenClaw took off. As users of these agents, we don't like walls of text, and it's a pain to get when you can have way better UX. CopilotKit🪁 + AG-UI handle that interaction layer. If you want to try out Agentic UI in Microsoft Teams, you can get early access here:
0:55

Microsoft Teams just got Generative UI But this is just the tip of the iceberg. AG-UI is the protocol connecting any agent to any user on any app, topped with Generative UI. That means your agent can render: - forms - buttons - charts - approval flows Right inside the chat, on the fly. But it's not limited to in-app copilots. What's special is that you can work with any agent using the same system and bring them into any surface, including Slack, WhatsApp, Discord and more. This is exactly why Hermes and OpenClaw took off. As users of these agents, we don't like walls of text, and it's a pain to get when you can have way better UX. CopilotKit🪁 + AG-UI handle that interaction layer. If you want to try out Agentic UI in Microsoft Teams, you can get early access here:

Atai Barkai

24,595 Aufrufe • vor 1 Monat

✨AG-UI has been taking off! The Agent-User Interaction Protocol, allows you to bring AI agents into Frontend Apps. Excited to announce BIG updates & adoption by LlamaIndex 🦙 ,Agno, Google ADK, AWS & more! + New Building Experience🧑‍💻 npx create-ag-ui-app How it works & more 👇
0:25

✨AG-UI has been taking off! The Agent-User Interaction Protocol, allows you to bring AI agents into Frontend Apps. Excited to announce BIG updates & adoption by LlamaIndex 🦙 ,Agno, Google ADK, AWS & more! + New Building Experience🧑‍💻 npx create-ag-ui-app How it works & more 👇

CopilotKit🪁

70,655 Aufrufe • vor 1 Jahr