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Atai Barkai

@ataiiam • 5,031 subscribers

CEO @CopilotKit🪁 | ex-@Meta | Author of PsyPhy (experimentally testable physics theory of consciousness) | Physics BA & MSc @Penn

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Introducing Open Tag. A better, open-source Claude Tag. Works with any model, any agent harness, and fully custom agents. Supports → Generative UI → Streaming replies → Human in the Loop approvals → Full thread context Slack and MS Teams today. Discord, Google Chat, WhatsApp soon. Request early access:

Introducing Open Tag. A better, open-source Claude Tag. Works with any model, any agent harness, and fully custom agents. Supports → Generative UI → Streaming replies → Human in the Loop approvals → Full thread context Slack and MS Teams today. Discord, Google Chat, WhatsApp soon. Request early access:

444,312 views • 27 days ago

All UI will become AI This is THE article you'll need give your agents a frontend. Agent-user collaboration is the future, see below 👇

All UI will become AI This is THE article you'll need give your agents a frontend. Agent-user collaboration is the future, see below 👇

498,081 views • 1 month ago

We've raised $27M to build CopilotKit🪁 — the Agentic Frontend Stack connecting humans & agents. Because all UI will be AI. Co-led by Glilot Capital, NfX and SignalFire.

We've raised $27M to build CopilotKit🪁 — the Agentic Frontend Stack connecting humans & agents. Because all UI will be AI. Co-led by Glilot Capital, NfX and SignalFire.

329,918 views • 2 months ago

Launching the 𝙾𝚙𝚎𝚗 𝚃𝚊𝚐 repo. A better, open-source Claude Tag. With support for Generative UI, Human in the Loop, Streaming replies, and Full threads context. The same agent runs in MS Teams, Discord, Telegram, and WhatsApp. Get started in minutes:

Launching the 𝙾𝚙𝚎𝚗 𝚃𝚊𝚐 repo. A better, open-source Claude Tag. With support for Generative UI, Human in the Loop, Streaming replies, and Full threads context. The same agent runs in MS Teams, Discord, Telegram, and WhatsApp. Get started in minutes:

54,717 views • 26 days ago

Introducing Shadify: Generative UI built on ShadCN Simply describe a UI and watch your LangChain agent compose from @ShadCN on the fly, using AG-UI and CopilotKit🪁. Then export it as React code. Repo below. Try it out here:

Introducing Shadify: Generative UI built on ShadCN Simply describe a UI and watch your LangChain agent compose from @ShadCN on the fly, using AG-UI and CopilotKit🪁. Then export it as React code. Repo below. Try it out here:

138,046 views • 4 months ago

We open sourced Claude Artifacts for your own apps. Ask your agent to visualize algorithms, create 3D animations, render charts, or generate interactive diagrams. PLUS it runs the generated code securely w/ sandbox iframe. It's additive to your app, so you can drop it in with one toggle. ➡️

We open sourced Claude Artifacts for your own apps. Ask your agent to visualize algorithms, create 3D animations, render charts, or generate interactive diagrams. PLUS it runs the generated code securely w/ sandbox iframe. It's additive to your app, so you can drop it in with one toggle. ➡️

87,741 views • 2 months ago

Introducing Open MCP Client 🪁 Chat with any MCP server in your own app, just grab a URL from . The team and I vibe coded with Cursor this weekend and built: 1. The first web-based MCP client (link👇) 2. An open-source client you can add into any app How it's built It uses CopilotKit🪁 for the client and interactivity layer, and connects to a 40 line LangGraph ReAct agent that coordinates MCP calls. Hosted on Vercel. Kudos to Suhas Deshpande and Tyler Slaton for hacking and thanks to Harrison Chase for pointers!

Introducing Open MCP Client 🪁 Chat with any MCP server in your own app, just grab a URL from . The team and I vibe coded with Cursor this weekend and built: 1. The first web-based MCP client (link👇) 2. An open-source client you can add into any app How it's built It uses CopilotKit🪁 for the client and interactivity layer, and connects to a 40 line LangGraph ReAct agent that coordinates MCP calls. Hosted on Vercel. Kudos to Suhas Deshpande and Tyler Slaton for hacking and thanks to Harrison Chase for pointers!

299,711 views • 1 year ago

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:

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:

24,529 views • 1 month ago

Stop leaving your Agent stateless. Give it Threads in one hook. Resumable conversations that capture everything: messages, generative UI, shared state, human-in-the-loop workflows. Built on AG-UI, so it works with any compatible agent framework. docs:

Stop leaving your Agent stateless. Give it Threads in one hook. Resumable conversations that capture everything: messages, generative UI, shared state, human-in-the-loop workflows. Built on AG-UI, so it works with any compatible agent framework. docs:

40,879 views • 2 months ago

AG-UI protocol has become as an industry standard📈 The Agent-User Interaction protocol allows you to connect AI agents and frontends. AND it just crossed 2.5M weekly downloads! With adoption/integration by Google, AWS, Microsoft, Oracle, LangChain, Mastra, Pydantic AI, CrewAI & so many more. As well as SDKs in .NET, Golang, Kotlin, Java, Rust and more all contributed by the community. How it works & more 👇

AG-UI protocol has become as an industry standard📈 The Agent-User Interaction protocol allows you to connect AI agents and frontends. AND it just crossed 2.5M weekly downloads! With adoption/integration by Google, AWS, Microsoft, Oracle, LangChain, Mastra, Pydantic AI, CrewAI & so many more. As well as SDKs in .NET, Golang, Kotlin, Java, Rust and more all contributed by the community. How it works & more 👇

18,650 views • 3 months ago

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:

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:

11,997 views • 5 months ago

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