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Today’s AI agents don’t run in a straight line anymore. They plan, delegate, and spin up multiple subagents in parallel. But most UIs still show… a loading spinner. In this video, Christian Bromann will show you how to build real-time interfaces for deep agent architectures using the new subagent streaming capabilities in LangGraph. Instead of waiting for the final answer, you can now: - Track each subagent as it runs - See tool calls in real time - Display progress and status per agent - Build rich, transparent, and trustworthy AI experiences We’ll walk through the new useStream updates in @langchain/langgraph-sdk, how the typed API works, and how to migrate existing apps with minimal changes. If you’re building multi-agent systems, this unlocks a completely new class of UX. 🔗 Links: Streaming Docs: https://docs.langchain.com/oss/javascript/deepagents/streaming/frontend GitHub example: https://github.com/langchain-ai/langgraphjs/tree/main/examples/ui-react/src/examples/deepagent