Create an agent that can browse the web with Managed Deep Agents and Browserbase's Stagehand
This video demonstrates building a production-ready web browsing agent by integrating Managed Deep Agents (LangSmith) with Stagehand v4 and BrowserStack. The resulting agent can interact with live websites—performing actions like scrolling, clicking, and navigating—using specialized tools exposed by Stagehand to connect the AI model to scalable browser infrastructure.
Key takeaways
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Agent Architecture Overview
The solution uses Managed Deep Agents as the core agent harness (LangSmith), which is augmented with tools from Stagehand v4. Stagehand, in turn, connects to web browsing infrastructure provided by BrowserStack for production-grade scalability.
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Stagehand V4 Tools
3:57
The agent is given three core tools from Stagehand: `screenshot` (visually inspects the rendered page), `snapshot` (inspects the active page and hydrates element IDs for simple interactions), and `run` (accepts snapshot actions or JavaScript via the Playwright-shaped page API, ideal for multi-step workflows).
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Development Workflow (Local vs. Production)
6:00
The development process involves running `mda dev` locally to test the agent in a managed deep agent studio environment. For production, the deployment is finalized using `mda deploy`, which creates a serverless deployment within LangSmith's Context Hub.