Tutorials, deep dives, and practical guides on browser automation and building AI agents.
Build LangChain agents with browser access using Browserbeam. Full code for ReAct agents, custom tools, and multi-agent browser workflows.
What browser as a service means in 2026, managed vs self-hosted architecture, and how Browserbeam's structured output differs from traditional BaaS.
Build a Python web scraping agent with Browserbeam. Covers login flows, multi-page scraping, debugging, and migration from Selenium.
Structured web scraping with declarative schemas. Extract JSON from any site using Browserbeam. Covers pagination, debugging, and migration.
Security best practices for AI browser agents: session isolation, credential management, prompt injection defense, and GDPR compliance.
Scale browser automation from 100 to 100,000 sessions. Queue architecture, capacity planning, cost optimization, and monitoring.
Raw HTML costs AI agents 15,000+ tokens per page. Structured output cuts that by 95%. Side-by-side code comparison and migration guide.
Install the Browserbeam Python SDK and start scraping in minutes. Create sessions, extract structured data, and automate browsers.
Connect your AI coding assistant to real browsers via MCP. Step-by-step setup for Cursor, Claude Desktop, and Windsurf with Browserbeam's MCP server.
Connect an LLM to a real browser using function calling and Browserbeam. Tutorial with OpenAI tool use and agent architecture patterns.
How Browserbeam's extract engine works: schema-driven extraction, advanced patterns for nested data, debugging, and benchmarks vs manual parsing.
Build AI browser agents that browse, click, and extract data using structured APIs. Step-by-step guide with Python and TypeScript.
Structured page data instead of raw HTML. Your agent processes less, decides faster, and costs less to run.
