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Build agents with LangChain + Browserbase. Give your Deep Agents search, fetch, and browser subagents to access the full web. All with full observability with the Browserbase dashboard.

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LangChain

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48,004 просмотров • 3 месяцев назад •via X (Twitter)

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We just solved authentication for AI Agents. Announcing 1Password + Browserbase, enabling secure agentic password autofill for your browser agents. Available exclusively on Director dot ai and Browserbase. Full post below.
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We just solved authentication for AI Agents. Announcing 1Password + Browserbase, enabling secure agentic password autofill for your browser agents. Available exclusively on Director dot ai and Browserbase. Full post below.

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Introducing the Search API, powered by Exa. In our benchmarking, browser agents are up to 3x faster when using integrated search. Your agents deserve the best search. Starting today, agents built on Browserbase get 1,000 free searches per month.
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Browserbase helps you build agents that interact with the web. But sometimes, the edge cases require a human touch. Meet Shrey, our newest Click Engineer.
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🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️
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🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️

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Browserbase integrates with @box, allowing your browser agents to save and analyze downloaded files. Watch an agent download safety data, save it to Box, extract what’s in the PDF, and then decide whether it’s compliant.
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Browserbase integrates with @box, allowing your browser agents to save and analyze downloaded files. Watch an agent download safety data, save it to Box, extract what’s in the PDF, and then decide whether it’s compliant.

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there's no excuse to be unemployed, even browser agents are getting jobs with Stagehand 🤘 & Browserbase, you can spin up concurrent browser sessions to apply to infinite jobs get yourself (and/or your browser agents) a job with our templates
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61,980 просмотров • 8 месяцев назад

We just built AWS Lambda with a browser built-in. Introducing Functions, a new compute paradigm that co-locates your code and browsers to build faster browser agents. Functions lets your team focus on the product, while we handle the infrastructure.
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We just built AWS Lambda with a browser built-in. Introducing Functions, a new compute paradigm that co-locates your code and browsers to build faster browser agents. Functions lets your team focus on the product, while we handle the infrastructure.

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🌟Our latest LangChain Academy course – Deep Agents with LangGraph – is now live!🌟 Many agents today follow the same simple pattern: run in a loop, call tools. That architecture works well enough, but it breaks down as tasks get more complex. Today, companies of all sizes – from startups to large enterprises – are building their own Deep Agents. These agents dive deeper. They’re able to plan complex tasks and carry them out over longer time horizons. There are four key features that set Deep Agents apart from regular agents: 1. Planning – keeps agents on track 2. File system – allows agents to offload context 3. Sub-agents – act as focused specialists 4. Prompting – provides agents with detailed instructions Our latest LangChain Academy course, Deep Agents with LangGraph, shows you how to combine these pieces with LangGraph to orchestrate long-running, multi-agent workflows. Big thanks to community member Dmitry Labazkin for helping us shape this course with his contributions! Enroll for free ➡️

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Computer use is finally reliable. It just needed a real harness. Now there is one. Starting today, anyone can ship a SOTA browser agent, batteries included. Introducing Browserbase Agents: one prompt and one API call is all you need to automate the whole web.

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Today, we’re shipping new ways to observe, analyze, and debug agents with LangSmith: • Polly: an AI assistant for AI engineering that helps you understand traces, threads, and improve prompts • LangSmith Fetch: a CLI for pulling trace & thread data straight into your terminal or coding agent Agents are running longer and getting more complex, which demands new debugging workflows beyond simple LLM apps. We wrote a blog on the trends behind this shift— and why tools like Polly and LangSmith Fetch are needed. Shipping reliable agents requires full visibility into agent behavior, with tooling that helps you reason over that data in the UI, the terminal, or alongside coding agents. 📔Learn more about Polly: 📔Learn more about LangSmith Fetch: 📔How to observe deep agents: 📽️ Polly video tutorial: 📽️ LangSmith Fetch video tutorial:

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Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail
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Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

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At Interrupt, Andrew Ng sat down with Harrison Chase for a fireside chat on the future of agents. Watch the session in full.
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At Interrupt, Andrew Ng sat down with Harrison Chase for a fireside chat on the future of agents. Watch the session in full.

LangChain

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TinyFish has made web Search and Fetch features FREE for all developers and AI agents, with generous rate limits! > Search: Low-latency search responses for agentic use > Fetch: Real browser render, clean markdown, or JSON outputs > Works with Claude Code, OpenClaw, Cursor, Codex, n8n, Dify, and more

🚨 AI News | TestingCatalog

32,989 просмотров • 3 месяцев назад

Your agents should use a remote browser built specifically for them, We revamped our Browser Skill to use our custom Stagehand CLI, It's faster than MCP tools and each run uses a new browser context, avoiding prompt injection. npx skills add browserbase/skills —skill browser
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Your agents should use a remote browser built specifically for them, We revamped our Browser Skill to use our custom Stagehand CLI, It's faster than MCP tools and each run uses a new browser context, avoiding prompt injection. npx skills add browserbase/skills —skill browser

Browserbase

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