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LangSmith Agent Builder Now Available in Public Beta
LangSmith Agent Builder is now in Public Beta, enabling anyone to create production ready agents without writing code. Learn what's new in the Beta release, how people are using Agent Builder, how...
Anthropic-Style Context Editing… Now for Every LLM in LangChainJS!
Learn how to bring Anthropic’s powerful Context Editing capabilities — like tool result clearing — to any LLM using LangChainJS. In this video, Christian Bromann breaks down Anthropic’s original d...
Product Evals (for AI Applications) in Three Simple Steps
Eugene Yan wrote a GREAT blogpost on how to build product evals (for AI applications) in three simple steps: https://eugeneyan.com/writing/product-evals/ These three steps are: 1. Label data 2. Al...
AI Agents in Production: Lessons from Rippling and LangChain
How does a company deploy AI agents across HR, payroll, IT, and finance products used by thousands of companies? Ankur Bhatt, Head of AI at Rippling, shares insights on building production-ready ag...
Using skills with Deep Agents CLI
Anthropic recently introduced the idea of agent skills, a directory of folders that an agent can access to perform different actions. Here, we talk about skills, why they are interesting, how agent...
Managing Agent Context with LangChain: Summarization Middleware Explained
Long-running agents eventually hit context overload — leading to context poisoning, distraction, confusion, and degraded performance. In this video, Christian from LangChain breaks down how Summar...
What are Deep Agents?
Deep Agents is a term we coined to describe agents capable of handling complex, open-ended tasks over long time horizons. We identified four essential components that make this possible: a planning...
Build a Research Agent with Deep Agents
Deepagents is a simple, open source agent harness built by LangChain. It uses some common principle seen in popular agents such as Claude Code and Manus, including planning (prior to task execution...
Model Call Limit Middleware (Python)
Learn about how to use LangChain's model call limit middleware as a guardrail for agents. This middleware can be used for single agent invocations or across conversations. We walk through an exampl...
Agents Gone Wild? Use Tool Call Limits in LangChainJS to Keep Them in Check!
In this tutorial, Christian Bromann will show you how to prevent runaway tool usage using the Tool Call Limit Middleware in LangChainJS. You’ll learn how to set clear, declarative limits on tool us...
Building a Research Agent with Gemini 3 + Deep Agents
Google's eagerly anticipated Gemini 3 Pro release shows state-of-the-art performance across a wide range of agentic evaluations. Here, we show how to use Gemini 3 Pro with Deepagents, our open sou...
Model Fallback Middleware (Python)
Learn about how to use LangChain's new model fallback middleware to add resilience to your applications. Automatically switch between models and even providers when an API call fails with just a fe...
Stop Endless Back-and-Forth — Add Model Call Limits in LangChainJS
Is your support agent getting stuck in endless back-and-forth conversations? Users asking the same thing three different ways? Or long chats where the bot clearly isn’t helping anymore? In this tu...
LangChain Academy New Course: LangSmith Essentials
Testing applications is essential to the development lifecycle, but LLM systems are non-deterministic – you can’t always predict how they will behave. Add multi-turn interactions and tool-calling...
To-Do List Middleware (Python)
Learn about how to use LangChain's to-do list middleware to equip agents with task planning and tracking capabilities for complex multi-step tasks. Our example uses a software development agent. M...
Why Most AI Agents Fail — and How a Simple Todo List Fixes It
Most AI agents don’t fail because the model is bad — they fail because they don’t plan. In this video, @christian-bromann from LangChain shows how the TodoListMiddleware gives your agents structure...
Execute code with sandboxes for Deep Agents
We're excited to launch Sandboxes for DeepAgents, a new set of integrations that allow you to safely execute arbitrary code and bash commands in remote sandboxes. Your DeepAgent runs locally (or wh...
Add a Human-in-the-Loop to Your LangChain Agent (Next.js + TypeScript Tutorial)
Bring humans back into the loop 👩💻 — this tutorial shows how to integrate Human-in-the-Loop (HITL) middleware into your LangChainJS agents using createAgent. You’ll learn how to: - Pause agent ex...
Tool Call Limit Middleware (Python)
Learn about how to use LangChain's tool call limit middleware to control an agent's tool calling abilities across single interactions and full conversations. Our example uses a shopping agent that...
How Agents Use Context Engineering
This video covers the core principles of context engineering for AI agents and how they're implemented across popular frameworks like Claude Code, Manus, and LangChain's DeepAgents. As AI agents ta...
Building a Typescript deep research agent
In this video, we will walk through how to easily build a Typescript deep research agent This builds upon our new DeepAgents JS library. All it involves is some detailed prompting, some search too...
Build a Streaming LangChain Agent in Next.js with useStream
Learn how to build a minimal LangChain agent inside a Next.js app using the useStream hook. We’ll stream responses, render human/AI messages, and add conversation memory via a LangGraph checkpointe...
Human in the Loop Middleware (Python)
Learn about how to use LangChain's human in the loop middleware to approve, edit, and reject tool calls before they're executed. Our example uses an email assistant agent that requires human feed...
Why We Built LangSmith for Improving Agent Quality
Harrison Chase (CEO of LangChain) sits down with Bagatur (LangSmith Engineer) and Tanushree (Product Manager) for a technical roundtable on bringing production agents from prototype to rigor. They ...
Deep Agent CLI: Coding Assistant with Memory
Using the deepagents package, we built a simple coding CLI as an example of a coding application you could build on top of deepagents. We added in a concept of memory so that it would remember ins...
Inside LangSmith's No Code Agent Builder
Harrison Chase (CEO of LangChain) sits down with Brace (Applied AI) and Sam (PM) for a technical roundtable on LangChain's first no code agent builder. They share how business users and engineers a...
Get Started with LangSmith Agent Builder
LangSmith Agent Builder (now in private preview) lets anyone create agents through a text-to-agent experience — no coding or prompt engineering required. Just describe what you want in plain langua...
LangChain Academy New Course: LangGraph Essentials
In our newest LangChain Academy course, LangGraph Essentials, you can learn the basics of LangGraph in less than an hour in either Python or TypeScript. LangGraph is a low-level orchestration fram...
LangChain Academy New Course: LangChain Essentials
In our newest LangChain Academy course, LangChain Essentials, you can learn the basics of LangChain in less than an hour in either Python or TypeScript. LangChain is the best way to get started wi...
Get Started with LangSmith Multi-turn Evaluations
Once you have a good sense of the top usage patterns your agent is handling, you can start to drill into how each complete conversation is performing. Multi-turn Evals help you measure whether your...
Building LangChain and LangGraph 1.0
LangChain CEO Harrison Chase sits down with open source engineers Sydney, Hunter, and Will for an in-depth technical discussion on the major 1.0 releases of LangChain and LangGraph. The team explor...
LangChain: Engineer reliable agents
We're launching LangChain 1.0 and LangGraph 1.0 — and announcing our $125M Series B. Building reliable agents has traditionally been hard. What started as frameworks for LLM applications has evolv...
Get Started with Insights Agent in LangSmith
Today's popular agents produce millions of traces per day—soon to be billions. These traces contain valuable signal about an agent's capabilities and how real users engage with it. If you could rev...
Context Engineering for AI Agents with LangChain and Manus
Join us for a deep dive into context engineering – the critical practice that determines how well your AI agents perform in production. Lance Martin from LangChain and Manus co-founder Yichao "Peak...
How We Built it: Clay - Fireside Chat with CEO Kareem Amin
Go behind the scenes with Kareem Amin (CEO of Clay) and Julia Schottenstein (Head of GTM and OPS at LangChain) in this fireside chat from Clay's conference. Discover Clay's philosophy on building A...
Getting Started with LangSmith (3/8): Debugging with Studio
- Code: https://github.com/xuro-langchain/eli5 - Learn more about LangSmith: https://www.langchain.com/langsmith/?utm_medium=social&utm_source=youtube&utm_campaign=q2-2025_onboarding-videos_co - Ge...
Getting Started with LangSmith (2/8): Types of Runs
- Code: https://github.com/xuro-langchain/eli5 - Learn more about LangSmith: https://www.langchain.com/langsmith/?utm_medium=social&utm_source=youtube&utm_campaign=q2-2025_onboarding-videos_co - Ge...
Rewriting Deep Agents on top of LangChain 1.0
In this video, we will walk through how we rebuilt DeepAgents on top of LangChain 1.0. It will cover the basics of deep agents (planning, filesystem, sub agents), and show case a real world and pra...
LangChain Academy New Course: Deep Agents with LangGraph
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...
Adding Human-in-the-Loop to DeepAgents
Many tools that you may want to give to agents will take actions in the real world. For these tools, you will often want to add "human-in-the-loop" steps - require a human user to approve, edit, or...
How PagerDuty Built AI Agents with LangGraph to Transform Incident Management
PagerDuty's engineering team built an AI agent that transforms how teams interact with incident data, replacing dashboard navigation with natural language conversations. Learn how LangGraph's struc...
Using `deepagents` to Build Deep Research (Python)
In this video we will use `deepagents` to build a Deep Research example. This consists of defining a search tool, defining some sub agents, and writing a detailed prompt. Example folder: https://g...
Deep Agents JS
Deep Agents is now in JavaScript! Simple tool-calling loops break down on long-horizon or intricate problems. Deep Agents, like Deep Research, Claude Code & Manus, chain reasoning, adapt plans, an...
LangChain Academy New Course: Deep Research with LangGraph
Deep research agents are taking off – from major AI labs to companies building their own. Research is inherently open-ended. You can't always predict whether a question needs broad exploration or...
Getting Started with LangChain Education
Welcome to LangChain Education! We offer a few different ways to learn – including courses, YouTube videos, and docs. Start diving in below! LangChain Academy: https://academy.langchain.com/?utm_...
Deep Agents UI
Deep agents operate with a todo list, file system, and subagents We built a dedicated UI for running deep agents that properly highlights all of these things! Github: https://github.com/langchain-a...
Testing Driving GPT 5
OpenAI just released GPT-5, their new series of frontier LLMs. Here, we analyze the models, assess reactions from developers, show how to use them, and provide some results from our own testing. O...
Introducing Open SWE: An Open-Source Asynchronous Coding Agent
An async, fully autonomous coding agent. Demo: https://swe.langchain.com GitHub Repository: https://github.com/langchain-ai/open-swe Documentation: https://docs.langchain.com/labs/swe Blog: https...
Tracing Claude Code to LangSmith
You can now trace your claude code sessions to LangSmith! See how to set up tracing from claude code to LangSmith in just a few minutes. Check out the docs for detailed instructions: https://docs....
n8n Tracing to LangSmith
Learn how to quickly set up tracing from n8n to LangSmith! Docs: https://docs.n8n.io/advanced-ai/langchain/langsmith/ Sign up for LangSmith: https://smith.langchain.com/