Loading video player...
I’m excited to announce the release
of our latest LangChain Academy foundations course,
Introduction to LangChain in Python.
We’ve entered a new era of AI, one where our apps don’t just respond,
they think, plan, and act autonomously.
Today, we're building agents – AI systems that can reason
and interact with their environments to get real work done.
Imagine a team of assistants that can summarize your inbox,
schedule meetings, and perform market research 24/7.
In this course, you'll learn to build deployment-ready agents
like these using LangChain.
LangChain is the best way to get started with building agents.
Together with the community, we've learned from production use cases
and identified the essential components an agent needs.
The “create agent” abstraction in LangChain captures these qualities in their simplest form.
In this course, you'll learn how to build agents
using this abstraction and how to customize them with middleware.
The goal of this course is to get you building agents right away.
As we go, we'll assemble a full team of personal assistants,
with each module culminating in a project to build a new one.
In module 1, we're starting with the basics.
Customizing a language model with out-of-the-box arguments
and system prompts,
before adding tools for it to call and short-term memory.
Within 30 minutes, you'll be building a personal chef
that suggests recipes based on pictures of your fridge.
In module 2, your agent will get a little bit more sophisticated
as you learn about MCP, customized memory, and multi-agent systems.
Before you know it, you'll have built an entire team of synchronized
wedding planners using up-to-date flight prices and venue details.
Finally, you'll learn how to level up your agents beyond the prototype stage
using middleware.
This will allow you to customize your agent with dynamic tools, prompts, and models,
introduce human in the loop to gate sensitive actions,
and summarize long conversations to protect your agent's context window.
At the end of module 3, you'll be tasked with creating an email assistant
using middleware that can automate your entire inbox.
We'll then show you a plug and play chat interface you can use to quickly demo
these impressive agents.
I'm excited for you to dive into this new course
and learn how to build agents with LangChain.
You can get started today.
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: https://bit.ly/4pJHThr ➡️ Sign up for LangSmith: https://bit.ly/4s3J3pF