Build a Research Agent with Deep Agents
Skills:
Agent Foundations90%Tool Use & Function Calling80%Research Methods70%Multi-Agent Systems60%Autonomous Workflows50%
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), computer access (giving the able access to a shell and a filesystem), and sub-agent delegation (isolated task execution). We're introducing a new repo with a collection of quickstarts that demonstrate different agents can be easily configured on top of the deepagents harness.
Quickstarts repo:
https://github.com/langchain-ai/deepagents-quickstarts
Learn how to build Deep Agents on LangChain Academy:
https://academy.langchain.com/courses/deep-agents-with-langgraph/?utm_medium=social&utm_source=youtube&utm_campaign=q4-2025_youtube-academy-links_aw
deepagents repo:
https://github.com/langchain-ai/deepagents
deepagents docs:
https://bit.ly/480icl1
deepagents UI:
https://github.com/langchain-ai/deep-agents-ui
Chapters --
0:00 Introduction to DeepAgents
1:00 Agent Trajectory Overview
2:00 Built-in Tools in DeepAgents
3:00 Quick Start Setup Options
4:00 Task-Specific Tools: Search & Think
5:00 Task-Specific Instructions
6:00 Preventing Agent Spin Out
7:00 Custom Prompts & Instructions
8:00 Custom Subagents for Context Isolation
9:00 Workflow Instructions & Delegation Strategy
10:00 Initializing DeepAgent
11:00 Middleware Overview
12:00 Running the Agent in Notebook
13:00 File System Backends
14:00 Subagent Research Output
15:00 LangSmith Tracing
16:00 Deploying with LangGraph Server
17:00 Summary & Key Takeaways
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Building LLM applications with LangChain with Lance
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Benchmarking Question/Answering Over CSV Data
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LangChain "RAG Evaluation" Webinar
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Fine-tuning in Your Voice Webinar
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Tabular Data Retrieval
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Building an LLM Application with Audio by AssemblyAI
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Effectively Building with LLMs in the Browser with Jacob
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Data Privacy for LLMs
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"Theory of Mind" Webinar with Plastic Labs
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Using Natural Language to Query Postgres with Jacob
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Building a Research Assistant from Scratch
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Benchmarking RAG over LangChain Docs
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Skeleton-of-Thought: Building a New Template from Scratch
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Benchmarking Methods for Semi-Structured RAG
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LangSmith Highlights: Getting Started
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LangSmith Highlights: Debugging
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LangSmith Highlights: Datasets
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LangSmith Highlights: Evaluation
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LangSmith Highlights: Human Annotation
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LangSmith Highlights: Monitoring
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LangSmith Highlights: Hub
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SQL Research Assistant
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Getting Started with Multi-Modal LLMs
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Build a Full Stack RAG App With TypeScript
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Auto-Prompt Builder (with Hosted LangServe)
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LangChain v0.1.0 Launch: Introduction
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LangChain v0.1.0 Launch: Observability
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LangChain v0.1.0 Launch: Integrations
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LangChain v0.1.0 Launch: Composability
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LangChain v0.1.0 Launch: Streaming
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LangChain v0.1.0 Launch: Output Parsing
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LangChain v0.1.0 Launch: Retrieval
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LangChain v0.1.0 Launch: Agents
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Build and Deploy a RAG app with Pinecone Serverless
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Hosted LangServe + LangChain Templates
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LangGraph: Intro
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LangGraph: Agent Executor
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LangGraph: Chat Agent Executor
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LangGraph: Human-in-the-Loop
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LangGraph: Dynamically Returning a Tool Output Directly
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LangGraph: Respond in a Specific Format
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LangGraph: Managing Agent Steps
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LangGraph: Force-Calling a Tool
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LangGraph: Multi-Agent Workflows
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Streaming Events: Introducing a new `stream_events` method
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Building a web RAG chatbot: using LangChain, Exa (prev. Metaphor), LangSmith, and Hosted Langserve
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OpenGPTs
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Open Source RAG with Nomic's New Embedding Model (and ChromaDB and Ollama)
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LangGraph: Persistence
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Chapters (18)
Introduction to DeepAgents
1:00
Agent Trajectory Overview
2:00
Built-in Tools in DeepAgents
3:00
Quick Start Setup Options
4:00
Task-Specific Tools: Search & Think
5:00
Task-Specific Instructions
6:00
Preventing Agent Spin Out
7:00
Custom Prompts & Instructions
8:00
Custom Subagents for Context Isolation
9:00
Workflow Instructions & Delegation Strategy
10:00
Initializing DeepAgent
11:00
Middleware Overview
12:00
Running the Agent in Notebook
13:00
File System Backends
14:00
Subagent Research Output
15:00
LangSmith Tracing
16:00
Deploying with LangGraph Server
17:00
Summary & Key Takeaways
🎓
Tutor Explanation
DeepCamp AI